Enhancing the Farmland Rover for Muddy Terrain with IoT

This paper presents the Enhancing the Farmland Rover for Muddy Terrain with Iot to improve the precision agriculture by automating field operations, resource efficiency, and supporting real-time data collection. This rover features a GPS-based navigation system with IMU and LiDAR for accurate, autonomous path-following and obstacle avoidance in diverse terrains. This design is proposed in use solar energy and rechargeable batteries and it supports sustainable, extended operation with reduced environmental impact. This rover design has proficient attachment for advanced sensors for soil health to monitor the moisture, pH, nutrient levels and crop condition monitoring (multispectral cameras for pest and stress detection). It integrated AI and machine learning. It can identify crops health patterns and predicts potential issues, enabling targeted interventions such as precision watering and nutrient delivery. Data gathered is accessible in real-time via a mobile app or web platform, aiding informed decision-making for optimized field management. Modular and scalable, the rover is adaptable to different crops, field sizes, and climate conditions, making it suitable for various farming practices Designed using Fusion 360's generative design tool. Prototype testing confirms its precision, reliability, and contribution to resource-efficient agriculture. This project highlights the potential of autonomous rovers to transform modern farming by minimizing labour, reducing resource use, and enhancing productivity through data-driven agriculture. Early Disease Detection Process and disease affected cotton plant leaves are detected using Ai and machine learning are presented. The model has trained 90% data from the entire dataset for training the model and remaining 10% data for testing the model for Accuracy graph & Loss graph analysed using the alexnet software. The accuracy graph shows proposed CNN- architecture performs much better than the AlexNet and VGG-16. The opportunities and Challenges for Implementing Irrigation Improvements Opportunities are discussed in the paper.