Parking Easier by Using Context Information of a Smart City: Enabling Fast Search and Management of Parking Resources

Abstract

In the great majority of cities it is difficult and hardly expensive to create more parking spaces for vehicles since they have almost reached its full occupancy. Combining this problem with an inefficient use of parking spaces leads to congestions due to aggregation of parking seekers and regular drivers. Recent advances in low-cost, low-power embedded systems bring the opportunity to develop new applications to solve these problems. In particular, Smart Cities greatly enrich their sustainability by introducing new resource management applications that rely in those constrained devices a significant part of the functionality of the system. The proposed Smart Parking solution consists mainly in the on-site deployment of an IoT solution to monitor and signalize the state of availability of each single parking space, as well as using context information generated by the city and its citizens to provide accurate responses to driver's demands. Furthermore, this system improves the management of parking resources by public authorities, for instance handling groups of parking spaces facilitating the whole city traffic management. The integration of this deployment into an existing live test-bed implies an easy task requiring just the data collection through the available means of the parking spaces availability. At the present time there exist living test-beds which can be used to integrate these new functionalities for experimentation on IoT data level, to gain a better knowledge and understanding of the M2M world, reducing costs, resources, pollution and time.