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10.1145/2070942.2070980acmconferencesArticle/Chapter ViewAbstractPublication PagessensysConference Proceedingsconference-collections
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Poster: INPRESS: indoor climate prediction and evaluation system for energy efficiency using sensor networks

Published: 01 November 2011 Publication History

Abstract

Modern buildings include an indoor climate control system, installed and operated to maintain a comfortable environment for the building occupants. However, these climate control systems consume a significant amount of energy due to an inefficient control algorithm. Improving energy efficiency is critical to reducing energy consumption, costs, and the emissions of greenhouse gases. In this paper, we present INPRESS: Indoor Climate Prediction and Evaluation System for Energy Efficiency using Sensor Networks. INPRESS uses meteorological weather data and the indoor climate conditions collected by sensor nodes to evaluate and improve the energy efficient climate control of an indoor space.

References

[1]
ANSI/ASHRAE Standard 55--1992 Thermal environmental conditions for human occupancy, 1992.
[2]
J. Lena, R. Swain, and N. K. Kamila. Mining Wireless Sensor Network Data: an adaptive approach based on artificial neural networks algorithm. Interscience Open Access Journals, 2010.
[3]
W. Watts, M. Koplow, A. Redfern, and P. Wright. Application of Multizone HVAC Control Using Wireless Sensor Networks and Actuating Vent Registers, 2007.

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Published In

cover image ACM Conferences
SenSys '11: Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems
November 2011
452 pages
ISBN:9781450307185
DOI:10.1145/2070942

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 November 2011

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  1. energy efficiency
  2. indoor climate
  3. sensor network

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Overall Acceptance Rate 174 of 867 submissions, 20%

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