Smart Parking System with Dynamic Pricing, Edge-Cloud Computing and LoRa

Sarker, Victor Kathan; Gia, Tuan Nguyen; Dhaou, Imed Ben; Westerlund, Tomi

doi:10.3390/s20174669

Cited by 38 publications

(18 citation statements)

References 35 publications

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“…Moreover, a vehicle smart routing system was a useful tool for assessing how air pollution caused by vehicles could be minimized by taking ecosystem services (green areas) into account [22]. Even if the impact on the environment in a real-time location based shared smart parking system was not assessed, it is found to be useful time saving solution for air pollution and efficient traffic management [25,26].…”

Section: Role Of Smart-mobility Services In Urban Environment Condition Improvementmentioning

confidence: 99%

“…The potential of reducing GHG emissions by using dynamic trip-planning and ticketing services, on-demand minibuses, and first-and last-mile ridesharing in Mexico City, London and San Francisco has been analyzed by Canales et al [24]. Moreover, several authors discussed the benefits of real-time location-based shared smart parking systems for large areas [25,26]. Research finds that smart mobility provides solutions for these fields of action, namely for air pollution [27][28][29][30], by creating new opportunities for businesses and research institutes [31].…”

Section: Introductionmentioning

confidence: 99%

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Smart-Mobility Services for Climate Mitigation in Urban Areas: Case Studies of Baltic Countries and Germany

et al. 2021

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The transport sector is one of the largest contributors of CO2 emissions and other greenhouse gases. In order to achieve the Paris goal of decreasing the global average temperature by 2 ºC, urgent and transformative actions in urban mobility are required. As a sub-domain of the smart-city concept, smart-mobility-solutions integration at the municipal level is thought to have environmental, economic and social benefits, e.g., reducing air pollution in cities, providing new markets for alternative mobility and ensuring universal access to public transportation. Therefore, this article aims to analyze the relevance of smart mobility in creating a cleaner environment and provide strategic and practical examples of smart-mobility services in four European cities: Berlin (Germany), Kaunas (Lithuania), Riga (Latvia) and Tartu (Estonia). The paper presents a systematized literature review about the potential of smart-mobility services in reducing the negative environmental impact to urban environments in various cities. The authors highlight broad opportunities from the European Union and municipal documents for smart-mobility initiatives. The theoretical part is supplemented by socioeconomic and environmental descriptions, as well as experience, related to smart-mobility services in the four cities selected.

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Section: Role Of Smart-mobility Services In Urban Environment Condition Improvementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Smart-Mobility Services for Climate Mitigation in Urban Areas: Case Studies of Baltic Countries and Germany

et al. 2021

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“…The system accumulates all messages in the messaging server for further processing if the main server for information collection fails. Another smart parking solution with a pricing algorithm for revenue maximization was proposed in [35]. The price is dynamically set to balance the available and requested parking spots and ensure the minimum parking fee is charged.…”

Section: Related Workmentioning

confidence: 99%

“…where Rate m is the maximum rate that the mth driver will pay. The sorting algorithms Merge Sort or Heapsort [35] can be used to search for the optimal maximum value, due to their low complexity.…”

Section: Hybrid Pricing Algorithmmentioning

confidence: 99%

Design and Development of Smart Parking System Based on Fog Computing and Internet of Things

et al. 2021

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Current parking systems employ a single gateway-centered solution (i.e., cloud) for data processing which leads to the possibility of a single point of failure, data loss, and high delays. Moreover, the parking-spot selection process considers criteria that do not maximize parking utilization and revenue. The pricing strategy does not achieve high revenue because a fixed pricing rate is utilized. To address these issues, this paper proposes a smart parking system based on the Internet of Things (IoT) that provides useful information to drivers and parking administrators about available parking spots and related services such as parking navigation, reservation, and availability estimation. A multi-layer architecture is developed that consists of multiple sensor nodes, and fog and cloud computing layers. The acquired parking data are processed through fog computing nodes to facilitate obtaining the required real-time parking data. A novel algorithm to obtain the optimal parking spot with the minimum arrival time is also presented. Proof-of-concept implementation and simulation evaluations are conducted to validate the system performance. The findings show that the system reduces the parking arrival time by 16–46% compared to current parking systems. In addition, the revenue is increased for the parking authority by 10–15%.

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“…This problem is severe and affects several aspects of human life. The lack of parking lots causes traffic congestion because people searching or waiting for an available parking lot move slowly, causing a long queue to form on streets and blocking other cars [ 3 ]. Moreover, cars moving slowly when searching for parking increases carbon emissions [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Space Allocation Based on Internal Demand for Optimizing Release of Shared Parking

Chou

Dewabharata

Zulvia

2021

Sensors

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The size of cities has been continuously increasing because of urbanization. The number of public and private transportation vehicles is rapidly increasing, thus resulting in traffic congestion, traffic accidents, and environmental pollution. Although major cities have undergone considerable development in terms of transportation infrastructure, problems caused by a high number of moving vehicles cannot be completely resolved through the expansion of streets and facilities. This paper proposes a solution for the parking problem in cities that entails a shared parking system. The primary concept of the proposed shared parking system is to release parking lots that are open to specific groups for public usage without overriding personal usage. Open-to-specific-groups parking lots consist of parking spaces provided for particular people, such as parking buildings at universities for teachers, staff, and students. The proposed shared parking system comprises four primary steps: collecting and preprocessing data by using an Internet of Things system, predicting internal demand by using a recurrent neural network algorithm, releasing several unoccupied parking lots based on prediction results, and continuously updating the real-time data to improve future internal usage prediction. Data collection and data forecasting are performed to ensure that the system does not override personal usage. This study applied several forecasting algorithms, including seasonal ARIMA, support vector regression, multilayer perceptron, convolutional neural network, long short-term memory recurrent neural network with a many-to-one structure, and long short-term memory recurrent neural network with a many-to-many structure. The proposed system was evaluated using artificial and real datasets. Results show that the recurrent neural network with the many-to-many structure generates the most accurate prediction. Furthermore, the proposed shared parking system was evaluated for some scenarios in which different numbers of parking spaces were released. Simulation results show that the proposed shared parking system can provide parking spaces for public usage without overriding personal usage. Moreover, this system can generate new income for parking management and/or parking lot owners.

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Smart Parking System with Dynamic Pricing, Edge-Cloud Computing and LoRa

Cited by 38 publications

References 35 publications

Smart-Mobility Services for Climate Mitigation in Urban Areas: Case Studies of Baltic Countries and Germany

Smart-Mobility Services for Climate Mitigation in Urban Areas: Case Studies of Baltic Countries and Germany

Design and Development of Smart Parking System Based on Fog Computing and Internet of Things

Dynamic Space Allocation Based on Internal Demand for Optimizing Release of Shared Parking

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