Skip to content

amberw68/Smart-Building

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

23 Commits
 
 
 
 
 
 

Repository files navigation

Improving Building Energy Efficiency by IoT and Mobile Computing (Tentative)

Abstract

Building environment management is always on the front line of the energy economic issue since its heating, cooling, lighting, ventilation, air conditioning system takes great part on energy consumption. According to the U.S. Energy Information Administration (EIA) estimates, residential and commercial buildings consumed about 40% of total U.S. energy consumption, which equals 39 quadrillion British thermal units(BTU). [1] Environment science researches has repeatedly proved that high-efficiency building infrastructure developed by appropriate artificial intelligence techniques provides great opportunities on decreasing energy consumption and greenhouse gas emission [2]. Internet of Things, as a suite of technologies and applications which equip devices (sensors) and locations generating necessary information, is advancing building energy management with balance between occupants’ satisfaction and energy saving. [3] We implemented an IOT system with non-intrusive multi-modal sensors to collecting real-time building environmental data, such as temperature, humidity, ambient light, CO2, acoustic frequency, and occupancy status. Our experiment testbed is located on our campus and the types of space various from small close enclosure space (office, small lab, small classroom) to large open space (library, lobby hall). Based on the data we collected from IOT network, we can accurately estimate occupancy size and situation and predict future occupancy by building agent model of the occupants. The result of predictions will be important reference in the application to control HVAC system and artificial lighting adjustments and eventually increase building efficient and environment performance by adapting to the forecast of occupancy changes in each specific location.

Keywords

IoT(Internet of Things), Smart Building, Building Efficiency, Environmental Sensing, Occupancy Forecast, Machine Learning

Introduction

Related Work

System Methodology

  1. IoT system
  2. data processing

Conclusion

NOTE

[1] “How much energy is consumed in residential and commercial buildings in the United States?” (Web Log Posted on EIA) April.6.2016 From http://www.eia.gov/tools/faqs/faq.cfm?id=86&t=1 [2] “Green Building 101: Why is energy efficiency important?” (Web Log Posted on LEED) May.14.2014 From http://www.usgbc.org/articles/green-building-101-why-energy-efficiency-important [3] Surabhi Kejriwal, Saurabh Mahajan “Smart buildings: How IoT technology aims to add value for real estate companies” Deloitte University Press 2016

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages