Intelligent systems framework for real-time crop monitoring and agricultural resilience
Maharishi International University, Fairfield.
Review Article
World Journal of Advanced Research and Reviews, 2023, 20(02), 1644–1655
Publication history:
Received on 04 August 2023; revised on 22 September 2023; accepted on 28 November 2023
Abstract:
Agriculture must deal with the rising strain of climate change, harmful environmental factors, and scarcities of supply, which make yield lower and raise risk, especially in rain-fed areas. Traditional farming methods are dependent on physical observation and reactive decisions’ making. Such methods fail to deal with these ever-increasing threats. The researcher offers in this paper an Idea System Framework for Real-Time Crop Monitoring and Agricultural Resilience to carry IoT sensing, last mile images from drones, computer AI, and flexible decision making. The prototype means to Granville voluminous environmental and crop data, real time trend testing, stress, pest, and disease alerts, farmers’ action suggestions. Random tests at 7 farming sites showed there was high sensor accuracy (soil: 96.2%, humidity: 95.8%), drone imaging (covering 12 hectares to flight at 0.5 pixels/cm2), robust prediction with AI (crop: 92.5%, pest: 91.3%), and decision making (intervention: 93.4%, alert: 5 mins) leading to few false alarms (0.3 grains/ha). Based on composite scores, Precision: 92.3%. All these findings show that the packing helps timely action, farm Customer Management, and overcome the price of change. By bringing hour-old and deck the amount of a height for sensory, analytics, and suggestions to generating one -- the built-in framework data-driven approach to risk-adaption, increases farm identity. At scale it is suitable to input for all types of farming with environmental veers that offers affordably in time, resource, environment centric inputs and outputs. In addition, this work provides a solution for bringing real-time monitoring of the crops together with intelligent, data-based analytical tools to help all systems of farming, whether in the hands of a small group, or anywhere else, which can suffer risk, use the available resources better, and make sure the long term productivity of the farms is not shortened.
Keywords:
Intelligent agricultural systems; Real-time crop monitoring; Internet of Things (IoT); Unmanned aerial vehicles (UAV); Artificial intelligence in agriculture; Agricultural resilience
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0