Wireless sensor actor network based on fuzzy inference system for greenhouse climate control

The pervasive merit of wireless sensor networks has led to a swelling interest in rendering them to be smart and autonomous which have the potential to enable a large class of applications in multiple fields. A novel cognitive wireless sensor-actor network based Greenhouse climate control (CWSAN-GH) is presented in this research. Fusion of artificial intelligent with nowadays Wireless Sensor Actor Networks (WSAN) is a promising era of smart WSAN. Primarily two most important greenhouse climate parameters are considered which are the temperature and humidity during diurnal and nocturnal time. Actuator and sensor nodes has been managed by CWSAN-GH Coordinator node (MGHSN) which mimics the brain of the planter to provide reliable, power conserving, autonomous control system of a greenhouse. The conventional control methods are not efficient in terms of energy, labor interference, productivity and flexibility. In this study, the adoption of Artificial Intelligent (AI) approach to controlling tasks within Wireless Sensor-Actor Network (WSAN) is presented. Fuzzy inference system has been designed and fused within the coordinator node of WSAN, hardware and software of network nodes and sensors has been presented. Initial field test for the CWSAN based greenhouse are also presented. The combination of AI with actor WSN proves high efficiently, cost effective method, beside flexibility of tuning the whole system for other agricultural tasks.