Solar-Powered PredictBot: AI-Driven Remote Sensing and IoT Integration for Real-Time Pest and Disease Detection in Agriculture

This paper presents the development of "Solar-Powered PredictBot: AI-Driven Remote Sensing and IoT Integration for Real-Time Pest and Disease Detection in Agriculture", designed to enhance agricultural productivity and sustainability. The proposed system utilizes artificial intelligence (AI) and Internet of Things (IoT) technologies to continuously monitor crop health, environmental parameters, and weather conditions in real time. Powered by solar energy, the robot operates autonomously, making it suitable for deployment in remote and off-grid agricultural areas. By analyzing the collected data, the system can detect early signs of pest infestations and disease outbreaks, as well as predict their occurrence based on changing environmental and weather patterns. IoT connectivity enables seamless data transmission to farmers and centralized platforms, facilitating prompt responses and informed decision-making. The implementation of this solution has the potential to reduce dependence on chemical pesticides, optimize resource use, and promote sustainable farming practices, ultimately contributing to increased crop yields and improved food security particularly beneficial in regions like Oman or Middle East where agriculture faces challenges from extreme heat, drought, or deficiency.