Transforming Farming With Machine Intelligence: Plant Affliction Detection Plans, Request And Their Limitations - Abdulla, Faruk; Kumar, Dharmendra; Sinha, Tanya; Singh, Rathod Kuldeep; Dashora, Utkarsh; Gupta, Suraj; Kumar, Lalit; Bariya, Jaimin (Journal of Neonatal Surgery, 2025)
This study investigates the merger of structure brilliance (AI) with Computer network of Accouterments (IoT) sensor electronics for mechanical leaf malady diagnosis in crops. The research outlines organized steps for trade plant syndromes through AI, containing idea addition, pre-convert, break-up, feature voting, and categorization. It contends miscellaneous system understanding and deep knowledge models used for ache detection, and reviews existent studies applying these methods. The paper repeated designates a collection of plant disease finding datasets. Challenges guide ML and DL uses are deliberate, apart from future research convenience, in the way that smart drones for on-ground illness discovery and hearing. The research aims to help specialists investigate various arrangements for plant affliction finding and discover the disadvantages of current methods.