GREEN-SENSE Short Description

Food production with respect to resource efficiency, enhanced productivity and quality is a world priority. Nowadays, one of the key factors in crop growing in protected spaces (greenhouses, solar houses, urban farms) is „sensing” the environment in order to be able to provide the best conditions for plants to develop and produce food. Usually, in conventional farming, the feedback is provided by the farmer which manually sample and analyze different measures of the growing conditions: soil humidity, air humidity, CO2 concentration, light, temperature, etc. As experience proved, these conditions differ based on the location they were measured, even inside the same greenhouse. Within this project, we will develop a wireless sensor network acting as a distributed measurement system composed of a grid of wireless nodes with multiple sensors (humidity, CO2, temperature, light) which will cover all the greenhouse area and will transmit the data to a central control station in a deterministic mean. Then, based on machine learning control algorithms, it will be commanded a custom-made control system in order to optimize the microclimate within the greenhouse (shading, CO2, substrate humidity zonal control, soil heat). The base of the system will consist of prior obtained results at TRL3, a wireless sensor node called DASMote (node for Data Acquisition Systems). Given the node, we will further develop custom interfaces for the interest sensors and control system, creating a network designed as a modular kit which could be adapted to any greenhouse with great potential for commercialization. The system will contain a web platform where the farmer could see in real time the evolution of the monitored environmental parameters.