Local Temperature Control within a Confined Space by Using a Neural Network Model.

Abstract

Precision agriculture is now practiced in plant factories. In the case of precision agriculture in Japan, the Microprecision Agriculture program is defined as an ultimate optimized plant production system utilized in order for plant factories to have environmental safeguards that are compatible with yield. Microprecision techniques to manage temperatures or other parameters in the plant factory can provide objectively controlled environments for specific purposes. In fact, in a plant factory, some environmental non-uniformity always exists within the interior. Most of the environmental factors in a fully controlled plant factory are observable and controllable. The conventional strategy for the environmental control of the interior of plant factories has been to make atmospheric factors, such as temperature and humidity, as uniform as possible throughout the interior space. This paper discusses an experiment to control local temperatures, as an example of how microprecision technology can be implemented in plant factories. The results of the experiment using a neural network model show that it is possible to control the temperature distributions by manipulating the wind directions and the temperatures of the airflow. This technique can also be implemented in people's living and working environments.