AI-DRIVEN PRECISION PEST MANAGEMENT: INTEGRATING MACHINE LEARNING AND IOT FOR REAL-TIME MONITORING AND CONTROL

Abstract

Activities done with the assistance of software and algorithms that do not involve humans are called artificial intelligence. The aim of artificial intelligence is to find solutions like a person through experience. Artificial intelligence is making machines learn patterns, analyze data and take decisions and predict outcomes in ways that humans are not able to. It is also capable of solving problems and predicting problems before they happen. In the education sector, this technology, a breakthrough, can be impactful.  Thus, the smart education system was developed. Artificial Intelligence analyzes & learns the images of pest species for machine learning from big data. Using a computer vision system, pest detection occurs from images. The machine learning system uses information derived from the camera, drone and smartphone to locate the pests on a real-time basis. Further, it does so without constant human intervention. The visual pattern recognition analytical tool detects damages caused to crop by insect pest. There are intelligent sensors that recognize pests using the seasonal behavioral patterns of pests and weather conditions. Sensors like temperature, humidity and soil moisture help in monitoring of changing condition. All these data help ascertain the scenario that causes pest development. AI tools can help classify and assess fruits and vegetables. The software determines the quality of produce by computing its shape, weight and colour. This helps in classifying the product under various grades as per specified quality parameters. To sum up, integrating artificial intelligence in pest monitoring can help recognize damage done to crops, thus reducing financial losses.