Green Environment is a key for Healthy Environment, to keep environment green every country doing a lot to preserve their Healthy growth in the agriculture. The detection of diseases in plants is very hard job and will have a significant impact of environmental development growth as well as production.The problem of the study is to diagnosis the plant’s micro diseases to prevent the big loss of plants’ production as well as food production, we used the IoT based technology with machine learning scheme This study aimed to detect unhealthy plants through infected leaves using CNN enabled method helped to mitigate the worst situation for the less developed countries. This research study had modelled the IoT network-based Plant Health Detection System, in which we explored the different invisible patterns of plant leaves which can’t be detected easily in the plants. In this research article, we have investigated and developed a IoT-network system with a CNN model successfully that can detect the invisible micro things in the plants by getting 95 percent of accuracy in the study. In this research study, we used IoT-Network system by applying the CNN technique to train the model for detection of diseases in leaves. This model scheme provided the best performance detection with an accuracy of 95 percent, demonstrating the performance of the proposed CNN scheme after implementation.