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A Technical Survey on Deep Learning and AI Solutions for Plant Quality and Health Indicators Monitoring in Agriculture

The crop production and quality face many challenges due to the loss caused by plant diseases and destruction due to pests. The traditional method of manual monitoring is not an early indicator when the span of the agricultural land is vast. Image processing is more accurate now with deep learning and computer vision techniques. The computer vision-based image classification can help identify diseases in plants at early stages from multi-angle images of the plant leaves and fruits. Such images can be auto captured by autonomous drones. The advantage of using drones as an edge device for image acquisition, filtering, and basic image preprocessing with further layers of Artificial Intelligence (AI) and deep learning to identify diseases in plants would solve the challenges faced by the human methods to a great extent. This paper surveys the state-of-the-art works done for the early detection of plant diseases using computer vision and deep learning techniques.