Edge Computing for Real-Time Crop Health Monitoring in Precision Agriculture

The autonomous and edge agricultural systems are providing a refreshing change in precision farming. The old methodologies of smart farming have paid a lot of attention to the real-time streaming and responsive processes such as pesticide spraying or irrigation of a certain specific process. However, these approaches disregard the higher order biotic news ones, and are more likely to disregard deep, interplay, the implications of which biotic interactions could have on the health of the plant, particularly dynamic interactions between the plants and the microbiome that surrounds them. The article provides a novel, real-time plant health optimization engine that has been designed to execute fully at the edge. Unlike those that are dependent on clouds, the root-zone microbial community will automatically be adapted to local and multiparametric data of biosensors in the proposed system. The system can detect both biotic and abiotic stress earlier on set and this has been possible by being able to gain insight into some plant physiology, alterations in soil chemical conditions and activity of the microbes. Once identified, it offers particular biological healing, in lure of the discharge of probiotic microorganisms, or pH; by a progressing situation of the plant. As it is a closed-loop feedback system, one can continuously learn and optimize decisions and therefore can respond to change in crop health condition or a change of the environment in real-time. It is important to note that the system will not need the common cloud infrastructure, thereby, making it to be exceptionally reliable and responsive, even in an area of the globe, where connection is limited. The performance of clustering-based intervention in terms of stress detection, time and energy efficiency, and yield are considerably improved compared to the performance of conventional systems through experimental evaluation in a wide variety of agricultural settings. The biological smart farming development will commence with the framework. It can support scalable, sustainable and autonomously operated precision agriculture ecosystem, which is founded on edge intelligence and microbiome-guided intervention.

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