UrbanAgro : Application to Support Sri Lankan Urban Farmers to Detect and Control Common Diseases in Tomato Plants

Abstract

Abstract Plant diseases cause many significant damages and losses in crops around the world. Some appropriate measures should be introduced on identification of plant diseases to prevent damages and minimize losses. With Covid-19 lockdowns many Urban dwellers are encouraged to grow their own foods. As most urban farmers do not tend to use pesticides in their farms there is a high chance for the crops to get caught of various diseases. Comparatively, identifying the plant diseases visually is expensive, difficult and inefficient. And also getting expertise knowledge is very expensive and practically impossible to reach them whenever they need. As such this might be a difficult task for urban farmers or newcomers to this field to decide which disease can be attached to the crops. Early detection of diseases helps in increasing the productivity of crops as well as in minimizing expenses. Technical approaches using machine learning and computer vision are actively researched to achieve intelligence farming by early detection on plant diseases. The accuracy of object detection and recognition systems has been drastically improved by the recent development in Deep Neural Networks. The system proposed presents a practical, applicable solution for the identification of the type and location of 5 different types of diseased and healthy leaves of tomato plant, which is a significant difference from the conventional methods for plant disease classification. In this context we have used YOLOv3 model which is a method based on transfer learning to diagnose tomato plant diseases using images taken in-place by camera devices on smartphones instead of using the procedure to collect, test and analyze physical samples (leaves, plants) in the laboratory. The trained model achieved an average accuracy of 92 percent, which is exceptional in comparison to previous studies in this context. The target group of users are urban farmers who request a quick diagnosis on common tomato leaf diseases at any time of the day as they lack knowledge on diseases that are attached with plants.