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2020 | OriginalPaper | Chapter

Detection and Recognition of Moving Biological Objects for Autonomous Vehicles Using Intelligent Edge Computing/LoRaWAN Mesh System

Authors : Volkov Artem, Malik Al-Sveiti, Ibrahim A. Elgendy, Alexey S. Kovtunenko, Ammar Muthanna

Published in: Internet of Things, Smart Spaces, and Next Generation Networks and Systems

Publisher: Springer International Publishing

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Abstract

Currently, 5G/IMT-2020 networks with their possibilities become more and more services of new areas. These services are integrated into different human life activities. And in several cases, human life depends on Artificial Intelligence technologies, Autonomous Systems, and the Internet of Things (IoT), etc. Autonomous vehicles provide very strict requirements to the network in terms of ultra-low latency, high throughput, and wide coverage. To support these requirements, additional technologies must be employed. The current paper discusses the possibility of the use of airborne platforms aiming to support the terrestrial networks for autonomous vehicles realization as a part of delay-critical applications. Airborne platforms will help in the provisioning of safe road trips by delivering time-critical information to the vehicles globally, even in remote areas. In this paper, we discuss requirements and potential solutions for supporting the autonomous vehicle infrastructure, as a part of an intelligent transportation system. It’s proposed to use a sensor network along the road, consists of energy-efficient sensors that can connect in a Mesh network. Also, a novel approach for the detection of biological objects activity on the roadside, based on Artificial Intelligence technologies are suggested.

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Title: Detection and Recognition of Moving Biological Objects for Autonomous Vehicles Using Intelligent Edge Computing/LoRaWAN Mesh System
Authors: Volkov Artem
Malik Al-Sveiti
Ibrahim A. Elgendy
Alexey S. Kovtunenko
Ammar Muthanna
Publisher: Springer International Publishing
Book: Internet of Things, Smart Spaces, and Next Generation Networks and Systems
Print ISBN: 978-3-030-65728-4

Electronic ISBN: 978-3-030-65729-1

Copyright Year: 2020
DOI: https://doi.org/10.1007/978-3-030-65729-1_1

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