OBSERVE: Occupancy-based system for efficient reduction of HVAC energy

Heating, cooling and ventilation accounts for 35% energy usage in the United States. Currently, most modern buildings still condition rooms assuming maximum occupancy rather than actual usage. As a result, rooms are often over-conditioned needlessly. Thus, in order to achieve efficient conditioning,...

Full description

Saved in:
Bibliographic Details
Published in:2011 10th International Conference on Information Processing in Sensor Networks pp. 258 - 269
Main Authors: Erickson, V L, Carreira-Perpinan, M A, Cerpa, A E
Format: Conference Proceeding
Language:English
Published: IEEE 01.04.2011
Subjects:
Buildings
Data models
Energy savings
Hidden Markov models
HVAC
Load modeling
Markov processes
Occupancy
Predictive models
Ventilation
ISBN:9781612848549, 1612848540
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract Heating, cooling and ventilation accounts for 35% energy usage in the United States. Currently, most modern buildings still condition rooms assuming maximum occupancy rather than actual usage. As a result, rooms are often over-conditioned needlessly. Thus, in order to achieve efficient conditioning, we require knowledge of occupancy. This paper shows how real time occupancy data from a wireless sensor network can be used to create occupancy models which in turn can be integrated into building conditioning system for usage based demand control conditioning strategies. Using strategies based on sensor network occupancy model predictions, we show that it is possible to achieve 42% annual energy savings while still maintaining American Society of Heating, Refrigerating and Air-Conditioning (ASHRAE) comfort standards.
AbstractList Heating, cooling and ventilation accounts for 35% energy usage in the United States. Currently, most modern buildings still condition rooms assuming maximum occupancy rather than actual usage. As a result, rooms are often over-conditioned needlessly. Thus, in order to achieve efficient conditioning, we require knowledge of occupancy. This paper shows how real time occupancy data from a wireless sensor network can be used to create occupancy models which in turn can be integrated into building conditioning system for usage based demand control conditioning strategies. Using strategies based on sensor network occupancy model predictions, we show that it is possible to achieve 42% annual energy savings while still maintaining American Society of Heating, Refrigerating and Air-Conditioning (ASHRAE) comfort standards.
Author Cerpa, A E
Erickson, V L
Carreira-Perpinan, M A
Author_xml – sequence: 1
  givenname: V L
  surname: Erickson
  fullname: Erickson, V L
  email: verickson@ucmerced.edu
– sequence: 2
  givenname: M A
  surname: Carreira-Perpinan
  fullname: Carreira-Perpinan, M A
  email: mcarreira-perpinan@ucmerced.edu
– sequence: 3
  givenname: A E
  surname: Cerpa
  fullname: Cerpa, A E
  email: acerpa@ucmerced.edu
BookMark eNotjNFKwzAUQCMq6Ga_wJf8QCHJTW4a32bZnDAo6NjrSNNbibh0NN1D_96BnpfzcjgLdpeGRDdsIbURIIxU8pYVzlYSpap0ZbR7YEXO3-IKolMGHtmmef1cfxzWL7wJ4XL2Kcxl6zN1PM95ohPvh5FT38cQKU18pO4SpjgkPvR8e1jVnBKNX_MTu-_9T6bi30u236z39bbcNW_v9WpXRiem0mhVkRYaO-gt2NYYsKjRo9fKoWkB0FegO2WlNEo5wmvXAgYlROsxwJI9_20jER3PYzz5cT4aa53QAL9wjkX_
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume
IEEE Xplore All Conference Proceedings
IEEE Electronic Library (IEL)
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
EISBN 1450305121
9781450305129
EndPage 269
ExternalDocumentID 5779043
Genre orig-research
GroupedDBID 6IE
6IF
6IK
6IL
6IN
AAJGR
AAWTH
ADFMO
ALMA_UNASSIGNED_HOLDINGS
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CBEJK
IEGSK
IERZE
OCL
RIE
RIL
ID FETCH-LOGICAL-i90t-5428e4046d3f737b5537646a6a42965b336a834d27115229e63f7b36c200ba6c3
IEDL.DBID RIE
ISBN 9781612848549
1612848540
IngestDate Wed Aug 27 02:53:16 EDT 2025
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i90t-5428e4046d3f737b5537646a6a42965b336a834d27115229e63f7b36c200ba6c3
PageCount 12
ParticipantIDs ieee_primary_5779043
PublicationCentury 2000
PublicationDate 2011-April
PublicationDateYYYYMMDD 2011-04-01
PublicationDate_xml – month: 04
  year: 2011
  text: 2011-April
PublicationDecade 2010
PublicationTitle 2011 10th International Conference on Information Processing in Sensor Networks
PublicationTitleAbbrev IPSN
PublicationYear 2011
Publisher IEEE
Publisher_xml – name: IEEE
SSID ssj0000669253
Score 1.9338074
Snippet Heating, cooling and ventilation accounts for 35% energy usage in the United States. Currently, most modern buildings still condition rooms assuming maximum...
SourceID ieee
SourceType Publisher
StartPage 258
SubjectTerms Buildings
Data models
Energy savings
Hidden Markov models
HVAC
Load modeling
Markov processes
Occupancy
Predictive models
Ventilation
Title OBSERVE: Occupancy-based system for efficient reduction of HVAC energy
URI https://ieeexplore.ieee.org/document/5779043
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV09T8MwED21FQMToBbxLQ-MGIX4mw2qVp1KBVXVrYodW-qSopLy-zk7oQiJhc2xoli25XvvLr53ALf2QctSh5IGqXLKtdPUWjxXzKEllIpzm7lUbEJNp3q5NLMO3O1zYbz36fKZv4_N9C-_3LhdDJWh865MxlkXukqpJldrH09B6DS5iGUbkMOgzdVIRVpJp-9n86uCSgKQ8dH_hj6GwU8mHpntMeYEOr7qw_jl-W30uhg9kkYjGO0jjWhUkkaXmSARJT5pQ-BHyTaqs8b1J5tAJounIfEp4W8A8_FoPpzQth4CXZuspgI9Bc_Rny1ZUExZEZVYuCxkgZgihWVMFprxMlfI8vLceInvWSYdHgRbSMdOoVdtKn8GxAVpghBFLpWLkvRa4SYxpUMmioCc7hz6cQlW743ixaqd_cXf3Zdw2ERa432WK-jV252_hgP3Wa8_tjdpm74AQA2QOA
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1NTwIxEJ0gmuhJDRi_7cGjNUu_15sSCEZEooRwI9tum3BhDYK_3-kuYky8eNtuNt3sTjrvzbTzBuDatozKTchpUJpRYZyh1uK64g49odJC2MSVzSb0YGAmk3RYg5tNLYz3vjx85m_jZbmXnxduFVNlGLzrNBF8C7alEKxVVWttMioInimTsXEDshj0ugbJyFrU6Xuc_uqhUkJId_9_Lz-A5k8tHhluUOYQan7egO7Lw1vnddy5I5VKMHpIGvEoJ5UyM0EqSnypDoGTkkXUZ40WIEUgvfF9m_iy5K8Jo25n1O7RdUcEOkuTJZUYK3iBEW3Og-bayqjFIlSmMkQVJS3nKjNc5Ewjz2Ms9Qqfs1w5XAo2U44fQX1ezP0xEBdUGqTMmNIuitIbjWbi2oREZgFZ3Qk04i-YvleaF9P115_-ffsKdnuj5_60_zh4OoO9Ku8aT7ecQ325WPkL2HGfy9nH4rI02Rf28ZN_
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2011+10th+International+Conference+on+Information+Processing+in+Sensor+Networks&rft.atitle=OBSERVE%3A+Occupancy-based+system+for+efficient+reduction+of+HVAC+energy&rft.au=Erickson%2C+V+L&rft.au=Carreira-Perpinan%2C+M+A&rft.au=Cerpa%2C+A+E&rft.date=2011-04-01&rft.pub=IEEE&rft.isbn=9781612848549&rft.spage=258&rft.epage=269&rft.externalDocID=5779043
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=9781612848549/lc.gif&client=summon&freeimage=true
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=9781612848549/mc.gif&client=summon&freeimage=true
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=9781612848549/sc.gif&client=summon&freeimage=true