Fruit yield estimation and forecasting for precision agriculture

Precision agriculture is an ever-growing domain. Fruit yield estimation and forecasting is a necessary step towards precision agriculture. Reliable and accurate estimation of fruit yield in an orchard help the farmers to make suitable arrangements. Fruit yield estimation is performed on video footage in which fruits are detected and tracked in each frame of the input video. YOLO V5 (You Only Look Once Version 5) neural network are applied to detect fruits in an orchard. Bounding boxes are extracted from detection and Non-Maximum Suppression (NMS) is performed to avoid multiple detections. Then the results are input into the tracking pipeline. DeepSORT algorithm is used for tracking the fruits. By keeping track of the fruits throughout the video frames, it is ensured that we are estimating the total fruit count appropriately when they are detected. Future fruit yield prediction is also carried out using time series forecasting by ARIMA model. This work may greatly help the needy farmers in yield estimation and predicting the future yields for sustainable growth.