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LoRaWAN-Based Energy-Efficient Surveillance by Drones for Intelligent Transportation Systems

Author

Listed:
  • Vishal Sharma

    (Department of Information Security Engineering, Soonchunhyang University, Asan-si 31538, Korea)

  • Ilsun You

    (Department of Information Security Engineering, Soonchunhyang University, Asan-si 31538, Korea)

  • Giovanni Pau

    (Faculty of Engineering and Architecture, Kore University of Enna, 94100 Enna, Italy)

  • Mario Collotta

    (Faculty of Engineering and Architecture, Kore University of Enna, 94100 Enna, Italy)

  • Jae Deok Lim

    (Electronics and Telecommunications Research Institute, Daejeon 34129, Korea)

  • Jeong Nyeo Kim

    (Electronics and Telecommunications Research Institute, Daejeon 34129, Korea)

Abstract

Urban networks aim at facilitating users for better experience and services through smart platforms such as the Intelligent Transportation System (ITS). ITS focuses on information acquisition, sensing, contrivance control, data processing and forwarding to ground devices via user-specific application-interfaces. The utility of ITS is further improved via the Internet of Things (IoT), which supports “Connectivity to All”. One of the key applications of IoT-ITS is urban surveillance. Current surveillance in IoT-ITS is performed via fixed infrastructure-based sensing applications which consume an excessive amount of energy leading to several overheads and failures in the network. Such issues can be overcome by the utilization of on-demand nodes, such as drones, etc. However, drones-assisted surveillance requires efficient communication setup as drones are battery operated and any extemporaneous maneuver during monitoring may result in loss of drone or complete failure of the network. The novelty in terms of network layout can be procured by the utilization of drones with LoRaWAN, which is the protocol designated for Low-Power Wide Area Networks (LPWAN). However, even this architectural novelty alone cannot ascertain the formation of fail-safe, highly resilient, low-overhead, and non-redundant network, which is additionally the problem considered in this paper. To resolve such problem, this paper uses drones as LoRaWAN gateway and proposes a communication strategy based on the area stress, resilient factor, and energy consumption that avail in the efficient localization, improved coverage and energy-efficient surveillance with lower overheads, lower redundancy, and almost zero-isolations. The proposed approach is numerically simulated and the results show that the proposed approach can conserve a maximum of 39.2% and a minimum of 12.6% of the total network energy along with an improvement in the area stress between 89.7% and 53.0% for varying number of drones over a fixed area.

Suggested Citation

  • Vishal Sharma & Ilsun You & Giovanni Pau & Mario Collotta & Jae Deok Lim & Jeong Nyeo Kim, 2018. "LoRaWAN-Based Energy-Efficient Surveillance by Drones for Intelligent Transportation Systems," Energies, MDPI, vol. 11(3), pages 1-26, March.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:3:p:573-:d:135011
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    References listed on IDEAS

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    1. Maxim Finkelstein, 2008. "Failure Rate Modelling for Reliability and Risk," Springer Series in Reliability Engineering, Springer, number 978-1-84800-986-8, June.
    2. Francisco Martins Portelinha Júnior & Antonio Carlos Zambroni de Souza & Miguel Castilla & Denisson Queiroz Oliveira & Paulo Fernando Ribeiro, 2017. "Control Strategies for Improving Energy Efficiency and Reliability in Autonomous Microgrids with Communication Constraints," Energies, MDPI, vol. 10(9), pages 1-16, September.
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    Cited by:

    1. Mario Collotta & Yunchuan Sun & Luca Di Persio & Emad Samuel Malki Ebeid & Riccardo Muradore, 2018. "Smart Green Applications: From Renewable Energy Management to Intelligent Transportation Systems," Energies, MDPI, vol. 11(5), pages 1-3, May.
    2. Mariusz Nowak & Piotr Derbis & Krzysztof Kurowski & Rafał Różycki & Grzegorz Waligóra, 2021. "LPWAN Networks for Energy Meters Reading and Monitoring Power Supply Network in Intelligent Buildings," Energies, MDPI, vol. 14(23), pages 1-14, November.
    3. Milos Maryska & Petr Doucek & Pavel Sladek & Lea Nedomova, 2019. "Economic Efficiency of the Internet of Things Solution in the Energy Industry: A Very High Voltage Frosting Case Study," Energies, MDPI, vol. 12(4), pages 1-16, February.
    4. Aleksandra Tiurlikova & Nikita Stepanov & Konstantin Mikhaylov, 2019. "Wireless power transfer from unmanned aerial vehicle to low-power wide area network nodes: Performance and business prospects for LoRaWAN," International Journal of Distributed Sensor Networks, , vol. 15(11), pages 15501477198, November.
    5. Auwal Alhassan Musa & Salim Idris Malami & Fayez Alanazi & Wassef Ounaies & Mohammed Alshammari & Sadi Ibrahim Haruna, 2023. "Sustainable Traffic Management for Smart Cities Using Internet-of-Things-Oriented Intelligent Transportation Systems (ITS): Challenges and Recommendations," Sustainability, MDPI, vol. 15(13), pages 1-15, June.

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