Smart Parking: A Literature Review from the Technological Perspective

Barriga, Jhonattan J.; Sulca, Juan; León, José Luis; Ulloa, Alejandro; Portero, Diego; Andrade, Roberto; Yoo, Sang Guun

doi:10.3390/app9214569

Cited by 96 publications

(34 citation statements)

References 114 publications

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“…Background: process mining in smart mobility and higher education Smart mobility Popular use case in the smart city domain is the implementation of smart parking solutions, which contributes to the optimisation of peoples' time, reduction of fuel consumption and carbon dioxide emissions (Barriga et al, 2019). The architecture of smart parking solutions is frequently characterised by three components -sensors, communication protocols, and software solutions (ibid).…”

Section: Methodsmentioning

confidence: 99%

Process Mining Contributions to Discrete-event Simulation Modelling

Jadrić

Pašalić

Ćukušić

2020

Business Systems Research Journal

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Background: Over the last 20 years, process mining has become a vibrant research area due to the advances in data management technologies and techniques and the advent of new process mining tools. Recently, the links between process mining and simulation modelling have become an area of interest.Objectives: The objective of the paper was to demonstrate and assess the role of process mining results as an input for discrete-event simulation modelling, using two different datasets, one of which is considered data-poor while the other one data-rich.Methods/Approach: Statistical calculations and process maps were prepared and presented based on the event log data from two case studies (smart mobility and higher education) using a process mining tool. Then, the implications of the results across the building blocks (entities, activities, control-flows, and resources) of simulation modelling are discussed.Results: Apart from providing a rationale and the framework for simulation that is more efficient modelling based on process mining results, the paper provides contributions in the two case studies by deliberating and identifying potential research topics that could be tackled and supported by the new combined approach.Conclusions: Event logs and process mining provide valuable information and techniques that could be a useful input for simulation modelling, especially in the first steps of building discreteevent models, but also for validation purposes.

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Section: Methodsmentioning

confidence: 99%

Process Mining Contributions to Discrete-event Simulation Modelling

Jadrić

Pašalić

Ćukušić

2020

Business Systems Research Journal

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“…A few recommendations, similar to those in [73], do not determine a particular type of sensor; however, the developers expect that a vehicle may contain cameras, ultrasonic sensors, and radar sensors. Different methodologies, such as that presented in [74], determine that the TSOP 1738 infrared sensor is accountable for identifying the presence or nonappearance of a vehicle. All things considered, the combination of sensors will surely deliver quality arrangement since the information will come from numerous sources that have various merits.…”

Section: Types Of Sensorsmentioning

confidence: 99%

Smart Parking Systems: Reviewing the Literature, Architecture and Ways Forward

et al. 2021

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The Internet of Things (IoT) has come of age, and complex solutions can now be implemented seamlessly within urban governance and management frameworks and processes. For cities, growing rates of car ownership are rendering parking availability a challenge and lowering the quality of life through increased carbon emissions. The development of smart parking solutions is thus necessary to reduce the time spent looking for parking and to reduce greenhouse gas emissions. The principal role of this research paper is to analyze smart parking solutions from a technical perspective, underlining the systems and sensors that are available, as documented in the literature. The review seeks to provide comprehensive insights into the building of smart parking solutions. A holistic survey of the current state of smart parking systems should incorporate the classification of such systems as big vehicular detection technologies. Finally, communication modules are presented with clarity.

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“…Smart Parking solutions vary with regards to sensing technologies and methods that are used for parking space occupancy prediction and classification. When regarding the architecture of these solution it can be noticed that it is generally constituted out of three distinguishing components: type of sensors, network protocols, and software solutions [37]. In [38], the authors designed a prototype of a parking occupancy monitoring and visualization system that uses an ultrasonic sensor being controlled by an Arduino Uno which uses a Wireless XBee shield and an XBee Series 2 module for communication.…”

Section: State Of the Artmentioning

confidence: 99%

“…What is more, they are easy to implement (for instance, the Viterbi algorithm can be directly implemented as a computer algorithm) and they explicitly model the actual distribution of classes in classification problems, such as classifying a free parking space. With regards to radio technology, research of literature in [37] has shown that only 5% of researches up to date have employed LoRa for their Smart Parking Solution and, among these, none have used ML models for estimation or prediction. Although LoRa targets a wide range of applications, it has not yet been employed in a considerable amount in Smart Parking solutions [29].…”

Section: State Of the Artmentioning

confidence: 99%

Sensing Occupancy through Software: Smart Parking Proof of Concept

et al. 2020

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In order to detect the vehicle presence in parking slots, different approaches have been utilized, which range from image recognition to sensing via detection nodes. The last one is usually based on getting the presence data from one or more sensors (commonly magnetic or IR-based), controlled and processed by a micro-controller that sends the data through radio interface. Consequently, given nodes have multiple components, adequate software is required for its control and state-machine to communicate its status to the receiver. This paper presents an alternative, cost-effective beacon-based mechanism for sensing the vehicle presence. It is based on the well-known effect that, once the metallic obstacle (i.e., vehicle) is on top of the sensing node, the signal strength will be attenuated, while the same shall be recognized at the receiver side. Therefore, the signal strength change conveys the information regarding the presence. Algorithms processing signal strength change at the receiver side to estimate the presence are required due to the stochastic nature of signal strength parameters. In order to prove the concept, experimental setup based on LoRa-based parking sensors was used to gather occupancy/signal strength data. In order to extract the information of presence, the Hidden Markov Model (HMM) was employed with accuracy of up to 96%, while the Neural Network (NN) approach reaches an accuracy of up to 97%. The given approach reduces the costs of the sensor production by at least 50%.

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Smart Parking: A Literature Review from the Technological Perspective

Cited by 96 publications

References 114 publications

Process Mining Contributions to Discrete-event Simulation Modelling

Process Mining Contributions to Discrete-event Simulation Modelling

Smart Parking Systems: Reviewing the Literature, Architecture and Ways Forward

Sensing Occupancy through Software: Smart Parking Proof of Concept

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