gCrop: Internet-of-Leaf-Things (IoLT) for Monitoring of the Growth of Crops in Smart Agriculture

Proper growth of a plant is an important parameter for plant status, crop yield and its quality. Traditional methods of analysing the ideal growth and development of crop often are estimation and the farmer's intuition. This paper presents a smart solution, gCrop to monitor the growth and development of leafy crops and to update the status in real-lime utilizing the IoT, image processing and machine learning technologies. Leaves are readily available and disposable component which could significantly help in analysing the health, environment and maturity of the crops. The gCrop system consists of a smart camera system which would identify the leaf as an object, calculate its dimensions and statistically analyse the measurements correlating with the species' age and maturity and predict the same as the 'ideal conditions'. A computer vision algorithm runs on the backbone of the Internet of Leaf Things (IoLT) based gCrop system to calculate the growth patterns of the leaves in real-time. The model shows a great potential with an accuracy of around 98% to predict the growth of the leaves. Thus, it is promisingly expected that this system will effectively contribute in strengthening the current farming practices by ensuring the quality of the crops and improving the production yield.