IoT-Based Smart Farm Protection and AI Crop Disease Detection System

DOI

https://www.doi.org/10.59256/indjcst.20260503056

Published In

Volume 5, Issue 3 (2026)

Published Online

September-December 2026

Pages

476-480

Article Type

Original Article

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Crop damage caused by unwanted animals and the difficulty of identifying crop diseases at an early stage are two common problems faced by farmers. This paper proposes the IoT-Based Smart Farm Protection and AI Crop Disease Detection System, a low-cost smart agriculture system that addresses both problems through a single web platform. For farm protection, a copper wire arrangement installed around the farm boundary acts as the sensing element; when an animal touches it, an ESP32/Arduino-class microcontroller detects the contact and activates a buzzer, and the farmer can turn the buzzer OFF remotely through the website. For crop health monitoring, a camera captures an image of a crop leaf, and an AI/ML-based image classification model identifies the possible disease, which is displayed on the website. The proposed classifier is a lightweight convolutional neural network (MobileNetV2, transfer learning) to be trained on the public PlantVillage leaf image dataset. The web application provides homepage, admin and farmer modules, and a MySQL database stores user, farm and crop details, intrusion alerts, buzzer control records and disease detection results. The system is organized into six modules: homepage, admin login, farmer login, crop disease detection, farm protection and database design. This paper presents the proposed architecture, methodology and planned evaluation; the system is at the design stage, all modules are described as proposed, and no experimental results are claimed