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Application of the Internet of Things (IoT) for Energy Efficiency in Buildings: A Bibliometric Review.

  • Nnaemeka Nwankwo
  • Ezekiel Chinyio
  • Emmanuel Daniel
  • Louis Gyoh

Buildings are experiencing tremendous transformation, where Internet of things (IoT) is been used to transform traditional buildings into smart structures. While there are viable IoT techniques, developing IoT applications and operations to fully realise the technology's promise is needed. This may be done successfully by bridging the gaps in the present research to establish a foundation for future investigations. This study analysed extant literature in IoT (between 2008 and 2022) through a bibliometric review to tease out critical measures for their integration and transformation. The study adopted a science mapping quantitative literature review approach and employed bibliometric and visualisation techniques to systematically investigate data. The Scopus database was used to collect data and VOSviewer software to analyse the data collected to determine the strengths, weights, clusters, research trends in IoT. Important findings emerging from the study include recent literature by various researchers on IoT applications in buildings. The shift in recent patterns of research from developed to developing countries. Eighty-nine (89) keywords were analysed and divided into six clusters. Each cluster is discussed to present its research area and associated future studies in relation to Smart buildings. This paper uses bibliometric analysis to unpick recent trends in IoT and its relevant application to buildings. The paper provides a blueprint for future IoT research and practice, needed awareness and future strategy directions for IoT applications in construction. This creates opportunities to transition to more sustainable construction sector

  • Keywords:
  • Bibliometric review,
  • Energy efficient buildings,
  • IOT (Internet of Things),
  • Literature review,
  • Smart buildings,
  • sustainability,
  • science mapping,
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Nnaemeka Nwankwo

University of Wolverhampton, United Kingdom - ORCID: 0009-0009-1681-8249

Ezekiel Chinyio

University of Wolverhampton, United Kingdom - ORCID: 0000-0001-8448-5671

Emmanuel Daniel

University of Wolverhampton, United Kingdom - ORCID: 0000-0002-5675-1845

Louis Gyoh

University of Wolverhampton, United Kingdom - ORCID: 0000-0002-8257-9380

  1. Ahad, M. A., Paiva, S., Tripathi, G. & Feroz, N. (2020). Enabling technologies and sustainable smart cities. Sustainable Cities and Society, Vol. 61, p.102301.
  2. Al-Obaidi, K. M., Hossain, M., Alduais, N. A. M., Al-Duais, H. S., Omrany, H. & Ghaffarianhoseini, A. (2022). A Review of Using IoT for Energy Efficient Buildings and Cities: A Built Environment Perspective. Energies, Vol.15 No.16, p. 5991.
  3. Alsamhi, S. H., Ma, O., Ansari, M. S. & Meng, Q. (2019). Greening internet of things for greener and smarter cities: a survey and future prospects. Telecommunication Systems, Vol. 72 No. 4, pp.609–632.
  4. Alsamhi, S. H., Ma, O., Ansari, M. S. & Almalki, F. A. (2019). Survey on collaborative smart drones and internet of things for improving smartness of smart cities. IEEE Access, Vol. 7, pp.128125–128152.
  5. AlSawafi, Y., Touzene, A., Day, K. & Alzeidi, N. (2020). Hybrid RPL-based sensing and routing protocol for smart city. International Journal of Pervasive Computing and Communications, Vol. 16 No.3, pp.279–306.
  6. Awan, F. M., Saleem, Y., Minerva, R. & Crespi, N. (2020). A Comparative Analysis of Machine/Deep Learning Models for Parking Space Availability Prediction. Sensors, Vol. 20 No. 1, p.322.
  7. Azzaoui, A. el, Singh, S. K., Pan, Y. & Park, J. H. (2020) ‘Block5GIntell: Blockchain for AI-Enabled 5G Networks. IEEE Access, Vol. 8, pp.145918–145935.
  8. Baghalzadeh Shishehgarkhaneh, M., Keivani, A., Moehler, R. C., Jelodari, N. & Roshdi Laleh, S. (2022) ‘Internet of Things (IoT), Building Information Modeling (BIM), and Digital Twin (DT) in Construction Industry: A Review, Bibliometric, and Network Analysis. Buildings, Vol. 12 No.10, DOI: 10.3390/BUILDINGS12101503
  9. Bola, M. H., Onwuka, E. N., & Zubair, S. (2019) An Efficient Energy Management in Buildings Using IoT - A Survey. 15th International Conference on Electronics, Computer and Computation, ICECCO 2019, DOI: 10.1109/ICECCO48375.2019.9043231
  10. Brynskov, M., Heijnen, A., Balestrini, M. & Raetzsch, C. (2018) ‘Experimentation at scale: challenges for making urban informatics work’, Smart and Sustainable Built Environment, Vol. 7 No. 1, pp.150–163.
  11. Cavalieri, A., Reis, J. & Amorim, M. (2021) ‘Circular Economy and Internet of Things: Mapping Science of Case Studies in Manufacturing Industry’, Sustainability, Vol. 13 No.6, p.3299.
  12. Chen, F., Xiao, Z., Cui, L., Lin, Q., Li, J. & Yu, S. (2020) Blockchain for Internet of things applications: A review and open issues. Journal of Network and Computer Applications, Vol. 172, p.102839.
  13. Cobo, M. J., Martínez, M. A., Gutiérrez-Salcedo, M., Fujita, H. & Herrera-Viedma, E. (2015). 25 years at Knowledge-Based Systems: A bibliometric analysis. Knowledge-Based Systems, Vol. 80, pp.3–13.
  14. Energy Information Administration (EIA) (2013). EIA Projects World Energy Consumption Will Increase 56% by 2040”. Available at: https://www.eia.gov/todayinenergy/detail.php?id=12251#:~{}:text=Source%3A%20U.S.%20Energy%20Information%20Administration,Btu)%20to%20820%20quadrillion%20Btu (accessed 8 December 2022)
  15. Faheem, M., Butt, R. A., Raza, B., Ashraf, M. W., Ngadi, M. A. & Gungor, V. C. (2019). Energy efficient and reliable data gathering using internet of software-defined mobile sinks for WSNs-based smart grid applications. Computer Standards & Interfaces, Vol. 66, p.103341.
  16. Ferreira, M. P., Pinto, C. F. & Serra, F. R. (2014). The transaction costs theory in international business research: A bibliometric study over three decades. Scientometrics, Vol. 98 No. 3, p.1899–1922.
  17. Fragkos, P., Tasios, N., Paroussos, L., Capros, P. & Tsani, S. (2017). Energy system impacts and policy implications of the European Intended Nationally Determined Contribution and low-carbon pathway to 2050. Energy Policy, Vol. 100, pp.216–226.
  18. Gholamzadehmir, M., del Pero, C., Buffa, S., Fedrizzi, R., & Aste, N. (2020). Adaptive-predictive control strategy for HVAC systems in smart buildings – A review. Sustainable Cities and Society, Vol. 63, p.102480.
  19. Ghahramani, A., Galicia, P., Lehrer, D., Varghese, Z., Wang, Z. & Pandit, Y. (2020). Artificial Intelligence for Efficient Thermal Comfort Systems: Requirements, Current Applications and Future Directions. Frontiers in Built Environment, Vol. 6 No. 49.
  20. Hariri, R. H., Fredericks, E. M. & Bowers, K. M. (2019). Uncertainty in big data analytics: survey, opportunities, and challenges. Journal of Big Data, pp.1–16, DOI: 10.1186/S40537-019-0206-3/TABLES/2
  21. Hemmings, J. (2020). Reconstructing Order: The Geopolitical Risks in China’s Digital Silk Road. Asia Policy, Vol. 27 No. 1, pp.5–21.
  22. siKanan, R., Elhassan, O. & Bensalem, R. (2018). An IoT-based autonomous system for workers’ safety in construction sites with real-time alarming, monitoring, and positioning strategies. Automation in Construction, Vol. 88, pp.73–86.
  23. Kumar, T., Srinivasan, R. & Mani, M. (2022). An Emergy-based Approach to Evaluate the Effectiveness of Integrating IoT-based Sensing Systems into Smart Buildings. Sustainable Energy Technologies and Assessments, Vol. 52, p.102225
  24. Lawal, K., & Rafsanjani, H. N. (2022). Trends, benefits, risks, and challenges of IoT implementation in residential and commercial buildings. Energy and Built Environment, Vol. 3 No. 3, pp.251–266.
  25. Leydesdorff, L.& Nerghes, A. (2017). Co-word maps and topic modeling: A comparison using small and medium-sized corpora (N > 1,000). Journal of the Association for Information Science & Technology, Vol. 68 No. 4, pp.1024–1035.
  26. Liu, M. & Heiselberg, P. (2019). Energy flexibility of a nearly zero-energy building with weather predictive control on a convective building energy system and evaluated with different metric. Applied Energy, pp.233–234, pp.764–775, DOI: 10.1016/J.APENERGY.2018.10.070
  27. Mataloto, B., Ferreira, J. C. & Cruz, N. (2019). LoBEMS—IoT for Building and Energy Management Systems. Electronics 2019, Vol. 8 No. 7, p.763.
  28. Mas-Tur, A., Roig-Tierno, N., Sarin, S., Haon, C., Sego, T., Belkhouja, M., Porter, A. & Merigó, J. M. (2021). Co-citation, bibliographic coupling and leading authors, institutions and countries in the 50 years of Technological Forecasting and Social Change. Technological Forecasting and Social Change, Vol. 165, p.120487.
  29. Nguyen, D. C., Pathirana, P. N., Ding, M. & Seneviratne, A. (2020). Blockchain for 5G and beyond networks: A state of the art survey. Journal of Network and Computer Applications, Vol. 166, p.102693.
  30. Obi, L., Arif, M., Daniel, E. I., Oladinrin, O. T. & Goulding, J. S. (2023). Establishing underpinning concepts for integrating circular economy and offsite construction: a bibliometric review’, Built Environment Project and Asset Management, Vol. 13 No. 1, pp.123–139.
  31. Patel, A.,K., Singh, M., Singh, K., Patel, A., K, Verma, A., K. & Kuri, R. (2021). Visualizing Publication Trends in Webology Journal: A Bibliometric Review based on the Scopus Database (2006-2020. Available at: https://www.researchgate.net/publication/353914061_Visualizing_Publication_Trends_in_Webology_Journal_A_Bibliometric_Review_based_on_the_Scopus_Database_2006-2020 (accessed 24 February 2023).
  32. Perianes-Rodriguez, A., Waltman, L. & van Eck, N. J. (2016). Constructing bibliometric networks: A comparison between full and fractional counting. Journal of Infor-metrics, Vol. 10 No. 4, pp.1178–1195.
  33. Plageras, A. P., Psannis, K. E., Stergiou, C., Wang, H. & Gupta, B. B. (2018). Efficient IoT-based sensor BIG Data collection–processing and analysis in smart buildings. Future Generation Computer Systems, Vol. 82, pp. 349–357.
  34. Rafsanjani, H. N., & Ghahramani, A. (2019). Extracting occupants’ energy-use patterns from Wi-Fi networks in office buildings. Journal of Building Engineering, Vol. 26, p.100864.
  35. Rafsanjani, H. N., Ahn, C. R. & Chen, J. (2018). Linking building energy consumption with occupants’ energy-consuming behaviors in commercial buildings: Non-intrusive occupant load monitoring (NIOLM). Energy and Buildings, Vol. 172, pp.317–327.
  36. Rani, S. & Kumar, R. (2022). Bibliometric review of actuators: Key automation technology in a smart city framework. Materials Today: Proceedings, Vol. 60, pp. 1800–1807.
  37. Rani, S., Talwar, R., Malhotra, J., Ahmed, S. H., Sarkar, M. & Song, H. (2015). A Novel Scheme for an Energy Efficient Internet of Things Based on Wireless Sensor Networks. Sensors 2015, Vol. 15 No. 11, pp.28603–28626.
  38. Rejeb, A., Rejeb, K., Simske, S., Treiblmaier, H. & Zailani, S. (2022). The big picture on the internet of things and the smart city: a review of what we know and what we need to know. Internet of Things, Vol. 19, p. 100565.
  39. Rejeb, A., Rejeb, · Karim, Steven, ·, Simske, J., Keogh, J. G., Rejeb, K., Simske, S. J. & Org, J. (2021). Blockchain technology in the smart city: a bibliometric review. Quality & Quantity, Vol. 56 No. 5, pp.2875–2906.
  40. Rivera, M. A., & Pizam, A. (2015). Advances in hospitality research: from Rodney Dangerfield to Aretha Franklin. International Journal of Contemporary Hospitality Management, Vol. 27 No. 3, pp.362–378.
  41. Saha, J., Saha, A. K., Chatterjee, A., Agrawal, S., Saha, A., Kar, A. & Saha, H. N. (2018). Advanced IOT based combined remote health monitoring, home automation and alarm system. IEEE 8th Annual Computing and Communication Workshop and Conference, pp.602–606, DOI: 10.1109/CCWC.2018.8301659
  42. Serale, G., Fiorentini, M., Capozzoli, A., Bernardini, D. & Bemporad, A. (2018). Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities. Energies 2018, Vol. 11, No. 3, p. 631.
  43. Siountri, K., Skondras, E. & Vergados, D. D. (2020). Developing Smart Buildings Using Blockchain, Internet of Things, and Building Information Modeling. International Journal of Interdisciplinary Telecommunications and Networking (IJITN), Vol. 12 No. 3, pp. 1–15.
  44. Sobin, C. C. (2020). A Survey on Architecture, Protocols and Challenges in IoT. Wireless Personal Communications, Vol. 112 No. 3, pp. 1383–1429.
  45. Sustainable Development Goal (SDG) – (2015). THE 17 GOALS. Available at: https://sdgs.un.org/goals (accessed 12, March 2023).
  46. Syed, D., Zainab, A., Ghrayeb, A., Refaat, S. S., Abu-Rub, H. & Bouhali, O. (2021). Smart Grid Big Data Analytics: Survey of Technologies, Techniques, and Applications. IEEE Access, Vol. 9, pp. 59564–59585.
  47. Xu, H., He, Y., Sun, X., He, J., & Xu, Q. (2020). Prediction of thermal energy inside smart homes using IoT and classifier ensemble techniques. Computer Communications, Vol. 151, pp. 581–589.
  48. Tavares-Lehmann, A. T. & Varum, C. (2021). Industry 4.0 and Sustainability: A Bibliometric Literature Review. Sustainability. Vol. 13 No. 6, p. 3493.
  49. Van Eck, N. J. & Waltman, L. (2014). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, Vol. 84 No. (2), pp. 523–538.
  50. Wang, Y., Zhang, F., Wang, J., Liu, L. & Wang, B. (2021). A Bibliometric Analysis of Edge Computing for Internet of Things. Security and Communication Networks, DOI: 10.1155/2021/5563868
  51. Wuni, I. Y., Shen, G. Q. & Osei-Kyei, R. (2020). Sustainability of off-site construction: A bibliometric review and visualized analysis of trending topics and themes. Journal of Green Building, Vol. 15 No. 4, pp. 131–154.
  52. Xu, H., He, Y., Sun, X., He, J. & Xu, Q. (2020). Prediction of thermal energy inside smart homes using IoT and classifier ensemble techniques. Computer Communications, Vol. 151, pp.581–589.
  53. Yin, X., Liu, H., Chen, Y. & Al-Hussein, M. (2019). Building information modelling for off-site construction: Review and future directions. Automation in Construction, Vol. 101, pp.72–91.
  54. Zupic, I. & Čater, T. (2015). Bibliometric Methods in Management and Organization. Organizational Research Methods, Vol. 18 No. 3, pp.429–472.
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  • Publication Year: 2023
  • Pages: 1072-1084

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  • Publication Year: 2023

Chapter Information

Chapter Title

Application of the Internet of Things (IoT) for Energy Efficiency in Buildings: A Bibliometric Review.

Authors

Nnaemeka Nwankwo, Ezekiel Chinyio, Emmanuel Daniel, Louis Gyoh

DOI

10.36253/979-12-215-0289-3.107

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY-NC 4.0

Metadata License

CC0 1.0

Bibliographic Information

Book Title

CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality

Book Subtitle

Managing the Digital Transformation of Construction Industry

Editors

Pietro Capone, Vito Getuli, Farzad Pour Rahimian, Nashwan Dawood, Alessandro Bruttini, Tommaso Sorbi

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY-NC 4.0

Metadata License

CC0 1.0

Publisher Name

Firenze University Press

DOI

10.36253/979-12-215-0289-3

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979-12-215-0289-3

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979-12-215-0257-2

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Proceedings e report

Series ISSN

2704-601X

Series E-ISSN

2704-5846

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