ANN-based occupancy detection for energy efficient HVAC control: a case study.
Author(s) : ADHIKARY P., BANDYOPADHYAY S., MAZUMDAR A.
Summary
Current building climate control systems often rely on pre-determined maximum occupancy numbers coupled with temperature sensor data to regulate heating, ventilation, and air conditioning (HVAC). However, rooms and zones in a building are not always fully occupied. Real-time occupancy information can potentially be used to reduce energy consumption. The paper proposes an ANN-based occupancy detection solution to address the need for real-time in-building occupancy information. The proposed solution can track real-time location of tagged occupants. Based on the findings, detailed and operable strategies for optimizing HVAC related building energy consumption by using occupancy information are proposed. Good agreement was found between the simulated results and obtained project data.
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Details
- Original title: ANN-based occupancy detection for energy efficient HVAC control: a case study.
- Record ID : 30024771
- Languages: English
- Source: Proceedings of the International Conference on Emerging Technologies for Sustainable and Intelligent HVAC&R Systems, Kolkata, July 27-28 2018.
- Publication date: 2018/07/27
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Indexing
- Themes: Comfort air conditioning
- Keywords: Energy consumption; Building; Artificial neural network; Simulation; Optimization; Modelling; Air conditioning; Heating
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