LoRa Communication for Agriculture 4.0: Opportunities, Challenges, and Future Directions

September 17, 2024 Β· Declared Dead Β· πŸ› IEEE Internet of Things Journal

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Authors Lameya Aldhaheri, Noor Alshehhi, Irfana Ilyas Jameela Manzil, Ruhul Amin Khalil, Shumaila Javaid, Nasir Saeed, Mohamed-Slim Alouini arXiv ID 2409.11200 Category cs.NI: Networking & Internet Cross-listed cs.ET, cs.LG Citations 46 Venue IEEE Internet of Things Journal Last Checked 6 months ago
Abstract
The emerging field of smart agriculture leverages the Internet of Things (IoT) to revolutionize farming practices. This paper investigates the transformative potential of Long Range (LoRa) technology as a key enabler of long-range wireless communication for agricultural IoT systems. By reviewing existing literature, we identify a gap in research specifically focused on LoRa's prospects and challenges from a communication perspective in smart agriculture. We delve into the details of LoRa-based agricultural networks, covering network architecture design, Physical Layer (PHY) considerations tailored to the agricultural environment, and channel modeling techniques that account for soil characteristics. The paper further explores relaying and routing mechanisms that address the challenges of extending network coverage and optimizing data transmission in vast agricultural landscapes. Transitioning to practical aspects, we discuss sensor deployment strategies and energy management techniques, offering insights for real-world deployments. A comparative analysis of LoRa with other wireless communication technologies employed in agricultural IoT applications highlights its strengths and weaknesses in this context. Furthermore, the paper outlines several future research directions to leverage the potential of LoRa-based agriculture 4.0. These include advancements in channel modeling for diverse farming environments, novel relay routing algorithms, integrating emerging sensor technologies like hyper-spectral imaging and drone-based sensing, on-device Artificial Intelligence (AI) models, and sustainable solutions. This survey can guide researchers, technologists, and practitioners to understand, implement, and propel smart agriculture initiatives using LoRa technology.
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