short-paper

Want to Reduce Energy Consumption, Which Floor Should I Prefer?

Authors:

Priyanka Mary Mammen,

Surabhi Mehrotra,

Krithi RamamrithamAuthors Info & Claims

e-Energy '20: Proceedings of the Eleventh ACM International Conference on Future Energy Systems

Pages 534 - 538

https://doi.org/10.1145/3396851.3402648

Published: 18 June 2020 Publication History

Abstract

With a rampant increase in the urban population, especially in megacities, the number of high rise buildings is increasing rapidly. Both high rise buildings and lifestyle changes have resulted in high energy consumption. Heating, Ventilation, and Air Conditioning (HVAC) contribute the most to energy consumption in high-rise buildings. As thermal comfort is the major driving factor for the functioning of HVAC systems in a space, it is essential to understand how indoor environmental conditions vary across buildings' dimensions. Traditional approaches rely on simulations to understand the spatial and temporal variations of indoor conditions. Visualization offers opportunities to find solutions for complex thermal variations in buildings because of variation in environmental conditions owing to orientation, height, etc.

In this paper, we adopt a data-driven approach that considers the difference in indoor temperature depending on the floor level in a building. Temperature sensors kept on different floors in a building lead to real-time observations. The visualization from Open source Visualization Platform' (Grafana) revealed interesting variations in temperature at different floors of a high-rise building, based on which recommendations could be made to reduce energy consumption.

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Cited By

Ade RRehm MVishnupriya V(2023)A wintertime thermal analysis of New Zealand Homestar certified apartments for older peopleBuilding Research & Information10.1080/09613218.2023.225643452:6(680-692)Online publication date: 14-Sep-2023
https://doi.org/10.1080/09613218.2023.2256434
Wu JNiu ZLi XHuang LNielsen PLiu X(2023)Understanding multi-scale spatiotemporal energy consumption data: A visual analysis approachEnergy10.1016/j.energy.2022.125939263(125939)Online publication date: Jan-2023
https://doi.org/10.1016/j.energy.2022.125939
Sathish Kumar LRamanan MAlzubi JJayarajan PThenmozhi S(2021)Smart Metering Using IoT and ICT for Sustainable Seller Consumer in Smart CityChallenges and Solutions for Sustainable Smart City Development10.1007/978-3-030-70183-3_4(75-89)Online publication date: 23-May-2021
https://doi.org/10.1007/978-3-030-70183-3_4

Index Terms

Want to Reduce Energy Consumption, Which Floor Should I Prefer?
1. Computer systems organization
  1. Embedded and cyber-physical systems
    1. Embedded systems
      1. Embedded software

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e-Energy '20: Proceedings of the Eleventh ACM International Conference on Future Energy Systems

June 2020

601 pages

ISBN:9781450380096

DOI:10.1145/3396851

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGEnergy: ACM Special Interest Group on Energy Systems and Informatics

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Association for Computing Machinery

New York, NY, United States

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Published: 18 June 2020

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e-Energy '20

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SIGEnergy

e-Energy '20: The Eleventh ACM International Conference on Future Energy Systems

June 22 - 26, 2020

Virtual Event, Australia

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e-Energy '20 Paper Acceptance Rate 77 of 173 submissions, 45%;

Overall Acceptance Rate 160 of 446 submissions, 36%

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Cited By

Ade RRehm MVishnupriya V(2023)A wintertime thermal analysis of New Zealand Homestar certified apartments for older peopleBuilding Research & Information10.1080/09613218.2023.225643452:6(680-692)Online publication date: 14-Sep-2023
https://doi.org/10.1080/09613218.2023.2256434
Wu JNiu ZLi XHuang LNielsen PLiu X(2023)Understanding multi-scale spatiotemporal energy consumption data: A visual analysis approachEnergy10.1016/j.energy.2022.125939263(125939)Online publication date: Jan-2023
https://doi.org/10.1016/j.energy.2022.125939
Sathish Kumar LRamanan MAlzubi JJayarajan PThenmozhi S(2021)Smart Metering Using IoT and ICT for Sustainable Seller Consumer in Smart CityChallenges and Solutions for Sustainable Smart City Development10.1007/978-3-030-70183-3_4(75-89)Online publication date: 23-May-2021
https://doi.org/10.1007/978-3-030-70183-3_4

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