4.8 Article

AgriSens: IoT-Based Dynamic Irrigation Scheduling System for Water Management of Irrigated Crops

Journal

IEEE INTERNET OF THINGS JOURNAL
Volume 8, Issue 6, Pages 5023-5030

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2020.3036126

Keywords

Irrigation; Wireless sensor networks; Internet of Things; Manuals; Dynamic scheduling; Real-time systems; Logic gates; Internet of Things (IoT); irrigated crop; precision agriculture; smart irrigation; water management system; wireless sensor node

Funding

  1. Ministry of Human Resource Development, Government of India under MHRD/IIT Kharagpur Food Security Project [425/2013-TS-I]
  2. NSF [SCC-1952045]

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AgriSens is a dynamic irrigation scheduling system based on the Internet of Things, providing real-time, automatic, and remote manual irrigation treatment to improve crop productivity and achieve significant results in various climatic conditions.
In this article, we present the design of an Internet-of-Things (IoT)-based dynamic irrigation scheduling system (AgriSens) for efficient water management of irrigated crop fields. The AgriSens provides real time, automatic, dynamic as well as remote manual irrigation treatment for different growth phases of a crop's life cycle using IoT. A low-cost water-level sensor is designed to measure the level of water present in a field. We propose an algorithm for automatic dynamic-cum-manual irrigation based on farmer requirements. The AgriSens has a farmer-friendly user interface, which provides field information to the farmers in a multimodal manner-visual display, cell phone, and Web portal. It achieves significant results with respect to different performance metrics, such as data validation, packet delivery ratio, energy consumption, and failure rate in various climatic conditions and with dynamic irrigation treatments. Experimental results show that the AgriSens helps improve the crop productivity by at most 10.21% over the traditional manual irrigation method, expands the network's lifetime 2.5 times more than the existing system yet achieving a reliability of 94% even after 500 h of operation.

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