Real Time Crop Harvest Time Prediction Model Using Raspberry Pi and Image Processing

Agriculture is a vital sector for ensuring global food security and promoting sustainable development in every country. Additionally, accurate prediction of crop yield and best harvest time is vital as it will help the farmers to maximize their profit with right utilization of the available resources. The proposed system enables prediction of crop harvest time using Raspberry Pi and image processing technique. The Raspberry Pi, which has a camera module installed, takes pictures of the crops over time. Image analysis techniques are applied to assess the visual indicators of crop maturity, such as color, size, and texture. This technology forecasts the best time to harvest by comparing these visual cues with past data. This approach eliminates the need for manual inspection and enables timely decision-making. The system incorporates a user-friendly interface accessible through a web or mobile application, presenting real-time and predicted harvest data. Notifications alert users to optimal harvest conditions. Continuous improvement is achieved through periodic updates and refinement of the image analysis algorithms, ensuring accurate predictions and adaptability to different crop types. This technique offers a practical and efficient solution for determining the ideal harvest time, facilitating resource optimization, and maximizing crop yields.