An Internet of Things Framework for Smart Energy in Buildings: Designs, Prototype, and Experiments
Open accessAbstract
Smart energy in buildings is an important research area of Internet of Things (IoT). As important parts of the smart grids, the energy efficiency of buildings is vital for the environment and global sustainability. Using a LEED-gold-certificated green office building, we built a unique IoT experimental testbed for our energy efficiency and building intelligence research. We first monitor and collect 1-year-long building energy usage data and then systematically evaluate and analyze them. The results show that due to the centralized and static building controls, the actual running of green buildings may not be energy efficient even though they may be “green” by design. Inspired by “energy proportional computing” in modern computers, we propose an IoT framework with smart location-based automated and networked energy control, which uses smartphone platform and cloud-computing technologies to enable multiscale energy proportionality including building-, user-, and organizational-level energy proportionality. We further build a proof-of-concept IoT network and control system prototype and carried out real-world experiments, which demonstrate the effectiveness of the proposed solution. We envision that the broad application of the proposed solution has not only led to significant economic benefits in term of energy saving, improving home/office network intelligence, but also bought in a huge social implication in terms of global sustainability.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The energy management and optimization systems in smart buildings can be regarded as the extension of smart grids AIoT.
“5) the energy management and optimization systems in smart buildings [255], [253] can be regarded as the extension of smart grids AIoT (Section IV-F).”
From Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things (2021) · cites this paper as [255]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Intelligent light control using sensor networks
Singhvi, V., Krause, A., Guestrin, C., et al. (2005) · International Conference on Embedded Networked Sensor Systems · doi:10.1145/1098918.1098942 · Cited by 247 · see citing works
Experiences with a high-fidelity wireless building energy auditing network
Jiang, X., Ly, M. V., Taneja, J., et al. (2009) · ACM Conference on Embedded Networked Sensor Systems (SenSys) · doi:10.1145/1644038.1644050 · Cited by 152 · see citing works
Wan, K. K. W., Li, D. H. W., & Lam, J. C. (2011) · Energy · doi:10.1016/j.energy.2011.01.033 · Cited by 113 · see citing works
Internet 3.0: Ten Problems with Current Internet Architecture and Solutions for the Next Generation
Jain, R. K. (2006) · doi:10.1109/milcom.2006.301995 · Cited by 108 · see citing works
Self-citationLeadership in Energy and Environmental Design (LEED)
Ford, C. (2016) · The Bloomsbury Encyclopedia of Design · doi:10.5040/9781472596161-bed-l023 · Cited by 80 · see citing works
Pan, J., Paul, S., Jain, R. K., et al. (2008) · IEEE Global Telecommunications Conference (GLOBECOM) · doi:10.1109/glocom.2008.ecp.436 · Cited by 79 · see citing works
Self-citationPan, J., Jain, R. K., Paul, S., et al. (2010) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2010.101012 · Cited by 65 · see citing works
Self-citationLocal weather correlations and bias in building parameter estimates from energy-signature models
Flouquet, F. (1992) · Energy and Buildings · doi:10.1016/0378-7788(92)90005-2 · Cited by 22 · see citing works
A framework for smart location-based automated energy controls in a green building testbed
Pan, J., Jain, R. K., Biswas, P., et al. (2012) · IEEE Energytech · doi:10.1109/energytech.2012.6304645 · Cited by 13 · see citing works
Self-citationPan, J., Jain, R. K., Biswas, P., et al. (2013) · IEEE Energytech · doi:10.1109/energytech.2013.6645358 · Cited by 7 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 2
- [6][6] R. Jain, 'The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling,' Wiley, 1991. -
- [10][10] S. Paul, R. Jain, J. Pan, M. Bowman, "A Vision of the Next Generation Internet: A Policy Oriented Perspective," British Computer Society (BCS) International Conference on Visions of Computer Science, Imperial College, London, September 22-24, 2008. -
Cited by
Sorted by citations
Machine learning for internet of things data analysis: a survey
Mahdavinejad, M. S., Rezvan, M., Barekatain, M., Adibi, P., Barnaghi, P., & Sheth, A. P. (2018) · Digital Communications and Networks · doi:10.1016/j.dcan.2017.10.002 · Cited by 921 · see citing works
Zhang, J., & Tao, D. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.3039359 · Cited by 774 · see citing works
Xie, J., Yu, F. R., Huang, T., Xie, R., Liu, J., Wang, C., & Liu, Y. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2018.2866942 · Cited by 700 · see citing works
O’Dwyer, E., Pan, I., Acha, S., & Shah, N. (2019) · Applied Energy · doi:10.1016/j.apenergy.2019.01.024 · Cited by 410 · see citing works
Reka, S. S., & Dragicevic, T. (2018) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2018.03.089 · Cited by 304 · see citing works
An energy-efficient architecture for the Internet of Things (IoT)
Kaur, N., & Sood, S. K. (2017) · IEEE Systems Journal · doi:10.1109/jsyst.2015.2469676 · Cited by 282 · see citing works
Saleem, M., Shakir, M., Usman, M., Bajwa, M., Shabbir, N., Shams Ghahfarokhi, P., & Daniel, K. (2023) · Energies · doi:10.3390/en16124835 · Cited by 197 · see citing works
A Survey on IoT-Enabled Smart Grids: Technologies, Architectures, Applications, and Challenges
Kirmani, S., Mazid, A., Khan, I. A., & Abid, M. (2022) · Sustainability · doi:10.3390/su15010717 · Cited by 94 · see citing works
- Authors
- Pan, J., Jain, R., Paul, S., Vu, T., Saifullah, A., & Sha, M.
- Affiliations
- University of Missouri–St. Louis (US)
- Washington University in St. Louis (US)
- Cisco Systems (United States) (US)
- University of Colorado Denver (US)
- Missouri University of Science and Technology (US)
- Governors State University (US)
- Venue
- IEEE Internet of Things Journal
- Published
- 2015-12
- Volume
- 2
- Issue
- 6
- Pages
- 527-537
- ISSN
- 2327-4662 (ISSN-L)
- OpenAlex
- W2122502237
- Cited by
- 367
- References
- 10
- Citations by year
- 2026: 6 · 2025: 20 · 2024: 16 · 2023: 33 · 2022: 43 · 2021: 41 · 2020: 47 · 2019: 62 · 2018: 48 · 2017: 32 · 2016: 16 · 2015: 3
- FWCI
- 44.79
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- IEEE Internet of Things Journal (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Engineering › Building and Construction › Building Energy and Comfort Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Computer Science › Hardware and Architecture › Energy Efficiency in Computing
- Keywords
- Internet of Things, building energy efficiency, energy proportionality, energy control, smartphone platforms, cloud computing, green office buildings, network intelligence, smart grid, energy conservation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
