17.16 Gops\W Sustainable FLS-Based Wireless Sensor Network For Surveillance System Using FPGA

Enhancing the sustainability of Wireless Sensor Networks (WSN) using different Artificial Intelligence (AI) approaches is one of the promising research topics nowadays, especially for battery-based applications such as border surveillance monitoring. In this paper, we proposed a Sustainable Systolic Wireless Sensor Network for Surveillance System (SS-WSN-SS) processing unit, which consists of two Fuzzy Logic System (FLS) processing cores. The first core is responsible for the event decision-making process based on the received data from a Lidar Sensor and an ultrasonic sensor. The second core is responsible for the detection and correction of any thermo-cognitive dysfunction that could reduce the reliability of the WSN system and could be assumed as a primitive electronics somatosensory cortex unit.The proposed SS-WSN-SS architecture could significantly decrease the power consumption at the processing unit level, sensory data acquisition level, and the wireless interfacing level as well. The proposed SS-WSN-SS processing unit architecture has been designed using VHDL, and the targeted FPGA chip was the Intel Cyclone V 5CGXFC9D6F27C7. Also, the proposed SS-WSN-SS processing unit obtained a Power efficiency of 17.16 GOPS\W at a maximum operating frequency of 263.5 MHz, while draining only 50.87 mW as a core dynamic thermal power dissipation loss and dissipates about 27.33 mW as an I/O thermal power dissipation loss.