Detection and recognition of moving biological objects for autonomous vehicles using intelligent edge computing/LoRaWAN mesh system

Volkov Artem; Malik Al-Sveiti; Ibrahim A. Elgendy; Alexey S. Kovtunenko; Ammar Muthanna

doi:10.1007/978-3-030-65729-1_1

Detection and recognition of moving biological objects for autonomous vehicles using intelligent edge computing/LoRaWAN mesh system

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

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

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 Intel- ligence 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.

Original language	English
Title of host publication	Internet of Things, Smart Spaces, and Next Generation Networks and Systems - 20th International Conference, NEW2AN 2020 and 13th Conference, ruSMART 2020, Proceedings
Editors	Olga Galinina, Sergey Andreev, Sergey Balandin, Yevgeni Koucheryavy
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	3-15
Number of pages	13
ISBN (Print)	9783030657284
DOIs	https://doi.org/10.1007/978-3-030-65729-1_1
State	Published - 2020
Externally published	Yes
Event	20th International Conference on Next Generation Teletraffic and Wired/Wireless Advanced Networks and Systems, NEW2AN 2020 and 13th Conference on the Internet of Things and Smart Spaces, ruSMART 2020 - St. Petersburg, Russian Federation Duration: 26 Aug 2020 → 28 Aug 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12526 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	20th International Conference on Next Generation Teletraffic and Wired/Wireless Advanced Networks and Systems, NEW2AN 2020 and 13th Conference on the Internet of Things and Smart Spaces, ruSMART 2020
Country/Territory	Russian Federation
City	St. Petersburg
Period	26/08/20 → 28/08/20

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2020.

Keywords

5G/IMT-2020
AI
Autonomous vehicles
IMT-2030
IoT
LoRaWAN mesh
MEC

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-65729-1_1

Cite this

Artem, V., Al-Sveiti, M., Elgendy, I. A., Kovtunenko, A. S., & Muthanna, A. (2020). Detection and recognition of moving biological objects for autonomous vehicles using intelligent edge computing/LoRaWAN mesh system. In O. Galinina, S. Andreev, S. Balandin, & Y. Koucheryavy (Eds.), Internet of Things, Smart Spaces, and Next Generation Networks and Systems - 20th International Conference, NEW2AN 2020 and 13th Conference, ruSMART 2020, Proceedings (pp. 3-15). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12526 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-65729-1_1

Artem, Volkov ; Al-Sveiti, Malik ; Elgendy, Ibrahim A. et al. / Detection and recognition of moving biological objects for autonomous vehicles using intelligent edge computing/LoRaWAN mesh system. Internet of Things, Smart Spaces, and Next Generation Networks and Systems - 20th International Conference, NEW2AN 2020 and 13th Conference, ruSMART 2020, Proceedings. editor / Olga Galinina ; Sergey Andreev ; Sergey Balandin ; Yevgeni Koucheryavy. Springer Science and Business Media Deutschland GmbH, 2020. pp. 3-15 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Detection and recognition of moving biological objects for autonomous vehicles using intelligent edge computing/LoRaWAN mesh system",

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 Intel- ligence 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{\textquoteright}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.",

keywords = "5G/IMT-2020, AI, Autonomous vehicles, IMT-2030, IoT, LoRaWAN mesh, MEC",

author = "Volkov Artem and Malik Al-Sveiti and Elgendy, \{Ibrahim A.\} and Kovtunenko, \{Alexey S.\} and Ammar Muthanna",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020.; 20th International Conference on Next Generation Teletraffic and Wired/Wireless Advanced Networks and Systems, NEW2AN 2020 and 13th Conference on the Internet of Things and Smart Spaces, ruSMART 2020 ; Conference date: 26-08-2020 Through 28-08-2020",

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publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "3--15",

editor = "Olga Galinina and Sergey Andreev and Sergey Balandin and Yevgeni Koucheryavy",

booktitle = "Internet of Things, Smart Spaces, and Next Generation Networks and Systems - 20th International Conference, NEW2AN 2020 and 13th Conference, ruSMART 2020, Proceedings",

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Artem, V, Al-Sveiti, M, Elgendy, IA, Kovtunenko, AS & Muthanna, A 2020, Detection and recognition of moving biological objects for autonomous vehicles using intelligent edge computing/LoRaWAN mesh system. in O Galinina, S Andreev, S Balandin & Y Koucheryavy (eds), Internet of Things, Smart Spaces, and Next Generation Networks and Systems - 20th International Conference, NEW2AN 2020 and 13th Conference, ruSMART 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12526 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 3-15, 20th International Conference on Next Generation Teletraffic and Wired/Wireless Advanced Networks and Systems, NEW2AN 2020 and 13th Conference on the Internet of Things and Smart Spaces, ruSMART 2020, St. Petersburg, Russian Federation, 26/08/20. https://doi.org/10.1007/978-3-030-65729-1_1

Detection and recognition of moving biological objects for autonomous vehicles using intelligent edge computing/LoRaWAN mesh system. / Artem, Volkov; Al-Sveiti, Malik; Elgendy, Ibrahim A. et al.
Internet of Things, Smart Spaces, and Next Generation Networks and Systems - 20th International Conference, NEW2AN 2020 and 13th Conference, ruSMART 2020, Proceedings. ed. / Olga Galinina; Sergey Andreev; Sergey Balandin; Yevgeni Koucheryavy. Springer Science and Business Media Deutschland GmbH, 2020. p. 3-15 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12526 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Detection and recognition of moving biological objects for autonomous vehicles using intelligent edge computing/LoRaWAN mesh system

AU - Artem, Volkov

AU - Al-Sveiti, Malik

AU - Elgendy, Ibrahim A.

AU - Kovtunenko, Alexey S.

AU - Muthanna, Ammar

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2020.

PY - 2020

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AB - 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 Intel- ligence 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.

KW - 5G/IMT-2020

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KW - Autonomous vehicles

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M3 - Conference contribution

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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ER -

Artem V, Al-Sveiti M, Elgendy IA, Kovtunenko AS, Muthanna A. Detection and recognition of moving biological objects for autonomous vehicles using intelligent edge computing/LoRaWAN mesh system. In Galinina O, Andreev S, Balandin S, Koucheryavy Y, editors, Internet of Things, Smart Spaces, and Next Generation Networks and Systems - 20th International Conference, NEW2AN 2020 and 13th Conference, ruSMART 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 3-15. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-65729-1_1

Detection and recognition of moving biological objects for autonomous vehicles using intelligent edge computing/LoRaWAN mesh system

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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Cite this