| Title |
An Investigation of Garbage Disposal Electric Vehicles (GDEVs) Integrated with Deep Neural Networking (DNN) and Intelligent Transportation System (ITS) in Smart City Management System (SCMS) |
| ID_Doc |
37293 |
| Authors |
Yuvaraj, N; Praghash, K; Raja, RA; Karthikeyan, T |
| Title |
An Investigation of Garbage Disposal Electric Vehicles (GDEVs) Integrated with Deep Neural Networking (DNN) and Intelligent Transportation System (ITS) in Smart City Management System (SCMS) |
| Year |
2022 |
| Published |
Wireless Personal Communications, 123.0, 2 |
| Abstract |
A smart city is a urban developed city that delivers the solution to the residents smarter especially using Information and Communication Technology. The conventional smart city management modules use sensors or IoT devices in conjunction with Intelligent Traffic System (ITS), however, these frameworks fail in managing the Electric Vehicles (EVs) routing with security or scheduling the EV for charging and smart energy distribution for the EVs. In this paper, we present a novel Smart City Management System (SCMS) with the integration of three immersive technologies are adopted to improve the management of garbage disposal EVs (GDEVs). Initially, the study uses IoT devices to collect the status of garbage bins. Secondly, the ITS is integrated with Deep Neural Networks (DNNs) to manage the GDEVs for effective traffic management and speed monitoring based on the collected information like garbage payloads, climatic conditions and distance between the collection, disposal of waste etc. Finally, the entire transmitted data between IoTs and EVs are secured effectively using blockchain technology, which protects them against cybersecurity attacks. The experimental validation on proposed SCMS with DNN-ITS and secured blockchain model offers improved energy efficiency, faster transmission and enhanced security capabilities than existing methods. |
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