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@article{190024,
        author = {Amos Akash P and Abhinav P and Abel Baiju and Akhil P Pradeep and Dr. Mary P Varghese and Ms.Anooja VS},
        title = {PLANT HEALTH MONITORING AI ROBOT},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {2704-2706},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=190024},
        abstract = {The agricultural sector is moving towards automation and intelligent systems to enhance crop productivity, particularly for plant health monitoring. This project presents the design and development of an Eggplant Health Monitoring Robot, an autonomous system that uses advanced image processing and Internet of Things (IoT) technologies. The robot is based on a line-following navigation mechanism using Infrared (IR) sensors and is controlled by Arduino UNO and NodeMCU (ESP8266) microcontrollers. Image acquisition and analysis are performed using Convolutional Neural Networks (CNN), implemented via the TensorFlow framework, to classify plant leaves as healthy or diseased. The system integrates with the Blynk application to provide real-time monitoring, control, and alerts to the user. Additionally, an automatic spraying unit is incorporated to dispense fertilizer or pesticide upon disease detection. The pro-posed system effectively reduces human intervention, enhances precision in plant health assessment, and contributes to the development of smart agricultural practices.},
        keywords = {Plant Health Monitoring, AI Robot, Convolutional Neural Networks (CNN), Internet of Things (IoT), Blynk, Precision Agriculture, Eggplant Disease Detection.},
        month = {January},
        }