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Green Energy-Based Efficient IoT Sensor Network for Small Farms

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Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST,volume 436)


The recent advancement in the Internet of Things (IoT) makes crop management much smarter and helps optimize resource consumption in the agriculture industry. However, due to the high deployment and operational cost of IoT-based infrastructure, it becomes pretty expansive to be afforded by small farm holders. In this paper, an energy-efficient, low-cost, in-house wireless sensor network has been developed and established for collecting important field parameters directly from small household farms. The sensor nodes equipped with in-situ sensors were placed in the test field. The parameters such as atmospheric temperature, humidity, and soil moisture are measured through various sensors. Consequently, the sensors’ data is transferred from the sensor nodes to the Gateway via Long-range (LoRA) communication. The Gateway is designed to push the sensor data to the application server (ThingSpeak) through the Long-range wide-area network (LoRAWAN) protocol. The performance of the proposed LoRaWAN based WSN was tested over the 868 MHz unlicensed ISM indoor network setup for an entire season of rice crop and found satisfactory even in the harsh propagation environment.


  • Sensor network
  • Sensor node
  • Gateway

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  • DOI: 10.1007/978-3-031-01984-5_2
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This work is fully funded and supported by the project 'Digital Village: A Data-Driven Approach to Precision Agriculture in Small Farms,' under the TIET-TAU center of excellence for food security (T2CEFS) in Thapar Institute of Engineering and Technology (A central university), Patiala, Punjab, India. I thank all the co-authors for their expertise and assistance throughout our study and help in writing the manuscript.

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Correspondence to Amit Mishra .

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Mishra, A., Singh, S., Verma, K., Bhatia, P., Ghosh, M., Shacham-Diamand, Y. (2022). Green Energy-Based Efficient IoT Sensor Network for Small Farms. In: Seyman, M.N. (eds) Electrical and Computer Engineering. ICECENG 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 436. Springer, Cham.

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