Cloud Enabled Neural Network with Intelligent Sensor nodes for HVAC
Author(s) -
Ragipati Karthik,
K. Aravind Reddy,
Rajesh Kumar
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.b7890.129219
Subject(s) - hvac , indoor air quality , wireless sensor network , computer science , real time computing , ventilation (architecture) , cloud computing , air conditioning , artificial neural network , embedded system , automotive engineering , engineering , computer network , artificial intelligence , mechanical engineering , environmental engineering , operating system
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.
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