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Smart city article details
| Title | Vehicular Intelligence System: Time-Based Vehicle Next Location Prediction In Software-Defined Internet Of Vehicles (Sdn-Iov) For The Smart Cities |
|---|---|
| ID_Doc | 60996 |
| Authors | Rani P.; Hussain N.; Khan R.A.H.; Sharma Y.; Shukla P.K. |
| Year | 2021 |
| Published | Intelligence of Things: AI-IoT Based Critical-Applications and Innovations |
| DOI | http://dx.doi.org/10.1007/978-3-030-82800-4_2 |
| Abstract | Background Theory: The development of traditional Vehicular Ad-Hoc Networks (VANETs) into the Internet of Vehicles (IOV) is inspired by the modern era of the Internet of Things (IoT). The smart city technologies can offer suitable services based on the citizens' demands. The Internet of Things (IoT) technology, that allows a large number of devices to communicate with one another, is one of the key enablers in Smart Cities (SC). Objective: This chapter is an outline of SC and the next position's prediction using software-defined IoT-based VANETs, known as IOV networks. This chapter is designed in three-phase: (1) Smart Cities (SC) deployment, (2) improved data forwarding, and (3) location prediction of vehicle. The vehicular intelligence system considers road conditions, traffic density, current position, and cars' speed. Methodology: The proposed Artificial Intelligence (AI) Model helps the Software-Defined Controller (SDN), centralized controller to calculate and predict future status inside and outside the area. To evaluate the proposed system, the SUMO simulator with Open Street map (OSM) is taken into account, and the outcome shows the significance of vehicle location prediction for VANET. Result: The mathematical examination and simulation results on Network Simulator 3 and SUMO shows a higher packet delivery ratio (PDR) as compared to the existing protocol. The proposed protocol ERS-SDN-IOV shows a less delivery transmission time compared to the AODV, GPSR, and SDGR. It is having the 95% delivery ratio and 50% lesser transmission time as compare to mention existing protocols. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved. |
| Author Keywords | Artificial Intelligence (AI); Edge controllers; Internet of Vehicles (IOV); SDN; Traffic Control; Vehicular Network |
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