MONITORING AND LEARNING OF PLANT GROWTH AND HEALTH FOR EFFECTIVE SUPPLY OF WATER, NUTRIENTS AND PESTICIDES IN LARGE SCALE PLANTATIONS

Abstract

Agriculture sector is a major economic force in Sri Lanka, making a significant contribution to the national economy. However, it is observed that land and human resources available in Sri Lanka for agriculture becomes scarce. On the other hand, the demand for high quality agricultural products is on the rise. Therefore, we need to embrace cost efficient and effective technologies that would facilitate the automation of large scale plantations to obtain an increased yield per given area. Providing water, nutrients, pesticides and other supplies is one of the most resource consuming tasks in a large scale plantation. Existing solutions to achieve this objective are only capable of providing supplies from time-to-time without knowing the exact requirement of the plant. This may result in a shortage or excess amount of supplies that will adversely affect the health of plants. In response, the proposed method is capable of identifying the exact status and health of plants to customize the supplies accordingly and ensure the healthy growth of plants. When it comes to this project, almost the total management of the plant is done by the system from the beginning to end. Initially the system decides the age of the plant and learn about the required conditions. An array of sensors and cameras connected through Narrowband Internet of Things (NB-IoT) will collect data that will be processed using machine learning techniques. Initially image processing is supposed to do the object detection and to perform the leaf counting task it is intended to consider the capability of deep convolution neural network. Automatic detection of these type of issues in plants is supposed to achieve by a software solution for automatic detection and classification of plant leaf diseases. This would facilitate the understanding of plant growth and any development of pests or weeds. Water, nutrients and pesticide will be supplied according to the exact requirement of plants. In addition, the proposed system will alert if immediate attention is required in case of an emergency and also report on the growth of plants and usage of each type of supplies to facilitate a thorough insight of the plantation. Because, when it comes to a traditional farm, farmers have to pay their attention to each and every plant separately to identify factors like diseases, insect attacks or any other infections. Therefore, farmer’s special attention have to be taken in such kind of situations. It is envisaged that the proposed system will play a pivotal role is automating large scale plantations that would in return benefit the agriculture sector In Sri Lanka.