In recent years, work management has been conducted by more than a few dozen workers at sites that are becoming increasingly large-scale, and the ratio of personnel costs to production costs is large, consequently, management improvement through the enhancement of work efficiency is required. In order to improve the efficiency of cultivation and labor management in the protected horticulture, the Horticultural Production System Group will construct an open platform for the protected horticulture which will be the basic technology of artificial intelligence technology utilization. In the construction, development and implementation of a framework that can link, output, and utilize various data acquired at production sites will be promoted with a view to cooperate with the agricultural data collaboration platform (WAGRI). In connection with this, we are developing a growth information diagnostic system that automatically measures fruit and vegetables capable of photographing and harvesting crop objects in the facility. In this system, the position and ripening degree of fruits are specified by utilizing deep learning, and appropriate labor management is realized by anticipating harvesting data (number of fruits, weights, working hours) for every day. Furthermore, aiming at perfect unmanned growth management utilizing this system, we will promote a construction of basic forms of modular type robot system applicable to multiple work processes including harvesting
