Matching GPS points to the road network

Matching GPS points to the road network

I am a newbie in Postgres and Postgis and I am trying to do a matching of GPS points to the road network. I need to find closest road from a shapefile and take speed attribute from it. I am using postgreSQL 9.3.7 and postgis 2.1.7.

I have imported a shapefile of the road network into my database. There are many columns, among others: speedlimit, rlid, startdate, enddate, startdistance, enddistance, direction and geom.

I feel unsure about SRID. When I plugged the contents of the .prj file into, I got 3006 - SWEREF99_TM as result, and that's what I used to import the shapefile. But I don't know if I need to transform it to 4326, because GPS-points I want to match are longitude and latitude I got from Google maps.

The query:

select distinct(ST_SRID(mytable.geom)) as srid, count(*) from mytable group by srid;

gives: 3006; 2674798

null; 930

I found some solutions and tried them:

Query 1:

SELECT speedlimit, ST_Distance(ST_GeomFromText('POINT(lat long)',3006),geom) AS distance FROM mytable ORDER BY distance ASC LIMIT 1;

70;6146326.22657711 (this query always gives same result, even if I change GPS points)

Query 2:

SELECT ST_makePOINT(lat long) as gps_point, ST_Distance( ST_Closestpoint( st_setSRID(r.geom,4326), st_setSRID(ST_makePOINT(lat long),4326) ) , ST_makePOINT(lat long) ,true ) as distance_with_c_p, r.speedlimit FROM mytable r WHERE (ST_Distance_Spheroid (st_setSRID(r.geom,4326),st_setSRID(ST_makePOINT(lat long),4326) , 'SPHEROID["GRS 1980",6378137,298.257222101]') < 100 ) ORDER BY 2 LIMIT 5

"01010000008849B89047D64C408FFE976BD1222840";1088667.79697218;50 "01010000008849B89047D64C408FFE976BD1222840";1088667.79697218;50 "01010000008849B89047D64C408FFE976BD1222840";3784055.84203355;110 "01010000008849B89047D64C408FFE976BD1222840";5163241.18884849;80 "01010000008849B89047D64C408FFE976BD1222840";5163241.18884849;80

Query 3:

with index_query as ( select st_distance(geom, 'SRID=3006;POINT(lat long)') as distance, mytable.speedlimit from mytable order by geom <#> 'SRID=3006;POINT(lat long)' limit 100 ) select * from index_query order by distance limit 1;

6146326.22657711;70 (this query also gives same result even if I change GPS points)

I don't understand why the nearest distance always is so far away. GPS points are taken from the main roads, and I tested several GPS points.

Is it something about SRID, or what am I doing wrong?

If you want a distance in meaningful units, you'll want toST_Transformyour GPS points from 4326 to the target projection. ThenST_Distancewill give you results in the units of the projection (usually metres, but some North American projections use survey feet instead).

So, instead ofST_GeomFromText('POINT(lat long)',3006), you'd want something likeST_Transform(ST_SetSRID(ST_Point(long,lat),4326),3006).

For performance, you might want to consider creating and indexing a column of the GPS geometry if you'll be using it repeatedly.

Please see the code below:

with index_query as ( select st_distance(geom, 'SRID=4326;POINT(long lat)') as distance, mytable.speedlimit from mytable order by geom <#> 'SRID=4326;POINT(long lat)' limit 100 ) select * from index_query order by distance limit 1;

Please notes that SRID = 4326 and also switch the "lat long" to "long lat"

Chartered Surveyor is the description (protected by law in many countries) of Professional Members and Fellows of the RICS entitled to use the designation (and a number of variations such as "Chartered Building Surveyor" or "Chartered Quantity Surveyor" or "Chartered Civil Engineering Surveyor" depending on their field of expertise) in Commonwealth countries and Ireland.

Civil engineering is a professional engineering discipline that deals with the design, construction, and maintenance of the physical and naturally built environment, including works such as roads, bridges, canals, dams, airports, sewerage systems, pipelines, and railways.

Data source of spatial interpolation

Data sources for continuous surface spatial interpolation include:

Orthophoto or satellite images obtained by photogrammetry

Scanning images of satellites or space shuttles

Sampling data are measured in the field. Sampling points are randomly distributed or regularly linearly distributed (along profiles or contours).

Digitized polygon and contour maps

Spatially interpolated data is usually measured data of sampling points with limited spatial variation, these known measurement data are called “hard data”. If the sampling point data is relatively small, spatial interpolation can be assisted according to the known information mechanism of a natural process or phenomenon that causes some spatial change, this known information mechanism is called “soft information”. However, in general, due to the unclear mechanism of this natural process, it is often necessary to make some assumptions about the spatial variation of the attributes of the problem, such as assuming that the data changes between sampling points are smooth, and assuming that the relationship between distribution probability and statistical stability is obeyed.

The spatial position of the sampling points has a great influence on the results of spatial interpolation, ideally, the points are evenly distributed in the study area. However, when there are a large number of regular spatial distribution patterns in the regional landscape, such as regularly spaced numbers or ditches, it is clear that a completely regular sampling network will yield a one-sided result, for this reason, statisticians hope to pass some random sampling to calculate the unbiased mean and variance. But completely random sampling also has its drawbacks, firstly, the distribution of random sampling points is irrelevant, while the distribution of regular sampling points only needs a starting point, direction and fixed size interval, especially in complex mountains and woodlands. Secondly, completely random sampling will result in uneven distribution of sampling points, data density of some points, and lack of data of other points. Figure 8-15 lists several options for spatial sample point distribution.

Figure 8-15: Various sampling methods

A good combination of regular sampling and random sampling is layered random sampling, i.e. individual points are randomly distributed in the regular grid. Aggregated sampling can be used to analyze spatial variations at different scales. Regular cross-section sampling is often used to measure River and hillside profiles. Isoline sampling is the most commonly used method for digital contour interpolation of digital elevation model.

Term: A property value of a data point, which is one of all measurement points. It is the value of a point x0after interpolation. If an interpolation method calculates data in which the calculated data of the sampling point is equal to the known sampling data, the interpolation method is called an exact interpolation method all other interpolation methods are approximate interpolation methods, the difference between the calculated and measured values (absolute and squared), - which is a commonly used indicator for evaluating the quality of inexact interpolation methods.

Thinking Geographically

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Comments (Show all 54 )

Justin Zhang said

Human Environment - The second theme of geography as defined by the Geography Educational National Implementation Project the reciprocal relationship between humans and environment.

Example: Irrigation systems, such as those in early civilizations in Egypt and China and other parts of the world, brought water from nearby sources to where crops were grown, enabling the civilizations to expand and grow.

Bibiana Toro said

Period 4
Distance: measurement of the physical space between two place. ex: geographers might map the distance between to places in order to determine how far they are from each other and the probability of their cultures diffusing.
Medical Geography: the study of health and disease within a geographic context and from a geographical perspective. Looks at sources, diffusion routes and distribution of disease. ex: currently this would be implemented in Africa in a case where researchers might examine Ebola and identify its source and ways it travels and how it diffuses thus what you could do in a community to help stop its spread

Clayton McDonald said

Fieldwork: The study of geographic phenomena by visiting places and observing how people interact with and thereby change those places.
Ex: A geographer travels to Egypt to study how the Egyptian people crowd around and rely on the Nile River.

Pattern: The design of a spatial distribution.
Ex: Urban areas seem to be more packed and bustling, whereas rural areas are generally more spread out and more slowed down.

Stimulus Diffusion: A form of diffusion in which a cultural adaptation is created as a result of the introduction of a cultural trait from another place.
Ex: When Korea was inhabited by the Japanese around the time of World War Two, the Japanese spread all of their culture traits to Korea and forced them to accept them.

Clayton McDonald said

Qiji lian said

9-1Cultural ecology: studies the relationship between a given society and its natural environment as well as the life-forms and ecosystems that support its lifeways.
Example, in the Hindu culture, one of the central points of worship is the cow. people in India needed cows for milk and cultivation, needs that were essential for their survival. Westerners think that Indians would rather starve than eat their cows. What they don't understand is that they will starve if they do eat their cows. This incorporates cows into their religion, making them sacred. but ultimately keeping them alive so that they can be used in farming and for milking.
9-2human geography: the study of the interaction between human beings and their environment in particular places and across spatial areas.
Example: the study of the culture, economy&hellip of a place.
9-3Relative location : refers to the position of a place or entity based on its positive with respect to other locations.
Example, the location of the US Capitol is located about 38 miles southwest of Baltimore.

Vinuthna Garidipuri said

Period 4
Cartography: The study and practice of making maps
Ex: Combining science, aesthetics, and technique, cartography builds on the premise that reality can be modeled in ways that communicate spatial information effectively.

Geographic concept: Ways of seeing the world spatially that are used by geographers in answering research questions.
Ex: Basic geographic concepts are:Location, Region, Place (physical and cultural attributes), Density, Dispersion, Pattern, Spatial Interaction, and Size and Scale.

Place: a description of the characteristics that make a certain location distinct. Physical characteristics include landforms, vegetation, and climate. Human characteristics include culture, economy, and government. Every place has a unique combination of physical and human characteristics.
Ex: The Great Pyramid of Giza has characteristics such as sand, heat, and the presence of a large pyramid.

Keon Ahn said

Accessibility: The degree of ease with which it is possible to reach a certain location from other locations. Accessibility varies from place to place and can be measured.
Example: From Seven Lakes, it is much easier to shop at Katy Mills rather than at Memorial City Mall because Seven Lakes is closer to Katy Mills than Memorial City Mall.

Location Theory: A logical attempt to explain the locational pattern of an economic activity and the manner in which its producing areas are interrelated.
Example: The agricultural location theory contained in the von Thünen model suggests that the accessibility to the market can create a system of agricultural land use.

Alice Wang said

Epidemic:a widespread occurrence of an infectious disease in a community at a particular time
Ex:Smallpox was brought over to the Americas on European ships in the late 1600s and decimated local Native American populations.

Movement: refers to the way people, products, information and ideas move from one place to another
Ex:It is believed humans trekked over to North America on a land bridge during the Ice Age.

Spatial interaction:the flow of goods, people, or information among places, in response to localized supply and demand, usually depends upon distances,accessibility,transportation, and communication connectivity
Ex: A person gets up early every Saturday and drives 6 minutes to the bakery so he/she can buy fresh bread.

Vishal Gupta said

Period 5
13-1 Culture Complex: A group of traits that a particular culture lives by or takes part in, they use them to define the culture

Ex: In India religion forbids the consumption of beef. This qualifies as a culture complex as it is evident all throughout India

13-2 Possibilism: the theory that the physical environment may set limits on human actions, but people have the ability to adjust to the physical environment and choose a course of action from many alternatives

Ex: Building bridges to pass large bodies of water.

Paul Zmick said

Period 5:
Landscape- The overall appearance of an area. Most landscapes are comprised of natural and human-induced influences.
Example- Katy's landscape used to be characterized by rice fields, but is now characterized by booming neighborhoods and growing businesses.

Tofe Alimi said

Period 5:
Connectivity - the degree of linkage between locations in a network
Example - The level of connectivity is high between Houston and its suburbs such as Katy and Sugarland.

Movement - the mobility of people, goods, and ideas across the surface of the planet
Example - There is an increasingly large movement of people into suburban as opposed to urban areas.

Shreya Gupta said

Period 5:
Culture - the beliefs, customs, arts, etc., of a particular society, group, place, or time
Political ecology - study of the relationships between political, economic, and social factors with environmental issues and changes

Shreya Gupta said

example of culture - in the indian culture, the bride and groom must take 7 rounds around the holy fire to symbolize a binding of 2 lives for 7 lifetimes
example of political ecology - terraced rice fields in Yunnan, China, evidence how the environment is shaped by and shapes economy and society

Nahal Iranpour said

Cultural barrier: Prevailing cultural attitude rendering certain innovations, ideas or practices unacceptable in that particular culture.
Example: Religious teachings may not support certain practices such as divorce, abortion, etc.

Globalization: The expansion of economic, political, and cultural processes to the point that they become global in scale and impact. The processes of globalization transcend state boundaries and have outcomes that vary across places and scales.
Example: The Silk Road allowed exchange of culture,goods, and knowledge.

Reference maps: Maps that show the absolute location of places and geographic features determined by a frame of reference, typically latitude and longitude.
Example: A map that displays general reference features like boundaries, cities, capitals, rivers and lakes.

Suchi said

Activity Space: places we travel to routinely in our rounds of daily activities.
Example: The Starbucks that's 5 minutes away lies within my activity space.
Geocaching: an increasingly popular hobby based on the use of GPS.
Example: Geocaching has been used increasingly to play treasure hunt indoors.
Physical Geography: branch of geography dealing with natural patterns & processes
example: land formations, climate, currents, and distribution of flora and fauna of a place

Bryce Griffin said

Period 5 - #11
Cultural Landscape: cultural properties that represent the combined works of nature and man
Example: Mt Rushmore

Place: All of the characteristics, usually physical, of an area that distinguish it from any other area
Example: School as a place includes books, halls, teachers, students, lessons, white boards, pencils, essays, math problems, instruments, theater productions, sports matches or games, etc.

Karen Tai said

Culture Complex - A culture complex is a related set of cultural traits, which consists of a discrete combination of traits.
Example: All the things Americans do: prevailing dress codes and cooking and eating utensils

Location - Location is the first theme of geography and is the geographical situation of people and things. It highlights how the geographical position of people and things on Earth's surface affects what happens and why.
Example: The Empire State Building is located at 40.7 degrees north (longitude), 74 degrees west (latitude). It sits at the intersection of 33rd Street and Fifth Avenue in New York City, New York.

Sense of Place - A sense of place is a state of the mind derived through the infusion of a place with meaning and emotion by remembering important events that occurred in that place or by labeling a place with certain character.
Example: You feel happy in your hometown because it gives you a sense of "home" and it reminds you of fond memories that you had there.

Faith Banjoko said

Period 5
1. Cultural Barrier: Cultural attitude causing certain ideas, innovation, or practices unacceptable to surrounding cultures.
ex. Cultural conflicts between Israel and Palestine

2. Pattern: The arrangement of spatial distribution
ex. How malnourishment percentage is lower in areas with more power and wealth across the world

Tyler Takeyama said

Period 5
Global Positioning System (GPS)- a satelite system in which is used to determine the location of a person, a geographic feature or an object.

Ex: GPS is used in cars and cell phones to determine the absolute location and guide them to their destination.

Spatial perspective - an observation that looks at particular phenomena and thinks about how and why that phenomena is happening and how interacts with others

Ex: when a store manager decides to open a store, he looks at the income of the neighborhood, and its population to determine which place is most suited for the store to open.

Luke Heffernan said

fifth period
Culture Trait: A single distinguishing feature of regular occurrence in a culture. For example, ways of eating, clothing worn by certain people based on their gender or social rank.
Reference Maps: A map that has reference information for a particular place, helping to find landmarks and navigating especially. Example, a map that includes national parks and unique features of the land, other things that would hep navigate through the area.

Naveen Chokkar said

Cultural Diffusion: spread of cultural items,like ideas, styles, religions, technologies, languages etc. between individuals, whether within a single culture or from one culture to another.
EX: Christianity, a religion beginning in Europe, eventually spread and grew to dominate the New World, as well.

Perception of Place: Belief or "understanding" about a place developed through books, movies, stories or pictures.
EX. Texas is identified by citizens of various other states, as a place where people speak with a southern drawl, always carry revolvers, and use the contraction "y'all" excessively.

Haris said

5th period- #15
Region: areas of broadly divided by physical characteristics, human-impact characteristics, and the interaction of humanity and the environment
EX: the middle east

Distance: distance measured along the surface of the earth
EX: miles, meters, kilometers

Sharon Xu said

Period 5- #27
Hierarchical Diffusion: A form of diffusion in which an idea or innovation spreads by passing first among the most connected places or peoples
Ex: Fashion trends are often first established in urban areas and spread by celebrities who have a high influence to other urban areas.

Thematic Maps: A type of map especially designed to show a particular theme connected with a specific geographic area.
Ex: A map that displays the average rainfall in an area

Deborah galvin said

<5th period>
Cultural Ecology- The study of human adaptions in a given society, including biological and cultural processes, to social and physical environments.

Perceptual Region- Places that seem to reflect sympathetic feelings or any other emotion, these regions also can be seen as places people have believed at one point to be a part of their cultural identity.

Zion Mpeye said

Five Themes:
1. Location - Highlights how the geographical position of people and things on Earth's surface affects what happens and why. It helps to establish the context within which events and processes are situated.
Ex: As the San Andreas fault line runs through California, it is susceptible to earthquakes.
2. Human-Environment Interactions - Considers how humans adapt to and modify the environment, looking at the reciprocal relationship between humans and environments which can have positive and/or negative effects on the environment.
Ex: The construction of the Chunnel underneath the English Channel, a rail tunnel linking England and France.
3. Region - An area that has certain unifying characteristics such as climate, language, or history.
Ex: Arizona, Texas, Oklahoma, and New Mexico are identified as being in the southwest region of the United States.
4. Place - The unique physical and human characteristics of a location.
Ex: New York City is known for having tall skyscrapers.
5. Movement - The mobility of people, goods, and ideas across the surface of the planet.
Ex: The dispersion of people from Louisiana in 2005 when Hurricane Katrina hit.

Sense of Place: The state of mind derived through the infusion of a place with meaning and emotion by remembering important events that occurred in that place or by labeling a place with a certain character.
Ex: For most people, The National September 11 Memorial and Museum will always be a somber place.

David Akpedeye said

(5th Period)
Cartography- The art and science of making maps, is as old as geography itself.
Ex:The Arab geographer Muhammad al-Idrisi produced his medieval atlas Tabula Rogeriana in 1154. He incorporated the knowledge of Africa, the Indian Ocean and the Far East

Mental Map- Is a map that every human being carries in their mind, which contains every place they have heard of or been to.
Ex: If your friend calls and asks you to meet her at the movie theater, you envision the hallway, the front door, the walk to the car, and the lane to choose in order to be prepared to turn left , and your path into the theater and up to the pop-corn stand.

Jessie Miller said

Expansion diffusion- The spread of an innovation or an idea through a population in an area in such a way that the number of those influenced grows continuously larger, resulting in an expanding area of dissemination
Ex: Since coming about, the internet has become increasingly popular and spread through different continents and demographics

Remote sensing- A method of collecting data or information through the use of instruments that are physically distant from the area or object of study
Ex: satellites in outer space collect information about the earth's surface and atmosphere

Eva Patel said

(5th period)
Formal region: A region with one or more shared traits, such as cultural or physical traits. Changes when the scale of analysis shifts.
Ex: A region where Spanish is spoken by the majority of people would be a Spanish-speaking region.

Sequent Occupance: The theory that occupants of a region leave successive cultural imprints, layering and affecting the next occupants.
Ex: The Parthenon in Greece, originally a temple dedicated to Athena, reflects cultural changes. It was converted to a Christian church in the 5th century A.D., and later converted to a mosque when the Ottomans conquered.

Rolland Zhang said

(5th Period)
Independent invention: A trait develops in more than one cultural hearth, or area without being influenced by another hearth.
Ex: Agriculture began independently in different places such as Southern China, Africa's Sahel and parts of India without being influenced by each other.

Yumei Li said

(5th Period)
epidemic : the regional outbreak of disease

Ex: Black Death decimated fourteenth-century Europe.This outbreak killed a third to more than a half of the population of Europe.

Relocation diffusion: Sequential diffusion process in which the items being diffused are transmitted by their carrier agents as they evacuate the old areas and relocate the new ones.
The most common form of relocation diffusion involves the spreading of innovations by migrating population.

Ex:The migration of Christianity with European settlers who came to America.

Karl Kim said

environmental determinism
- human behavior, individually and collectively, is strongly affected by, even controlled or determined by, the physical environment.

ex) both Aristole and Cushing suggested climate as the critical factor in how humans behave. However this was false because they had
different ideals of climates that give a better characteristic . For Aristole it was the climate of the Greece and Cushing stated more recent commentators from Western Europe and North America.

-the location of a place in relation to other human and physical features.

ex) When you are explaining Katy to a foreigner it's better to give them a relative location such as the suburban area of Houston than
explaining Katy by absolute location , the cordiantes.

Pranav Agrawal said

5th period
Absolute Location- The exact location of a place or geographic feature using a coordinate system (longitude and latitude)
ex: Airplane pilots use absolute location when flying to their destination with a gps system, they might be flying to an airport in Houston and use the coordinates 29.9844° N, 95.3414° W.

Pranav Agrawal said

5th period
Location- a term used to identify a point or area on the Earths surface, it is more exact than the term "place" and less ambiguous.
ex: Seven Lakes High School is located in Katy TX.

Isabel Alonzo said

Accessibility: the opportunity and degree of ease for interaction between one location and another.
Example: 12,000 years ago during the last ice age, ocean levels dropped to reveal a land bridge known as Beringia between Russia and Alaska. It is believed that this land bridge allowed for the inhabitation of the Americas therefore, increasing accessibility to new land. This spread culture and created new opportunities for those entering America.

Formal Region: a region with clearly established borders and undisputed boundaries.
Example: the contiguous United States is a formal region, as it has official borders and a set territory.

Perceptual Region: a region defined by a person's perception of a specific area, which can be affected by their own personal knowledge and viewpoints of a regions culture, religion, etc. This region is not established by borders.
Example: the perceptual region of "the south" is associated with and viewed to be a group of horse-riders and cowboys living in the desert.

Time Distance decay: the declining degree of acceptance of an idea with increasing time and distance the decreasing interaction between locations as distance increases.
Example: all of the land forms surrounding the Mediterranean Sea were so valuable because they allowed for a decrease in distance between locations when travelling by sea. When an empire had control of the Mediterranean Sea, trade flourished due to increased interaction. This increased interaction was largely due to the accessibility of new locations and the decreasing of distance decay, providing an explanation as to why empires such as Byzantium were so successful during their rule.

Peder H. Sverdrup said

4th #12
Edit to definition of rescale:
Rescale:Involvement of players (external factors) at other scales to generate support for a position or initiative.
Example:the Kony 2012 campaign, shedding light on a regional scale issue of central Africa and getting attention and support on a global scale through the use of Youtube, and Facebook.

[email protected] said

at 10:18 am on Jan 13, 2015

Sandra Tran: Vocab. Environment determinism-belief that the physical environment sets limits on human social development *Geographical hindrance to humans such as deserts* Mental Map-Image of the way space is organized as determined by an individual's perception impression, and knowledge of that space *Remembering the path to go home everyday relies on mental map* Spatial distribution- physical location of geographic phenomena across space *Police departments color code a city-map by the number of crimes*

[email protected] said

Bhavana Gollapudi from your 5th period.

10.) Cultural hearth- is an area where cultural traits develop (point of origin) and from which traits diffuse (where culture is a certain group's particular way of life).

Example: the Nile river valley or Indus River valley.
Or the religion, Islam (cultural trait) can be traced back to one single place and time

10.) Physical geography- spatial analysis of the structure, processes, location of climate, soil, plants, animals and topography (Earth's natural phenomena).

Example: physical phenomena- landforms and environmental changes
Human environmental interaction

[email protected] said

David Yuan
Period 5
Human Geography- the study of the interaction between human beings and their environment in particular places and across spatial areas.
Ex. The movement of African American population in the United States after the Civil War
Time Distance Decay- The declining degree of acceptance of an idea or innovation with increasing time and distance from its point of origin or source.
The adoption of cultural practices decreases the further you look from the practices&rsquo original location

Yumei Li said

Does anyone know what is the extra credit?

[email protected] said

Karl Kim said
at 12:33 am on Jan 9, 2015
5 period

environmental determinism
- human behavior, individually and collectively, is strongly affected by, even controlled or determined by, the physical environment.

ex) both Aristole and Cushing suggested climate as the critical factor in how humans behave. However this was false because they had
different ideals of climates that give a better characteristic . For Aristole it was the climate of the Greece and Cushing stated more recent commentators from Western Europe and North America.

-the location of a place in relation to other human and physical features.

ex) When you are explaining Katy to a foreigner it's better to give them a relative location such as the suburban area of Houston than
explaining Katy by absolute location , the cordiantes.

Charlie Haaga said
at 8:15 am on Jan 9, 2015
Charlie Haaga 4th Period

Connectivity - The degree of linkage between locations in a network
Geographic Information System - A collection of compute hardware and software that permits spatial data to be collected, recorded, stored, retrieved, manipulated, analyzed, and displayed to the user.
Political Ecology - an approach to studying nature - society relations that is concerned with the ways in which environmental issues both reflect, and are the result of, the political and socioeconomic contexts in which they are situated.

1. Introduction and background

The rate of population growth in urban regions is increasing rapidly with increased urban–rural migrations, especially in developing countries. As such, towns and cities are expanding without regards to the future development plan rules and scenarios, more so with regards to the generated waste (Brockerhoff 2000 ). The increased consumption of different natural and man-made composite resources in these urban areas results in huge quantities of refuse and other waste materials that must be properly managed, if sustainable growth is to be realized. Traditionally, there have been some ways of disposing urban-produced waste, of which one of the most coherent ways is dumping in suitable landfills (e.g., decommissioned quarries) outside the towns or cities (Kohbanani et al. 2009 ).

Although waste disposal in most towns and cities is done in the simple form of landfill deposing, less attention has been paid to the use of expert and engineering knowledge to find the most optimal waste disposal site in municipal solid waste management (MSWM). One of the most important aspects in well engineered waste disposal siting is the determination of a long-term optimal waste depot location (Awomeso et al. 2010 ).

Landfill site selection can generally be divided into two main steps: the identification of potential sites through preliminary screening, and the evaluation of their suitability based on environmental impact assessment, economic feasibility, engineering design, and cost comparison (Karadimas and Loumos 2008 ). As a consequence, landfill siting can be classified as a difficult, complex, tedious, and protracted process (Allanach 1992 ).

Many siting factors and criteria should be carefully organized and analyzed by experts. An initially chosen candidate site may be later abandoned because opposition arises due to previously neglected but important factors. Such a delay increases costs and postpones the final decision of a landfill site. The ‘not in my backyard’ and ‘not in anyone's backyard’ phenomena is becoming popular nowadays creating a tremendous pressure on the decision-makers and experts involved in the selection of a landfill site, as inappropriately sited waste facility may adversely affect the surrounding environment and other economic and socio-cultural aspects (Chang et al. 2008 ).

The criteria used for preliminary site screening are primarily to examine the proximity of potential sites with respect to geographic objects that may be affected by the landfill siting (e.g., rivers, ground-water wells) or that may affect landfill operations (e.g., areas with steep slopes). Methodologies used are normally based on a composite suitability analysis using thematic map overlays (O'Leary et al. 1986 ), and their extension to include statistical analysis (Anderson and Greenberg 1982 ). With advancements of geographical information systems (GIS), landfill siting process is increasingly based on more sophisticated spatial analysis and modeling. Jensen and Christensen ( 1986 ) demonstrated the use of a raster-based GIS with its associated Boolean logic map algebra to identify potential waste sites based on suitability of topography and proximity with respect to key geographic features. The utilization of GIS for a preliminary screening is normally carried out by classifying an individual map, based on selected criteria, into exactly defined classes or by creating buffer zones around geographic features to be protected. All map layers are then intersected so that the resulting composite map contains two distinct areas (Kao et al. 1997 ). It is worth noting that concepts of GIS spatial analyses were initiated by McHarg ( 1969 ) in his Richmond Parkway studies.

Multifaceted decision-making approaches using multi-criteria decision-making and the relevant methods were developed and applied with more or less success depending on the specific problem. In the past, analytic hierarchy process (AHP) (Saaty 1994 ) was one of the useful methodologies, which plays an important role in alternatives selection (Fanti et al. 1998 , Labib et al. 1998 , Chan et al. 2000 ). AHP is an analytical tool that enables explicit ranking of tangible and intangible criteria against each other for the purpose of selecting priorities. The process involves structuring a problem from a primary objective to secondary levels of criteria and alternatives. Once the hierarchy has been established, a pairwise comparison matrix of each element within each level is constructed. AHP allows group decision-making, where group members can use their expertise, experience, and knowledge to break down a problem into a hierarchy and solve it by the AHP steps. Participants can weigh each element against each other within each level, each level is related to the levels above and below it, and the entire scheme is tied together mathematically. For evaluating the numerous criteria, AHP has become one of the most widely used methods for the practical solution of multi-criteria decision-making problems (Cheng 1997 , Akash et al. 1999 , Chan et al. 2000 ). The main difficulty arises in the estimation of the required input data that express qualitative expert observations and preferences. The AHP is mainly used in nearly crisp decision applications and does not take into account the uncertainty associated with the mapping of people's judgment to an evaluation scale (Chen 1996 , Hauser and Tadikamalla 1996 , Cheng 1997 ). To overcome the shortcomings of the crisp AHP, this study proposes a weighted multi-criteria decision analysis (MCDA) and GIS in determining the most optimal alternative for landfill siting.

This association of MCDA and GIS not only permits us to manage the spatial reference information but also to apply analysis methods permitting to have the most pertinent and most profitable information at spatial-temporal scales. The MCDA-GIS hybrid approach uses MCDA to take into account not only the traditional quantitative criteria, but also the qualitative and imprecise criteria, from experts, for site localization. The objective of this study is to develop a landfill siting methodology that integrates the MCDA, which is the AHP and weighted linear combination method, within a GIS environment. This proposed approach, detailed in Section 3, is applied to Eldoret Municipality (EM) in Kenya, with the aim of evaluating the potential areas for landfill siting within the municipality, and proposes the most suitable area for siting a new landfill by integrating relevant siting determinants.

Eldoret Town, with more than 500,000 residents, is an industrial and agricultural town located in the Rift Valley, western part of Kenya. Despite its rapid growth in population and economic activities, the town has never been equipped with an organized ravage system, and consequently garbage and other refuse materials are mostly discarded outside of the town, without applying any specific managed strategy. Such an unsuitable procedure has inflicted substantial damage on the environment (Photo 1).

A megrendelt területről a kért részletességgel felmérést végzünk, majd a felmért adatbázisból 3D térképet készítünk, melyet a megrendelő digitális formában kap meg. »

A megrendelőtől kapott tervek vagy földhivatalból megrendelő kérésére beszerzett adatok alapján a kért pontokat rövid határidővel a helyszínen kitűzzük, a részletpontokat megjelöljük, vagy külön kérésre állandósítjuk. »

Smart parking in IoT-enabled cities: A survey

The rapid growth in population has led to substantial traffic bottlenecks in recent transportation systems. This not only causes significant air pollution, and waste in time and energy, but also signifies the issue of the autopark scarcity. In the age of Internet of Things (IoT) and smart city ecosystems, smart parking and relevant innovative solutions are necessary towards more sustainable future cities. Smart parking with the help of sensors embedded in cars and city infrastructures can alleviate the deadlocks in parking problems and provide the best quality of services and profit to citizens. However, several design aspects should be well investigated and analyzed before implementing such solutions. In this paper, we classify the smart parking systems while considering soft and hard design factors. We overview the enabling technologies and sensors which have been commonly used in the literature. We emphasize the importance of data reliability, security, privacy and other critical design factors in such systems. Emerging parking trends in the ecosystem are investigated, while focusing on data interoperability and exchange. We also outline open research issues in the current state of smart parking systems and recommend a conceptual hybrid-parking model.

1. Introduction The idea of smart parking was introduced to solve the problem of parking space and parking management in megacities. With the increasing number of vehicles on roads and the limited number of parking spaces, the congestion of vehicles is inevitable. This congestion would lead to driver aggression as well as environmental pollution. These factors may worsen particularly during peak hours where the flow density is at its maximum, locating a vacant parking spot is near to impossible. A recent report by INRIX (Cookson, 2019) shows that on average, a typical American driver spends 17 h a year looking for a parking space. However, looking at a major city such as New York this figure is much higher. According to the report, New York drivers spend 107 h per year searching for parking spots. Taking into account the amount of fuel spent during this period, significant levels of the emissions and the harmful gases are expected to appear. Identifying these problems and trying to resolve them in a manner that is effective and at the same time sustainable is a challenging task. In the context of a smart city ecosystem, inputs from elements such as vehicles, roads and users have to be networked and analyzed together in order to provide the best service in fast and secure manners (Gohar, Muzammal, & Ur Rahman, 2018). One of the reasons for marching towards a smart city ecosystem is to use the potential of

existing technologies and infrastructures in providing the best utility to users and improving their future. With the help of IoT applications, mobility and transportation are considered to be the key influencing factors in sustaining our surrounding environments, especially those which utilize intelligent transportation systems (ITS) (Bibri, 2018). One of the key components in ITS is the Smart Parking System (SPS), which relies significantly on analyzing and processing the realtime data gathered from vehicle detection sensors and the radio frequency identification (RFID) systems that are placed in parking lots to report the absence and/or presence of a vehicle. These sensors have their strengths and weaknesses in certain areas where they are deployed. In addition, there might be issues in data anomalies and discrepancies where the collected information does not always conform to the initially expected pattern. This could potentially lead to a less reliable system. Moreover, security and privacy issues of the data transmitted and/or received must be carefully treated. Several factors such as communication and data encryptions must be well investigated in advance before implementing such systems. These subjects have to be seriously considered as the data collected from these sensors might be used in several critical scenarios such as, the parking space prediction in emergencies, and the path optimization in self-driven cars. Any vulnerability in these scenarios, no matter how significant/insignificant they are, can potentially lead to personal information leakage and

Corresponding author. E-mail address: [email protected] (F. Al-Turjman). Received 27 December 2018 Received in revised form 14 May 2019 Accepted 14 May 2019 Available online 28 May 2019 2210-6707/ © 2019 Elsevier Ltd. All rights reserved.

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Table 1 List of used abbreviations. Abbreviation


Agent Based Guiding System Artificial Intelligence Anisotropic Magneto-Resistive Advanced Public Transport System Automated Vehicle Identification Centralized Assisted Parking Search Closed-Circuit Television Car Park Occupancy Information System Short-Range Communication Elliptic Curve Cryptography Electric Vehicle First Come First Serve Frequency-Modulated Continuous Wave Generative Adversarial Network Geographic Information System Global Positioning System Industrial Internet of Things Inductive loop detector Internet of Things Internet of Vehicles Intelligent Transportation system Light Dependent Resistor Long Range Wide Area Network Low-Power Wide-Area Network Long-Term Evolution Mobile Ad Hoc Network Micro Aerial Vehicle Machine Learning


Message Queuing Telemetry Transport Mobile Storage Nodes Non-Assisted Parking Search Narrowband Internet of Things Opportunistically Assisted Parking Search On Board Unit Open Data Format Open Messaging Interface Parking Guidance and Information System Parking Lot Recharge Scheduling Parking Reservation System Quality of Life Quality of Service Radio-Frequency Identification Roadside Unit Software Defined Network Smart Parking System Scalable Vector Graphics Transit Based Information System Unmanned Aerial Vehicles Vehicle to Infrastructure Vehicle to Roadside Vehicle to Vehicle Vehicle Ad Hoc Networks Vehicle-In Motion Variable Message Sign Wireless Sensor Network

increase the risk of security attacks. Considering the aforementioned aspects can significantly enhance the experience of both the parking lot operators (by maximizing their revenues), and the SPS users (by easily searching, booking and paying in advance for their parking lot). Accordingly, any smart application in the current smart city ecosystem has to be context-aware and has to adapt dynamically to contiguous changes. In (Lu, Lin, Zhu, & Shen, 2009), authors presented the main motivations in carrying smart devices and the correlation between the user surrounding context and the used application. They focused on contextawareness in smart systems and space discovery paradigms. New generations of real-time monitoring in SPS have recently been discussed and gained attention, as well. Vehiculer Ad Hoc Networks (VANET), in which vehicles are communicating with other nearby vehicles as well as roadside units, play a key role in SPS while providing a real-time parking navigation service (Lu et al., 2009). Authors have considered the development of a hybrid sensor and vehicular network for safety ITS applications. Another trend is the Unmanned Aerial Vehicles (UAVs), which provide wireless connectivity in locations where the cellular range is limited, or the existing infrastructure fails to operate. Equipping UAVs (or drones) with the vehicle detection sensors can ultimately solve many problems that the current deployments of smart parking systems are facing. Furthermore, with the emerging long-range low power wide area networks (LPWAN) and the 5th generation (5 G) networks, several IoT services can be provisioned in SPS. In (Uckelmann, Harrison, Michahelles, & Al-Turjman, 2011), authors describe the IoT paradigm as a dynamic global network infrastructure with self-configuring capabilities based on standard and interoperable communication protocols. With the increasing number of connected devices day by day, the need for faster and more efficient wireless communication trend in parking systems is expected. This is where 5 G can fill the gap (AlTurjman, 2019). However, interoperability issues related to both software and hardware aspects in these solutions can dramatically degrade the system performance. And thus, ubiquitous IoT solutions in SPS need to be open and able to integrate with other existing platforms.

1.1. The scope of this paper This survey aims to offer an insight into new parking paradigms in ITS. We look at different aspects of the smart parking system (SPS). First, we define and classify the existing smart parking attempts in order to provide the reader an idea about the concept of the smart parking system in general and its possible categories/alternatives. For a comprehensive study, we cover both hardware and software aspects in this system. In terms of hardware, we investigate all vehicular sensors that are currently in use via several use-cases in terms of their strengths and weaknesses. Moreover, we list and overview the different physical communication technologies that are especially used in smart parking, while identifying the main elements influencing the parking system performability. Summary tables have been also added to offer a quick and rich overview about these sensors and communication technologies. On the other hand, relevant software systems and algorithms used to assure smooth and comfort quality of service to the end-user have been also investigated. We outlined and analyzed potential algorithms in parking prediction, path optimization and assisting techniques in the literature. We also delved into the soft security issues and assessed the literature for countermeasures against the existing security attacks. For more uniform and open access solutions, we discussed the system interoperability from the soft privacy point of view in the context of smart parking. We further present new emerging applications and software systems handling common parking problems with the help of VANET paradigms, in addition to recommending a novel conceptual hybrid smart parking system. In general, this survey aims to gather and zoom in critical design aspects that might be of interest to readers from the academia, as well as, the industry. It provides a multidisciplinary source for those who are interested in ecosystems and IoT-enabled smart cities. Also, it opens the door for further interesting research projects and implementations in the near future. For more readability, the used abbreviations in this survey along with their definitions are provided in Table 1.

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summarize these differences in comparison to the aforementioned surveys and contributions in the literature. The rest of this paper is organized as follows. Section II classifies the existing smart parking systems into centralized versus distributed systems, and discusses their main features. In Section III, we overview and compare the current state of vehicular detection technologies while focusing on critical parameters such as scalability, accuracy, and sensitivity to weather conditions. Utilized sensors are also classified into active versus passive sensors. In Section IV, common design factors are listed under three main categories soft, hard and interoperability factors. Varying use-cases have been presented and discussed in the context of both, small-scale individual vehicular systems, and large-scale implementations for smart city ecosystems. We also investigate the new generation of smart parking systems utilizing VANET and drone paradigms, in addition to recommending a new conceptual hybrid model for the smart parking system. In Section VI, we overview existing open research issues in smart parking systems ranging from the sensor limitations to the communication network capabilities, as well as, the need for energy harvesting and data interoperability. Finally, we conclude our survey in Section VII.

1.2. Comparison to other surveys There have been similar attempts and surveys in the literature on smart parking solutions with their own merits and limitations. In this subsection, we overview these attempts and highlight how it contrasts with our survey. For example, a very short survey on the parking lot reservations in cloud-based systems was discussed in (Chandrahasan, Mahadik, Lotlikar, Oke, & Yeole, 2016). The explanation for the mechanism of each reservation technique was briefly discussed with examples. A similar survey was provided in (Revathi & Dhulipala, 2012), however, without examples from the literature. Authors have slightly touched a few types of the vehicular sensors. Nevertheless, it was not comprehensive and did not cover all types of possible sensors and limitations. The inadequacy of the previous surveys was covered and better expressed with more examples and justifications in (Idris, Leng, Tamil, Noor, & Razak, 2009). Authors presented some of the vehicular detection sensors with examples from the literature. However, it fails to demonstrate other aspects of the smart parking system (SPS) such as the utilized communication protocols and/or software systems. With respect to communications, authors in (Hilmani, Maizate, & Hassouni, 2018) explained the different implementation aspects of the wireless sensor communication protocols and later proposed an adaptive and self-organized protocol. Despite this, they did not consider the emerging trends in low power wide area network (LPWAN) communication protocols and mostly relied on sensors and RFID systems while conducting their research. Multi-agent, fuzzy, vision and VANET -based smart parking methods were overviewed in (Faheem, Mahmud, Khan, Rahman, & Zafar, 2013). Authors talked about the used software systems in general, but they did not go much into the hardware details. A related, albeit brief, summary of smart parking software systems and applications with different advantages and disadvantages was presented in (Hassoune, Dachry, Moutaouakkil, & Medromi, 2016). However, like the other surveys, reasonable parts of the necessary information and hardware details were missing. Perhaps the most comparable survey to our work is given in (Lin, Rivano, & Le Mouel, 2017). This survey referred to reasonable aspects of the smart parking system such as information collection, dissemination, and deployment. However, it relies on outdated references and lacks the discussion of new enabling technologies related to drones and other emerging sensors in the field. Our survey can be considered one of the most comprehensive and up to date studies in comparison to the aforementioned surveys with additional insights and discussions about the new trends in SPS, which were briefly mentioned and/or totally ignored in the literature. In addition to covering the detailed hardware components, data interoperability, privacy and security issues are discussed and assessed. Moreover, hybrid solutions, with more comprehensive analysis in terms of communication networks and recent innovative parking applications are discussed in the smart city context. In Table 2, we

2. Smart parking systems and classifications Smart parking systems are categorized into various categories in which each of them has a different purpose and use different technologies in detecting vehicles. Smart parking systems benefit both the drivers and the operators. Drivers use the system to find the nearest parking spots and the parking operators can utilize the system and the collected information to agree on better parking space patterns and a better pricing strategy. For example, since the demand for a parking lot is not stable, using a dynamic pricing approach, which takes into consideration the time and type of customers, can help the operators boost their revenues (Polycarpou, Lambrinos, & Protopapadakis, 2013). Smart parking enables several attractive services such as the smart payment/reservation, which can substantially enhance the experience of both drivers and operators. Moreover, the smart parking system helps in preventing the unauthorized vehicular usage, as it increases the security measures on parking lots. Furthermore, SPS can play a significant role in providing a clean and green environment by minimizing the vehicle emissions via decremented delays in finding the vacant parking spot (Chinrungrueng, Sunantachaikul, & Triamlumlerd, 2007). Smart parking system (SPS) architectures commonly consist of several layers based on their functionalities (Bagula, Castelli, & Zennaro, 2015 Revathi & Dhulipala, 2012). Firstly, the sensing layer, which is the backbone of the smart parking system, and it is responsible for detecting the presence and/or absence of a vehicle in an area using different sensing technologies. These technologies are mostly comprised of receivers, transmitters, and anchors. Secondly, the network

Table 2 Summary of related surveys. Reference

Interoperability and data exchange

(Chandrahasan et al., 2016) (Revathi & Dhulipala, 2012) (Idris, Leng et al., 2009) (Hilmani et al., 2018) (Faheem et al., 2013) (Hassoune et al., 2016) (Lin, Rivano, Le Mouel et al., 2017) Our Survey

✓represents a comprehensive analysis. ✓* represents a general analysis. ✓† represent very little analysis. - means not considered. 3

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Fig. 1. Smart parking system architecture, adapted from (Revathi & Dhulipala, 2012).

2015). PGIS can be implemented in both citywide and/or individual parking lots, where in both cases, drivers can easily follow and navigate to reach the vacant parking space (Buntić, Ivanjko, & Gold, 2012). In (Hui-ling et al., 2003) a combination of PGIS and Dedicated ShortRange Communication (DSRC) is presented, where the DSRC-based PGIS provides a real-time, rapid and efficient way of guidance. However, concerns regarding the PGIS algorithm efficiency and the data safety, as well as, the need for incorporating heterogeneous smart subsystems may cause severe issues in the implementation stage. A combined PGIS with a mobile phone terminal with the help of Global Positioning System (GPS) to locate and predict vacant spots and to guide drivers to the destination was presented in (Qian & Hongyan, 2015). Whereas Shiue et al., utilized both GPS and 3 G in (Shiue, Lin, & Chen, 2010). Reliability of GPS and 3 G connectivity in a multilevel parking lot is an issue, which may cause such systems to be impractical and ineffective. In (Chen & Chang, 2011), authors proposed a PGIS in combination with ultrasonic sensors and WSNs. Meanwhile, (Patil & Bhonge, 2013) integrated RFID- and ZigBee- based solutions. These sensor-based solutions have their own disadvantages as we are going to explain later in this article. In general, all processing and decision making processes in PGIS are performed at a central processor (server) (Kokolaki, Karaliopoulos, & Stavrakakis, 2012).

layer, and it is the communication segment of the system, which is responsible for exchanging messages between transmitters/receivers and the anchors. Thirdly, the middleware layer, which is the processing layer of any SPS in which intelligent and sophisticated algorithms are utilized to process the real-time data. It also acts as a data storage, as well as, the link between the end users requesting services from the lower layers. Finally, the application layer, and it is the top layer in the system, which interfaces the SPS with clients (end-users) requesting different services from different mobile and/or stationary information panels as depicted in Fig. 1. These multilayered parking systems can be categorized into the following three types. 2.1. Centralized-assisted smart parking systems In centralized smart parking systems, a single central server collects the necessary parking information and process it to provide services such as the parking lot reservation, allocation, and/or driver guidance. The following sample systems are generally implemented as a centralized system. 2.1.1. Parking guidance and information system (PGIS) PGIS, or also known as Advanced Public Transport System (APTS), works by collecting parking information dynamically from loop detectors, ultrasonic, infrared, and microwave sensors in order to inform the drivers in real-time manners about the vacancy of the parking lot via an onboard guidance system or a variable message sign (VMS) (Chinrungrueng et al., 2007 Hui-ling, Jian-min, Yu, Yu-cong, & Ji-feng, 2003). PGIS consists of four major subsystems namely the information collection, processing, transmission, and distribution (Qian & Hongyan,

2.1.2. Centralized assisted parking search (CAPS) In this example, the First Come First Serve (FCFS) approach is adopted, where the first requester vehicle is guided towards a guaranteed vacant spot closest to the driver location. However, in this manner, other vehicles waiting in the queue are in continuous movement until the server can satisfy them. This brings the issue of uncooperativeness 4

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between drivers that can significantly degrades the performance in CAPS. Furthermore, the high maintenance cost and scalability are serious concerns in CAPS, as well. In (Kuran, Viana et al., 2015), authors proposed a parking lot recharge scheduling (PLRS) system under this category for electric vehicles. Authors compared the performance of their approach against basic scheduling mechanisms such as FCFS and earliest deadline first (EDF). Their optimized version of FCFS and EDF outperforms the basic mechanisms with regard to maximizing revenue and the number of vehicles in the parking lot. In another example, edPAS, the abbreviation for event-driven parking allocation system, focuses on effective parking lot allocation based on certain events in the parking lot while dynamically updating the communicator (Raichura & Padhariya, 2014). This system utilized both FCFS and priority (PR) based allocation schemes.

parking is very high, however, for the services that you receive, the price is very competitive. In fact, 50% saving compared to conventional modes of the parking in locations, where the parking fee is high and time-limited, is expected (Mario Buntić et al., 2012). In these systems, employment of one or a combination of many services and sensors may be integrated to provide a fast, reliable, and a secure mode of parking with little or no interactions between the drivers and the system. A general concern regarding such a system is that a universal building code does not exist yet. In order to serve all customers, compatibility issues with the varying vehicles’ models’ have to be addressed and solved. 2.2. Distributed-assisted smart parking systems In distributed smart parking systems, many services are connected and are controlled by a single server. This is well explained in vehicular networks where one vehicle can exchange information to one or more vehicles effectively creating a distributed network of vehicles. Another example is in the systems where information processing and dissemination is generally based on roadside infrastructure. Examples below are considered as distributed and opportunistic smart parking system in the literature.

2.1.3. Car park occupancy information system (COINS) COINS utilizes video sensor techniques based on one single source to detect the presence and/or absence of vehicles. The status is then reported on information panels which are strategically placed around the parking lot (Bong, K.C, & Lai, 2008). COINS is mainly dependent on four different technologies: 1) the counter-based technology, 2) the wired sensor-based technology, 3) the wireless sensor-based technology, and 4) the computer-vision based technology. Knowing that, using the last technology can provide more accurate results about the exact status of the parking spot without deploying other sensors in each individual spot (Bong et al., 2008 Buntić, Ivanjko, & Gold, 2012). In (Bong et al., 2008), COINS was developed and simulated in different environments with different parameters such as weather conditions and illumination fluctuations, which can add an extra layer of complexity to the system. Applications of COINS in a multilevel parking lot may not be that much effective like the other parking systems due to scalability and coverage issues.

2.2.1. Transit based information system (TBIS) TBIS is a park- and ride- based guidance system with similar functionalities to PGIS. It communicates with drivers through VMS to guide them towards a vacant parking spot. It also provides a real-time information about the public transportation schedules/routes status, which enables drivers to pre-plan their journey more efficiently (Idris, Leng et al., 2009). A field test in San Francisco (Rodier & Shaheen, 2010) shows promising results for the effectiveness of TBIS. However, due to the initial capital cost, such a system should be implemented mainly in large-scale applications to recover the cost. Geographic Information System (GIS) is also another way for providing traffic information to users (Pal & Singh, 2011 Peng, 1997). This system provides the minimum travelling time by optimizing the route/schedule of the functioning public transportation system in real-time manner. It enables web-based GIS systems to be implemented for the convenience of users in planning their trips.

2.1.4. Agent based guiding system (ABGS) ABGS simulates the behavior of each driver in a dynamic and complex environment explicitly. The agent in this system is capable of making decisions and define the interaction between drivers and the parking system based on perceived facts from the driver and other varying aspects such as, autonomy, proactivity, reactivity, adaptability, and social-ability. For instance, SUSTAPARK was developed in (Dieussaert, Aerts, Thérèse, Maerivoet, & Spitaels, 2009) to enhance the searching experience while locating the parking space in an urban area with an agent-based approach. The authors aimed at dividing the parking task into manageable sub-tasks that the computer agents could follow using Artificial Intelligence (AI) techniques. Another agent-based approach was introduced in (Benenson, Martens, & Birfir, 2008), named PARKAGENT, based on ArcGIS with similar functionalities to SUSTAPARK. However, it considers the effects of the system entities’ heterogeneity and the population distribution of drivers. In (Chou, Lin, & Li, 2008), an agent-based system was used as a negotiator to bargain over the parking fee with guidance capabilities to guide drivers to the optimal parking destination using the shortest path. It was relying on some perceived factors and performed interactions with other agents.

2.2.2. Opportunistically assisted parking search (OAPS) Vehicles with IEEE 802.11x communication standard in ad-hoc mode can share information about the status and location of the parking spots. This enables drivers to make more knowledgeable decisions, while they are searching in the crowd. In this approach, drivers are guided toward the closest vacant parking space by analyzing timestamps and geographical addresses using GPS units, for example. Since OAPS dissemination service does not impose a global common knowledge about the status of parking spots. The outdated timestamps and infrequent updates could cause delays and intimidate the effectiveness of this approach (Kokolaki et al., 2012). Another issue could be the misbehavior of drivers when they enjoy the shared information from other drivers, but show selfishness in sharing theirs (Kokolaki, Kollias, Papadaki, Karaliopoulos, & Stavrakakis, 2013). This can increase the distance between the destination and the parking spot, in addition to increasing the parking search time.

2.1.5. Automated parking Automated parking consists of computer-controlled mechanical systems which enable drivers to drive their vehicles into a designated bay, lock their vehicles and allow the automated parking system to manage the rest of the job (Chinrungrueng et al., 2007 Idris, Leng et al., 2009). Stacking cars next to each other with very little space in between, allows this system to work in an efficient way such that the maximum available space in the parking is utilized. The retrieval process of the vehicles is as easy as entering a pre-defined code or password. The process is fully automated, which adds an extra layer of security and safety to the whole system including both drivers and vehicles (Idris, Leng et al., 2009). Although the initial cost of automated

2.2.3. Mobile storage node-opportunistically assisted parking search (MSNOAPS) Instead of normal vehicle nodes, the inflow of information is channeled through Mobile Storage Nodes (MSNs), which enable information sharing with other mobile nodes acting as a relay between vehicles. Similar issues in data dissemination can also be observed as the status of the parking spot changes overtime. Because the accuracy of disseminated data has a tendency to drop down as the number of relays increases. In (Kokolaki et al., 2013) authors suggested that MSN, could 5

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required to calculate the parking fee. Internet-connected parking meters can also be used as a tool for the parking patterns determination and prediction, especially for the on-street parking where machine learning techniques are applied. However, the technical issue with SPS is the reliability and integrity of the system in case of wireless signal interception and/or routing protocol attacks, which could compromise confidential information (Juliadotter, 2016).

improve the performance of OAPS. However, it does not have a significant effect, when a selfish driver as we afore-described uses it. 2.3. Non-assisted parking search (NAPS) In NAPS approach, there is no inflow of information from any vehicle/server. The parking decision is solely dependent on the driver’s observation in the parking lot, or on a former experience considering the traffic flow and the time of the arrival in the parking lot. Drivers wander around a parking lot and check for empty spots in sequence until an empty one is found. This empty spot is then allocated to the driver who has reached the spot first (Kokolaki et al., 2012 Thierry, Sergio, Sylvain, & Nicolas, 2013). Usually, it is performed with the minimum technology involvement. That is why we call it, “Non-assisted” parking. Scalability and cost design issues associated with the aforementioned categories of smart parking systems are mainly justified/claimed by the amount and type of the utilized sensors and/or enabling technologies. For example, in a large-scale smart parking application (e.g. in the multi-story shopping malls), where multiple sensors of one or more type(s) are required, the overall cost may exceed the cost of using the same parking system in a small-scale application. Therefore, as noted in Table 3, the cost of a few smart parking systems might be dependent on the scale and the scope of the targeted application. Table 3 tabulates the afore-overviewed parking systems based on their varying parameters and requirements.

2.4.2. Parking reservation system (PRS) PRS is a new concept in intelligent transportation systems (ITS), which allows drivers to secure a parking spot particularly in peak hours prior to or during their journey (Mouskos, Boile, & Parker, 2007). The objective of PRS is to either maximize the parking revenue or minimize the parking fee. This has been achieved by formulating and solving a min-max problem. Implementation of PRS requires several components namely: the reservation information center, the communication system between the users and the PRS, the real-time monitoring system for the parking lot, and an estimation for the anticipated demands (Mouskos et al., 2007). Drivers can later use a variety of communication services such as SMS, mobile phone, or web-based applications to make the reservation of a parking space. SMS-based reservation was implemented in (Hanif, Badiozaman, & Daud, 2010), where the integration of microRTU (Remote Terminal Unit) and the microcontroller, in addition to other safety features make it a smart solution in PRS. Such a system is also scalable and capable of handling multiple requests from drivers. CrowdPark system is another example of PRS proposed in (Yan et al., 2012), where the system works by crowdsourcing and rewarding to encourage drivers to use the system and report the parking vacancy. Malicious users and accuracy of the parking lot are a concern in these types of systems. However, in the case of CrowdPark, a 95% of a success rate has been reported in San Francisco downtown area. ParkBid crowdsourced approach was proposed in (Noor, Hasan, & Arora, 2017) where this system, unlike other crowdsourced applications, is based on a bidding process. This process provides numerous incentives about the parking spot information that enable urgent requests to be satisfied, in addition to reserving the closest parking spot.

2.4. Use-cases in practice In this subsection, we outline three common use cases of the smart parking system for a discussion that is more comprehensive. These use cases are named as follows: 1) The Smart Payment System (SPS), 2) The Parking Reservation System (PRS), and 3) The E-parking System. A detailed analysis for these use cases is provided in the following subsections. 2.4.1. Smart payment system (SPS) Conventional parking meters were always slow and inconvenient to use. Nevertheless, the smart payment system has been developed and integrated nowadays with IoT and advanced technologies that assure reliability and fast payment methods (Chinrungrueng et al., 2007). This system employs contactless, contact, and mobile modes to achieve its purpose. In contactless mode, smart cards and RFID technologies such as Automated Vehicle Identification (AVI) tags are used. In contact mode, credit and debit cards are utilized. In mobile mode, mobile phone services are employed to collect the payment (Chinrungrueng et al., 2007 Revathi & Dhulipala, 2012). In (Idris, Tamil, Razak, Noor, & Kin, 2009) authors proposed image processing technology in conjunction with SPS by utilizing RFID technology. This enables drivers to recall their parking spot, which contains the duration information

2.4.3. E-parking system E-parking, as the name suggests, provides a system in which users can electronically obtain information about the current vacancy of the parking lots from other services and sensors. Moreover, it makes reservations and payments all in one go without leaving the vehicle and before entering the parking lot. The system can be accessed via mobile phones or web-based applications. In order to identify the vehicle making reservations, a confirmation code is sent to the user’s email and/or mobile phone through SMS which then can be used to verify the identity of the vehicle (Chinrungrueng et al., 2007). Majority of the smart parking deployments that are introduced in this paper are an example of E-parking where information about the parking vacancy can be achieved in advance. ParkingGain (Sauras-Perez, Gil, & Taiber,

Table 3 Classified parking systems. Parking System Classification


All All All Vehicle – Video & image processing All Limited

VMS VMS VMS V2V, V2I, MSN – Information Panel Agent Information Panel

City wide, local City wide, local Local Local – Local City wide, local Local

Scale dependent Scale dependent ***** *** None *** Scale dependent ****

represents a rating system, one star (*) means poor and the 5 stars (*****) means excellent in terms of their used metric (e.g., accuracy, scalability, etc.), whereas, for the cost metric, more stars means more expensive. ✓* indicates only applicability in certain cases (applications) as discussed in each subsection. 6

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Table 4 Comparison of Different Parking Sensors. Sensor type

Passive IR Active IR Ultrasonic Inductive loop Magnetometer Piezoelectric Pneumatic road tube WIM Microwave CCTV RFID LDR Acoustic

2014) is another example of the E-parking, where authors presented a smart parking approach by integrating the OBU installed on vehicles to locate and reserve their desired parking spots. Moreover, their system offered the value-added services to subsidize part of the running cost and create business opportunities, as well. 3. Sensors overview

In this section, several sensing and vehicle detection technologies are discussed. They are the integrated part of information sensing in smart parking system. In order to choose the best alternative for each application, several design factors should be taken into account. Knowing that these sensors can vary in their strengths and weaknesses. Vehicle detection sensors are mainly categorized into two types intrusive (or pavement invasive), and non-intrusive (or non-pavement invasive) (Federal Highway Administration, 2019). Table 4 summarizes the list of sensors that have been typically used in smart parking systems. In addition, it overviews numerous parameters that can influence the choice of the sensor type to be used in a specific smart parking application. The sensed data accuracy and complexity levels, as well as, the sensor maintenance operations, can typically influence the cost associated with these sensors. Moreover, depending on the installation requirement, the overall cost may rise. As in the case of piezoelectric sensors, accuracy represents additional cost on top of the installation difficulty. Therefore, the best sensor is the one that can best fill the need of the parking owner, while maintaining the lowest cost without sacrificing accuracy and comfort levels. In the following, these sensors are discussed and classified into active versus passive sensors.

3.1.4. Vehicle license recognition In conjunction with CCTV and image processing units, plates of the ingress and egress vehicles can be captured and analyzed to give an estimation of the arriving/departing vehicles in real-time manners. Furthermore, continuous monitoring of vehicles movement in the parking lot until they reach the pre-designated parking spaces, which have been allocated to them, is a desirable feature in these systems (Mouskos et al., 2007). This also enables smart payment to be deployed which allows the drivers to exit the parking bay without any delay since the required information is already forwarded to the automated gate controller. However, bad weather conditions can disrupt the functionality of plate recognition systems. Additionally, privacy concerns regarding storing the information of vehicles on a public database is another flaw in these systems.

3.1. Active sensors Active sensors are those which need an external power source to operate and perform their task. In the following, we overview the most common parking sensors which are classified as active ones. 3.1.1. Active infrared sensor Active infrared sensors are configured to emit infrared radiation and sense the amount that is reflected from the object. And hence, it can detect empty spaces in a parking lot. While these sensors can accurately take advantage of multilane roads (active) and discover the exact location and speed of a vehicle on a multilevel parking lot, they are prone to weather conditions such as heavy rain, dense fog and very sensitive to the sun (Lin, Rivano, & Mouël, 2017).

3.2. Passive sensors Passive sensors are those, which rely on detecting and responding to inputs from the surrounding physical environment without the need for dedicated power supply units. In the following, common examples of these types of sensors are overviewed.

3.1.2. Ultrasonic sensors Ultrasonic sensors work in the same way as infrared sensors do, but they use sound waves as opposed to light. It transmits sound energy with frequencies between 25 to 50 kHz, and upon the reflection from the vehicle body, it can detect the status of the parking lot (Al-Turjman,

3.2.1. Passive infrared sensor Passive infrared sensors work by detecting the temperature 7

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difference between an object and the surrounding environment (Song, Choi, & Lee, 2008). In contrast to active infrared sensors, that emit IR waves in a predefined pulse rate, passive sensors identify the vacancy of a parking space by measuring the temperature difference in the form of thermal energy emitted by the vehicle and/or the road. Thus, it is only triggered when a vehicle is in the vicinity of the detection zone of the sensor. Unlike the other sensors’ types, passive infrared sensors do not need to be anchored or tunneled on the ground or the wall. However, these sensors are mounted to the ceiling in the parking lot (Someswar, Dayananda, Anupama, Priyadarshini, & Shariff, 2017). These sensors are prone to weather conditions effects, which can degrade the parking system performance sometimes.

3.2.6. Magnetometer Magnetometer functions in the same way as loop detectors. It senses the changes in the earth magnetic field that is caused by metallic objects, such as vehicles, passing over these sensors. The cause for such distortion is that the magnetic field can easily flow through ferrous metals in contrast to the air (Arab & Nadeem, 2017). There are two types of magnetometers the single axis, and the double/triple axis magnetometer. Accuracy of detecting vehicles using the second type is much higher due to the fact that it uses two/three axes while identifying the presence of a vehicle. Nonetheless, both types are reliable and resist undesired weather conditions. Meanwhile, lane closure, pavement cut, and in some cases short-range detection and inability to detect stopped vehicles are considered as shortcomings in this category (Al-Turjman, 2018a).

3.2.2. LDR sensor Light Dependent Resistor sensor or LDR in short, detect changes in luminous intensity. By assigning a primary source of light, such as the sun, and a secondary source, such as the other surrounding light, the vehicle creates a shadow that causes the light sensor to detect luminous intensity changes. This indicates the presence of the vehicle in the parking spot. Weather conditions such as rain, fog and the change in the angle where the sunlight is assumed to arrive can affect the performance of these kinds of sensors and can lower the detection accuracy (Bachani, Qureshi, & Shaikh, 2016). As for their installations, these sensors are usually deployed on the ground in the center of the parking spot.

3.2.7. Vehicle-in-motion sensors Vehicle in motions (VIM) sensors can precisely determine the weight of a vehicle and the portion of the weight distributed on the body axles. Data gathered from these sensors are extremely useful and heavily used by highway planners, designers as well as, law enforcement procedures. There are four distinct technologies used in VIM load cell, piezoelectric, bending plate, and capacitance mat (Al-Turjman, 2018a Martin et al., 2003). Load cell uses a hydraulic fluid that triggers a pressure transducer to transmit the weight information. Despite its high initial investment, load cells are by far the most accurate VIM systems. Piezoelectric VIM system detects voltage variations per the applied/experienced pressure on the sensor. Such a system consists of at least one piezoelectric sensor and two ILDs. Piezoelectric sensors are among the least expensive sensors in the market. However, their accuracy in vehicle detection is lesser than load cells and bending plate VIM systems. Bending plate uses strain gauges to record the strain or the change in length when vehicles are passing over it. The static load of vehicles is then measured by dynamic load and calibration parameters such as the speed of vehicle and pavement characteristics. Bending plate VIM system can be used for traffic data collection. It also cost less than the load cell system, but its accuracy is not at the same level. Lastly, the capacitance mat system consists of two or more sheet plates, which carry equal but opposite charges. When a vehicle passes on top of these plates, the distance between the plates becomes shorter and the capacitance increases. The changes in the capacitance reflect the axle weight. The advantage of using this system is that it can easily operate in a multilane road. However, it suffers high initial investment costs.

3.2.8. Microwave radar Microwave radar generally transmits frequencies between 1–50 GHz by the help of an antenna, which can detect vehicles from the reflected frequency. Two types of microwave radar are used in this sector, Doppler Microwave Detectors (DMD) and Frequency-Modulated Continuous Waves (FMCW) (Al-Turjman, 2018a Martin et al., 2003). In the former type, if the source and the listener were close to each other, the listener would perceive a lower frequency. Contrary, if they were moving apart from each other, the frequency would get higher. If the source was not moving, Doppler shift would not happen. In this case, continuous range of frequencies is transmitted and the detector can then measure the distance to the vehicle and indicates its presence. Microwave radars are more effective under harsh weather conditions. It can also measure the speed of the vehicle and conduct data collections on multilane traffic flow. However, measuring the speed using Doppler detectors requires additional sensor types such as the aforementioned ones to collaborate in accomplishing this task.

3.2.5. Pneumatic road tube Pneumatic road tube encompasses air pressure sensor at one end of the tube, whereas the other end is sealed to prevent the air leakage. Once the vehicle crossover this tube, the sensor sends a burst of air pressure along the tube. This operation results in triggering an electrical switch to be closed and produces an electric signal in order to recognize the vehicle presence. A software analyzer can then identify the vehicle type from the associated weight and axle configuration. These sensors are cost effective and offer quick/simple installation. Nevertheless, this type of sensors can lead to inaccurate axle counting in case of the long vehicles’ passing (e.g., buses and/or trucks). This results in less reliable parking vacancy information (Al-Turjman, 2018a).

3.2.9. RFID RFID or radio frequency identification can be used for vehicle detection as well in the parking lot. RFID units (readers and tags) consist of a transceiver, transponder, and antenna. RFID tags or transponders 8

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units with its unique ID can be read via a transponder antenna (Kotb et al., 2017). It can be placed inside the vehicle to be identified by the reader antenna that is placed in the parking lot. The reader reads the tag and changes the parking spot status to be occupied. With this system, the delay can be minimized and the flow of the traffic in the parking lot becomes smoother. Due to the range limitation in RFID systems, the distances between the reader and the tag is of utmost importance (Pala & Inanc, 2007). It worth remarking that RFID in hybrid systems have shown more reliability than the standalone RFID system (Karbab, Djenouri, Boulkaboul, & Bagula, 2015).

manage, monitor and analyze the data in an efficient manner. Many of the existing smart parking applications are using a centralized server to store and manage their data. After performing data analysis, several services such as the parking reservation and guidance can be implemented. For example, in (Khanna & Anand, 2016), authors presented a smart parking IoT and a cloud-based system using real-time information. Services such as the parking lot payments, reservation, and confirmation, are all processed via a mobile application. In case of overshooting the parking time, the system offers an automated extension for the parking lot reservation and failing to do so will impose certain fees against the driver. A context-aware smart parking system based on collaborative work between smart servers, smart objects, and smart mobile devices was proposed in (Rico, Sancho, Cendon, & Camus, 2013). The smart servers collect/process the city-context information and all other related information regarding the parking status and registered users. It relays the information to distributed smart objects in the surrounding environment to make changes in the availability of the parking space. It finally displays the results via a GUI interface on the smart device, where the user can search, book, and pay for the parking lot. Guidance software systems are getting smarter nowadays. Unlike the old PGIS, several design factors have been taken into consideration. In (Zhu, Liu, Peng, & Li, 2017), authors applied Stackelberg game theory to the PGIS in order to model the experienced dynamic changes in drivers’ behaviors. Authors aim at balancing the parking revenue against the average time required in searching for a parking spot. A utility-based guidance approach for parking in a shopping mall was discussed in (Liang, Zhang, Hu, & Wang, 2017). This guidance approach uses an improved A* shortest path algorithm that generates the optimal vehicle route based on six different factors associated with the user preference and the parking utility. MQTT guidance protocol was considered in (Hantrakul, Sitti, & Tantitharanukul, 2017) in order to share simultaneously the real-time parking lot vacancy information with at least 1000 users. Their web application in JavaScript presents the information on the layout of the shopping mall drawn by Scalable Vector Graphics (SVG). Moreover, an Internet of vehicle (IOV) based guidance system was proposed in (Zhang, Yu, Wang, Xue, & Xu, 2017). Onboard hardware in vehicles enables IOV to interact with everything around (vehicles, pedestrian, and sensors) which then can be used with the optimal path and parking algorithms embedded in the system to guide the drivers to the nearest parking spot. Continuous license plate recognition using video with Gray Level Changes (GLC) algorithm and Dijkstra algorithm for locating and guiding to the nearest parking spot was experimented in (Xie, Liu, Miao, & Liu, 2016). The combination of license plate and GLC detection ensure that the system is viable in case of passing pedestrians on the parking spot or when they cover the license plates. The use of GPS in smartphones with the combination of a genetic algorithm to locate and navigate to the closest parking lot was developed in (Aydin, Karakose, & Karakose, 2017). Authors presented their solution and were able to obtain accurate results in several case studies. Instead of using exploration algorithms for locating the nearest parking space, a learning mechanism was used in (Houissa, Barth, Faul, & Mautor, 2017). Authors used reinforced learning algorithms in conjunction with Monte Carlo approach to minimize the expected time to find a parking place in an urban area. They compared their algorithms against the tree evaluation and random methods. It was deduced that their algorithms are less complex and more efficient. In (Zheng, Rajasegarar, & Leckie, 2015), the authors propose a cache replacement approach for Fog applications in Software Defined Networks (SDNs). This approach depends on three functional factors in SDNs. These three factors are age of data based on the periodic request, the popularity of on-demand requests, and the duration for which the sensor node is required to operate in active mode to capture the sensed readings. These factors are considered together to assign a value to the cached data in a software-defined network in order to retain the most valuable information in the cache for longer time. The higher the value, the

3.2.10. Acoustic sensor Acoustic sensors can detect the sound energy produced by the vehicular traffic or the interaction of tires with the road. In the detection zone of the sensor, a single processor computer can detect and signal the presence of a vehicle from the generated noises. Similarly, in the drop of the sound level, the presence of the vehicle signal is terminated. Acoustic sensor can function on rainy days and can also operate on multiple lanes. However, cold weather conditions and slow vehicles can degrade the accuracy of such sensors (Al-Turjman, 2018a Kotb et al., 2017). To overcome this limitation, machine-learning techniques have been incorporated with these sensors for better performance. 4. Design factors In this section, we look at the design factors that influence the performance of the smart parking systems in practice. We divide these factors into three main categories. Firstly, we overview soft design factors that deal with software aspects of the system. Several soft solutions that have been found in the literature have been presented and correlated. Secondly, the experienced hardware issues and critical design aspects related to utilized sensors and communication networks in smart parking systems have been intensively studied and discussed, as well. Moreover, we investigate the system components interoperability and data exchange with more focus on relevant smart city applications. This category is unique in nature and has been rarely overlooked in the literature, although it can make a significant effect in terms of the system performability and cost. We believe that the discussions in this section can be beneficial to all relevant smart solutions in a smart city ecosystem. Proposed examples and tabulated conclusions can considerably assist those who are interested in this area to quickly grab the fundamental information they seek. 4.1. Soft design factors This category of the relevant design factors deals with software aspects of the parking system, as well as, the processing of data collected via the aforementioned sensors. We also discuss under this category the potential influences of the experienced privacy and security aspects from the collected data. 4.1.1. Software systems in smart parking Software systems play a key role in smart parking applications. They are used in managing the collected data from the sensors, and then analyze it efficiently. The performed soft analytics are based on algorithms that vary in intricacy depending on the scale and the complexity of the parking application. Furthermore, using the collected data and applying certain machine learning methods, these analytics can be used to predict parking vacancy and optimize the selected vehicle route. This enables the parking operators to efficiently manage their parking lots, in addition to maximizing their revenues. In this section, the software aspect of smart parking systems and some interesting ideas such as path scheduling, path optimization, prediction, and parking assignment have been intensively discussed. Managing the information gathered from multiple sensors on a multilevel parking lot requires a robust software system that can 9

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longer the duration for which the data will be retained in the cache. This replacement strategy provides significant availability for the most valuable and difficult to sense data in the SDNs. Decisions based on when and where to park is largely based on driver’s observations. Many factors such as accessibility, fee, and availability of the parking influence the decision of the drivers. On the other hand, decisions based on experience when drivers locate a free parking space with or without prior information of the availability always tend to congestion of that particular space and increases the searching time and causes long queues. However, if the availability of the parking space can be predicted and disseminated in time, the driver’s experience in locating the most suitable location can be enhanced. Moreover, the prediction of the parking availability offers the parking operators short and long term system checks that ultimately enables them to take preventative decisions in case of any system failure. Nowadays, prediction is as easy as to collect data from the sensors and apply algorithms. Previously, prediction was based on historical data and surveys about the parking vacancy. In (Ji, Tang, Blythe, Guo, & Wang, 2015), data collected from off-street parking garages was used to create a short-term model that could forecast the changing characteristic of the parking space using the wavelet neural network method. Authors compared their research method with the largest Lyapunov exponents in terms of accuracy, efficiency, and robustness. Although the model was successfully tested, however, other important criteria such as driver’s behavior and/or environmental characteristics were not taken into consideration. In (Caicedo, Blazquez, & Miranda, 2012), the authors proposed a real-time availability forecast (RAF) algorithm based on drivers’ preferences and the availability of parking that are iteratively allocated using an aggregated approach. Their algorithm is updated upon each vehicle arrival and departure to predict the dynamic capacity and the parking availability. Their test simulation in a parking facility in Barcelona showed promising results with minor errors. The results were then compared with the numerical method, where they observed no significant difference between the two approaches. Prediction of the parking space availability of Ubike system in Taipei City was also experimented in (Leu & Zhu, 2015). The authors used regression-based models (mainly linear regression and support vector regression) to forecast the number of bicycles in Ubike stations. Their model, due to a constraint that bicycles are only circulating around the station, was different from a parking system used for cars. However, a similar approach can be used for the car-park facilities. A prediction mechanism based on three features’ sets with three different algorithms for comparison, namely regression tree, support vector regression, and neural networks were developed in (Zheng et al., 2015). With the data sets provided from San Francisco and Melbourne parking facility and based on their model, it was concluded that the regression tree is the least computationally intensive algorithm. The parking search-space optimization is another part of the software system in smart parking that utilize the collected information to minimize the searching time and to maximize the number of parking spaces in a given parking lot. Authors in (Maric, Gracanin, Zogovic, Ruskic, & Ivanovic, 2017) showed that their adaptive multi-criteria optimization model can effectively reduce the search time by 70% in an urban area. Multi-criteria such as the walking distance, price, and driving time, were set based on the drivers’ preferences. It was presented by a utility function with the objective to maximize the expected utility. In a study conducted in University of Akron (Moradkhany, Yi, Shatnawi, & Xu, 2015), authors used direct random search method to perform their optimization model based on mainly different classroom assignment options. However, other factors such as the parking search behavior, arrival and departure distributions, and locations of different buildings and parking facilities were also taken into account. Their model managed to reduce the parking search time by about 20%. A Cooperative Parking Search amongst the vehicles searching for a parking space using V2V and V2I technologies was studied in (Rybarsch

et al., 2017). Authors found that when vehicles search cooperatively, a search time reduction up to 30% can be achieved. They also concluded that drivers would benefit more, if drivers can exchange information before and after reaching their destination. An intelligent hybrid model for optimizing the parking space search based on Tabu metaphor and rough set based approach was introduced in (Banerjee & Al-Qaheri, 2011). Tabu search was used as a complement to other heuristic algorithms while the rough set was used as a tool to manage the noisy and incomplete data. 4.1.2. Privacy and security in smart parking It is estimated that the number of connected IoT devices would reach 20 billion by 2023 (Internet of Things outlook – Ericsson, 2017). These devices are in constant communication and a large number of data that is being processed, aggregated and shared with users can be intercepted and used for nefarious intentions (Chatzigiannakis, Vitaletti, & Pyrgelis, 2016). The most crucial part of any smart application is to assure that the network supports end-to-end encryption and authentication. In the case of interconnected IoT services and devices, any vulnerability, no matter the size is, can interrupt one side of the system and cascade it to the rest of the system (Braun, Fung, Iqbal, & Shah, 2018). In the following, we list a few key things to be considered while securing any SPS. a) Data collection, which if it has been limited to a certain extent, could greatly help to mitigate any risks. For example, storing a large amount of data can elevate security breaches and the collection of a huge amount of personal data may be used in a way that it is out of the scope of consumer's expectations from the system. b) Information sharing, which requires lots of optimization and analysis in any smart based application. In this regards, service providers and technology partners should come into an agreement for secure data handling and used techniques to ensure user’s privacy such as de-identification. c) Reliability of servers, encryptions, and digital signatures are also as important as the risk management protocols and the physical security of the system. d) Human errors/mistakes, intentional or unintentional, can also elevate security risks. Therefore, policies and procedures for training sessions among the SPS users are required to mitigate oversight issues. e) Finally, transparency of any smart system assures the integrity of such a system, which offers accountability and clear policies in regards to data security and privacy. In addition to the aforementioned generic considerations, a good smart parking application requires a secure end-to-end communication between the end user and the server. Since the majority of the smart parking solutions are established based on either web or mobile applications, it requires users in such systems to enter personal information such as their home/business address. Since these systems also keep track of the history of transactions including the credit card information, they are also considered as critical aspects in data privacy and security of the existing smart parking systems (Chatzigiannakis et al., 2016). P-SPAN, or privacy-preserving smart parking navigation system, was developed in (Ni, Zhang, Yu, Lin, & Shen, 2018). Their navigation system for locating and guiding drivers to a vacant parking spot using Bloom filter and vehicular communications using private mechanisms has shown to be an effective smart parking system with low computational and communication overhead. Another VANET based approach similar to the previous study with privacy-preserving in mind was discussed in (Lu, Lin, Zhu, & Shen, 2010). Their system provided a secure navigation protocol with one-time credentials. Some communication protocols lack data encryptions or require high computational resources in order to function securely. However, in (Chatzigiannakis et al., 2016), authors employed Elliptic Curve Cryptography (ECC) with 10

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LPWAN protocol as an alternative to other cryptography techniques in devices where there exist hardware limitations. The aim of the work performed in (Wang & He, 2011) was to design a typical network security model for cooperative virtual networks in the IoT era. This paper presents and discusses network security vulnerabilities, threats, attacks and risks in switches, firewalls, and routers, in addition to a policy to mitigate those risks. The paper provides fundamentals of secure networking system including firewall, router, AAA server, and VLAN technology. It presents a novel security model to defend the network from internal/external attacks and threats in the IoT era. In (de C. Silva, Rodrigues, Alberti, Solic, & Aquino, 2017), the authors proposed a context-sensitive seamless identity provisioning (CSIP) framework for the IIoT (Industrial Internet of Things). CSIP proposes a secure mutual authentication approach using hash and global assertion value to prove that the proposed mechanism can achieve major security goals in a short time period. Furthermore, in (Wang & He, 2011), authors proposed a solution for secure data collection. They used a repository of sensing information acting as a sink for the collected data and a mirror of reservation database, which is synchronized with the repository. In this fashion, drivers are the only elements that can access the mirror database in order to make payments, check the vacancy of parking lots, and perform reservation via mobile devices.

Fig. 2. Comparison of range and bandwidth of LPWAN and other protocols (Arab & Nadeem, 2017).

Telensa5 solutions use the Weightless N protocol along with magnetic sensors for the vehicles’ detection. A deployment of the NB-IoT and third-party payment based smart parking system was studied in (Shi, Jin, Li, & Fang, 2017). The authors proposed a cloud and mobile application platform that utilized an NB-IoT module to provide SMS and data transmission services over a wide range with low power consumption. As it can be observed, the applications of LPWAN protocol are limited. This is because the standards have not yet been adopted in many areas and regions. Unlike LPWAN, the WSN legacy protocols are the first choice in many smart parking solutions. However, as the population of vehicles increases, the need for wider communication range, more reliable, faster and more secure mode of communication is expected. This promises LPWAN to develop more and overcome the current existing challenges such as high complexity of interoperability between different LPWAN technologies, coexisting with other WSN protocols, and lack of standard models for large scale applications (Lavric & Popa, 2017 Raza et al., 2017). As Table 5 suggests, almost all the LPWAN communication modules have longer than 7–8 years of battery life with higher power efficiency and wider communication range in both urban and rural areas. In rural areas, the range of the communication is wider due to the absence of obstacles such as skyscrapers, which interfere the quality of data sent and/or received. Furthermore, the most common topology used in LPWAN is of the star type where all the nodes are directly connected to a central computer or server. Every node is also connected to each other indirectly in this topology. Short-range wireless networks are mostly connected in a mesh topology to extend their range. However, the development cost and the energy usage for a large number of distributed devices make it ineffective in large scale implementations (Raza et al., 2017) such as the multilevel parking lots. This is where LPWAN technology derives to overcome the limitations of the previous generations of wireless networks. Latency or the delay of the information from sensor nodes to the central server is quite small for legacy protocols compared to SigFox or LoRaWAN. Nevertheless, this does not necessarily mean that they are not effective in smart parking systems. In large-scale smart parking applications where low latency is necessary, NB-IoT and LTE-M are among the best options.

The communication networks surrounding the smart parking systems, from the legacy to LPWAN communication protocols, for small and large-scale applications have been addressed in this subsection from the hardware perspectives. In addition, we discuss the influences of the experienced sensors errors on the designed parking system. 4.2.1. Communication networks The employed IoT sensors in smart parking systems vary in terms of the used communication protocols. However, they all can be categorized into long-range low power wide area networks (LPWAN) or shortrange wireless networks. LPWAN has been integrated with existing cellular technology to avoid any further infrastructure need (Lin, Rivano, Mouël et al., 2017). The work performed in (Yan et al., 2012), for example, provides an overview for deployment strategies of femtocells that can support several smart applications in the IoT era. In addition, it presents major LPWAN standards such as LoRaWAN, Sigfox, Weightless (SIG), Ingenu, LTE-M and NB-IoT. On the other hand, shortrange communication technologies such as Bluetooth, Wi-Fi, and ZigBee have been used for short distances communication in the SPS. A comparison of range versus bandwidth for both modern and legacy communication protocols is shown in Fig. 2. Moreover, Table 5 summarizes the technical parameters for both short and long-range methods of communications (Al-Sarawi, Anbar, Alieyan, & Alzubaidi, 2017 Asaduzzaman, Chidella, & Mridha, 2015 Collotta, Pau, Talty, & Tonguz, 2017 de C. Silva et al., 2017 Lauridsen et al., 2017 Raza, Kulkarni, & Sooriyabandara, 2017 Wellnitz & Wolf, 2010). Libelium1, a WSN platform provider, has used both LoRaWAN and Sigfox in their Plug & Sense platform, which uses magnetic sensors to detect vehicles in parking spots. Huawei2 solution for smart parking has resulted in 80% energy reduction in their Czech Republic trial. ZTE3 trials in China has claimed 12% and 43% reduction in congestion and time spent searching free spots, respectively. These are some of the examples of NB-IoT based smart parking solutions. Moreover, China Unicom Shanghai smart parking, which is developed by Huawei, uses 4.5 G LTEM commination protocol in their parking network. Nwave4 and 1