Cloud Enabled Neural Network with Intelligent Sensor nodes for HVAC

Abstract

HVAC (Heating, Ventilation and Air Conditioning) is the technology of indoor and vehicular environmental comfort and to control these systems. The status of building energy consumption is increasingly prominent. Indoor air pollution is 10times danger than outdoor due to incorrect functionality of heating, ventilation, and air condition system. For indoor environment quality, a novel real-time method for HVAC system operation is developed. Internet of things is used to monitor the indoor air quality by using embedded electronics, software and sensors and connectivity. This project aims to integrate air condition, ventilation and protected system on a single embedded system that alerts early warning for the unpredictable dangers. The wireless sensor nodes have limited processing power and memory. In order to embed intelligence into sensor nodes, a hybrid algorithm is proposed containing RNN (Random Neural Network) and LNP (Linear Non-linear Poisson) cascade model.