In this paper, we propose a novel IoT-based smart parking (SP) solution which has been designed to provide information on the status of parking spots offered in on-street parking areas. We mostly focused on the following issues of the state of the art solutions: scalability, interoperability to address the heterogeneity of IoT devices, low energy consumption, and timely prediction of the availability of the parking spots. To this we leverage the Social IoT (SIoT) Lysis environment to create virtual entities of the real world objects involved in the SP system for on-street parking areas. The usage of the social virtual entities allows for addressing the interoperability issues among different types of IoT devices used by separate solutions deployed in adjacent areas. Magnetometer sensors are used to automatically detect the presence of a vehicle in each parking spot and the sensors data are collected through concentrators that cover the whole parking areas through low-energy Wi-Fi. Additionally, a control dashboard has been designed and developed to manage the monitored parking areas and provide responsive data analytics regarding the occupancy of parking areas in the city, which can be accessed through an Android App. Finally, a smart payment service allows the users to automatically pay for the used services making use of Bluetooth beacons. Experiments have been performed with the developed test-bed to show the performance of the system to timely detect the presence of a vehicle and identify the owner ID to trigger the payment procedure.

A Social IoT-based platform for the deployment of a smart parking solution

Floris A.
;
Porcu S.;Atzori L.;Girau R.
2022-01-01

Abstract

In this paper, we propose a novel IoT-based smart parking (SP) solution which has been designed to provide information on the status of parking spots offered in on-street parking areas. We mostly focused on the following issues of the state of the art solutions: scalability, interoperability to address the heterogeneity of IoT devices, low energy consumption, and timely prediction of the availability of the parking spots. To this we leverage the Social IoT (SIoT) Lysis environment to create virtual entities of the real world objects involved in the SP system for on-street parking areas. The usage of the social virtual entities allows for addressing the interoperability issues among different types of IoT devices used by separate solutions deployed in adjacent areas. Magnetometer sensors are used to automatically detect the presence of a vehicle in each parking spot and the sensors data are collected through concentrators that cover the whole parking areas through low-energy Wi-Fi. Additionally, a control dashboard has been designed and developed to manage the monitored parking areas and provide responsive data analytics regarding the occupancy of parking areas in the city, which can be accessed through an Android App. Finally, a smart payment service allows the users to automatically pay for the used services making use of Bluetooth beacons. Experiments have been performed with the developed test-bed to show the performance of the system to timely detect the presence of a vehicle and identify the owner ID to trigger the payment procedure.
2022
Internet of Things; Vehicle detection; Smart parking
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/326989
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