ANALYSIS OF PLANTS’ GROWTH USING COMPUTER VISION METHODS

Abstract

The study describes the development of a service for monitoring plants’ growth in an indoor greenhouse using computer vision models, visual data collection with the esp32-cam card, the OV5640 camera, and the YOLO v4 detection model for extracting individual plants from the images. The plants tracking was performed by the DeepSORT library. The study determined the age of plants according to their type in order to identify their growth rate and notify the user when the parameters achieved. The computer vision methods are implemented through the TensorFlow 2 framework, with 99 % of classification accuracy, and Random Forest coefficient of determination of 0.94 for the regression of a plant’s age.