Author：Taiwan Agricultural Research Institute,COA

In response to the future development of smart agriculture, a set of facility crop leaf area real-time monitoring systems are developed in this research. The systems can remotely measure the leaf area and send the data back to the cloud for big data analysis applications. Leaf area is one of the crop characteristics, the leaf area index can be utilized and extended to estimate the yield of facility crops and to provide suggestions for cultivation management. A relational model, which based on the leaf area (or converted into leaf area index) and environmental data, has been constructed currently, and it can be used to predict the yield volume within a few days after the harvest date.
The whole systems are composed of measuring equipment in the field, Web API (Web Application Programming Interface) architecture, back-end applications MVC, the remote storage servers, database, and some other components. The block area of the leaf is calculated by using SICK VSPM-6F2113 to fetch the image, and perform image blob analysis and feature extraction. The area data will be uploaded in Json format via the network to the Web API, and then transmitted to the back-end applications. MVC exchanges Json format data between client and server. All the numeric data is transmitted to the remote server and stored in MS SQL database. The original images are directly saved to the storage devices by using FTP.