UAV-assisted federated learning with hybrid LoRa P2P/LoRaWAN for sustainable biosphere
The increasing amount of data sensors generate, and the dynamic nature of climate and environment pose challenges for conventional smart environmental monitoring systems. These systems encounter difficulties in long-distance data communication, accurate data processing, and generalized prediction mo...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Communications and Networks |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/frcmn.2025.1529453/full |
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| author | Mehran Behjati Haider A. H. Alobaidy Rosdiadee Nordin Nor Fadzilah Abdullah |
| author_facet | Mehran Behjati Haider A. H. Alobaidy Rosdiadee Nordin Nor Fadzilah Abdullah |
| author_sort | Mehran Behjati |
| collection | DOAJ |
| description | The increasing amount of data sensors generate, and the dynamic nature of climate and environment pose challenges for conventional smart environmental monitoring systems. These systems encounter difficulties in long-distance data communication, accurate data processing, and generalized prediction modeling, particularly in large-scale, remote, and hard-to-reach areas. Moreover, they are costly, complex, and inefficient, especially in regions with limited telecommunications infrastructure. Consequently, there is a pressing need for more efficient and effective monitoring techniques to safeguard natural resources and ecosystems. To address these challenges, we propose the concept of a novel environmental monitoring system that integrates aerial access networks (AAN), federated learning (FL), and hybrid LoRa Point-to-Point (P2P)/LoRaWAN technologies. This integration offers a reliable and efficient solution for monitoring remote regions. We provide an overview of the AAN, FL, and aerial FL paradigms and discuss the benefits and challenges of their integration. Preliminary simulation results demonstrated the proposed system’s feasibility and effectiveness. Lastly, we outline open challenges and potential research directions to advance this field. |
| format | Article |
| id | doaj-art-33ea6f46d3f4439e9897c4c4b31a6115 |
| institution | Kabale University |
| issn | 2673-530X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Communications and Networks |
| spelling | doaj-art-33ea6f46d3f4439e9897c4c4b31a61152025-01-30T06:22:43ZengFrontiers Media S.A.Frontiers in Communications and Networks2673-530X2025-01-01610.3389/frcmn.2025.15294531529453UAV-assisted federated learning with hybrid LoRa P2P/LoRaWAN for sustainable biosphereMehran Behjati0Haider A. H. Alobaidy1Rosdiadee Nordin2Nor Fadzilah Abdullah3Department of Smart Computing and Cyber Resilience, School of Engineering & Technology, Sunway University, Sunway, MalaysiaDepartment of Information and Communications Engineering, College of Information Engineering, Al-Nahrain University, Baghdad, IraqDepartment of Smart Computing and Cyber Resilience, School of Engineering & Technology, Sunway University, Sunway, MalaysiaDepartment of Electrical, Electronic & Systems Engineering, Universiti Kebangsaan Malaysia (UKM), Bangi, MalaysiaThe increasing amount of data sensors generate, and the dynamic nature of climate and environment pose challenges for conventional smart environmental monitoring systems. These systems encounter difficulties in long-distance data communication, accurate data processing, and generalized prediction modeling, particularly in large-scale, remote, and hard-to-reach areas. Moreover, they are costly, complex, and inefficient, especially in regions with limited telecommunications infrastructure. Consequently, there is a pressing need for more efficient and effective monitoring techniques to safeguard natural resources and ecosystems. To address these challenges, we propose the concept of a novel environmental monitoring system that integrates aerial access networks (AAN), federated learning (FL), and hybrid LoRa Point-to-Point (P2P)/LoRaWAN technologies. This integration offers a reliable and efficient solution for monitoring remote regions. We provide an overview of the AAN, FL, and aerial FL paradigms and discuss the benefits and challenges of their integration. Preliminary simulation results demonstrated the proposed system’s feasibility and effectiveness. Lastly, we outline open challenges and potential research directions to advance this field.https://www.frontiersin.org/articles/10.3389/frcmn.2025.1529453/fullfederated learningaerial access networkUAVLORAwireless sensor networksenvironmental conservation |
| spellingShingle | Mehran Behjati Haider A. H. Alobaidy Rosdiadee Nordin Nor Fadzilah Abdullah UAV-assisted federated learning with hybrid LoRa P2P/LoRaWAN for sustainable biosphere Frontiers in Communications and Networks federated learning aerial access network UAV LORA wireless sensor networks environmental conservation |
| title | UAV-assisted federated learning with hybrid LoRa P2P/LoRaWAN for sustainable biosphere |
| title_full | UAV-assisted federated learning with hybrid LoRa P2P/LoRaWAN for sustainable biosphere |
| title_fullStr | UAV-assisted federated learning with hybrid LoRa P2P/LoRaWAN for sustainable biosphere |
| title_full_unstemmed | UAV-assisted federated learning with hybrid LoRa P2P/LoRaWAN for sustainable biosphere |
| title_short | UAV-assisted federated learning with hybrid LoRa P2P/LoRaWAN for sustainable biosphere |
| title_sort | uav assisted federated learning with hybrid lora p2p lorawan for sustainable biosphere |
| topic | federated learning aerial access network UAV LORA wireless sensor networks environmental conservation |
| url | https://www.frontiersin.org/articles/10.3389/frcmn.2025.1529453/full |
| work_keys_str_mv | AT mehranbehjati uavassistedfederatedlearningwithhybridlorap2plorawanforsustainablebiosphere AT haiderahalobaidy uavassistedfederatedlearningwithhybridlorap2plorawanforsustainablebiosphere AT rosdiadeenordin uavassistedfederatedlearningwithhybridlorap2plorawanforsustainablebiosphere AT norfadzilahabdullah uavassistedfederatedlearningwithhybridlorap2plorawanforsustainablebiosphere |