Controlled Environment for Spinach Cultured Plant with Health Analysis using Machine Learning

The combination of mobile application and machine learning with environmental sensing and image processing device in monitoring the health and growth of the plant in real-time. The goal of the study is to develop a controlled environment for spinach by monitoring its health condition using image processing and supervised machine learning. The device collects real-time data for humidity, temperature, and soil conditions using different sensors. Diagnosis of spinach health status is done by capturing the images of spinach using image processing techniques. Two classifiers were used in detecting spinach health conditions, Green for healthy spinach or no damages on leaves and Green, Yellow, Brown for unhealthy or with holes, damages; this classifier is also called datasets. Spinach health status is monitored using a mobile application called Spinach Monitoring Application (SPIMON) and all collected data are stored in the cloud. The result spinach health status showed that its best to culture spinach in a controlled environment.