PIR Sensor Based Motion Detection using Fuzzy Controller
Sreejith Damodaran1, Bhavani Sridharan2

1Mr. Sreejith Damodaran, Research Scholar, Department of Electronics and Communication Engineering, Karpagam Academy of Higher Education, Coimbatore (Tamil Nadu), India.
2Dr. Bhavani Sridharan, Professor, Department of Electronics and Communication Engineering, Karpagam Academy of Higher Education, Coimbatore (Tamil Nadu), India.
Manuscript received on 25 May 2019 | Revised Manuscript received on 12 June 2019 | Manuscript Published on 26 June 2019 | PP: 232-235 | Volume-8 Issue-1S5 June 2019 | Retrieval Number: A00400681S519/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The prime task of the Smart grids is to manage the power demand and the power supplied during the peak conditions at least possible cost. When the adequate scheduling of the consumer power requirements were done for the residential users, Electricity Costs (EC ) can be minimised to an extent. For an feasible and reliable energy management Automatically restrained Heat ventilation and Air conditioning (HVAC) in the residential zone is used. These systems play an crucial role in balancing power requirements and supply during the peak durations. The automatic control of the HVAC systems are based on the customized programmable and communicable thermostats. These systems Assists the consumers in scheduling and prioritising their demand and usage. Specifications like Demand response programs (DR), Time of use (TOU), Real time pricing (RTP) motivates the consumers to minimize their power consumption during the peak hours of load. With the fluctuating pricing scheme of electricity it is impossible for the consumers to schedule their priorities and preferences of power usage. Hence this analysis is framed in a way to assist them with the automated customized thermostat along with motion sensor to regulate the demand and supply of the power during peak periods in cost effective manner. This automation is made using fuzzy logic, WSNs, and smart grids. The experimental procedure was simulated and the results were demonstrated in the MATLAB simulation software. The results showed the development in energy conservation without endangering the thermal amenity of the user.
Keywords: Demand Response (DR), Electricity Cost (EC), HVAC, RTP, TOU, CCT.
Scope of the Article: Fuzzy Logics