Smart Building Technologies in Response to COVID-19
Abstract
:1. Introduction
2. Impact of COVID-19
2.1. Residential Energy Uses
- An increase of 40% for household cooking, a similar change for entertainment, +60% for heating and cooling, +40% for lighting, and +22% to +95% for energy bills in China [8].
- A decrease of 13% in national electricity use; the morning peak reduced and diluted, and the evening peak also reduced and postponed in cases of studied households in Spain [9].
- Approximately, there was the same peak load but a broader distribution in almost 7000 sample households in Poland [10].
- There was almost the same load profile during weekdays, but an increased evening peak in Australia [11].
- There were major alterations in April–May and minor alterations in June–July in the case of studied social housing in Québec, Canada [14].
Key Findings | Key Elements |
---|---|
COVID-19 exacerbated energy poverty, combining increased energy expenditures and decreased incomes [15]. Low-income users are more exposed to energy poverty and more responsive to energy saving [12,16]. | Importance of measured data [10]. Importance of energy awareness in users [10] and in service providers and governments [11]. Importance of support measures [17,18,19,20]. |
2.2. Usage of Information and Communication Technology
2.3. Increased Request of Ventilation
- Increase the input of outdoor air.
- Use fans as an auxiliary to support the effect of open windows.
- Ensure that ventilation systems operate properly and provide acceptable indoor air quality according to the current occupancy level for each space.
- If possible, adjust HVAC systems to increase total airflow to occupied spaces. Disable demand-controlled ventilation controls that could reduce air supply according to occupancy or temperature in occupied hours.
- Improve central air filtration. Ensure that restroom exhaust fans are operating correctly and at full capacity when the building is occupied.
- Inspect and maintain exhaust ventilation systems in areas such as kitchens, cooking areas, etc. Use these systems when these spaces are in use.
- Use portable, high-efficiency particulate air fan/filtration systems to enhance air cleaning.
- Generate a ‘clean-to-less-clean’ air movement by evaluating and repositioning, as necessary, the supply louvers, exhaust air grilles, and/or damper settings.
2.4. Mobility Variation and Electric Vehicle Charge
3. Science and Technology in Response to COVID-19
4. Refrigeration and Measurement
5. Robotics
5.1. Surface Disinfection
5.2. Temperature Measurement
5.3. Supply Chain
5.4. Security
5.5. Telehealthcare
5.6. Special Applications
- provide treatments and enable continuous communication with patients, minimizing the exposure of HCWs and the use of protective equipment;
- improve interactions with individuals subject to isolation, to preserve mental health;
- facilitate the rescheduling of events in virtual mode, instead of cancellation.
6. Sensor Networks for Contagion Modeling
7. Building Automation
7.1. Main Building Automation Rating Systems and Standards
- EN ISO 16484-1: ‘Building automation and control systems project specification and implementation’;
- EN 50173-6:2013: ‘Information technology—generic cabling systems—part 6: distributed building services’;
- EN 50398-1: ‘Alarm systems. Combined and integrated alarm systems. General requirements’;
- CIBSE Guide H: ‘Building control systems’;
- EEUMA Publication 191: ‘Alarm systems—a guide to design, management and procurement’;
- IET ‘Code of Practice for Cyber Security in the Built Environment’;
- ISO/CD 37173: ‘Smart city infrastructure—Development guidelines for information-based system of smart building’.
7.2. Main Building Automation Protocols
- 1-Wire, from Dallas/Maxim
- BACnet (Building Automation and Control networks), maintained by ASHRAE Committee SSPC 135
- BatiBUS, merged to KNX
- C-Bus, Clipsal Integrated Systems Main Proprietary Protocol
- CC-Link Industrial Networks, supported by Mitsubishi Electric
- DALI (Digital Addressable Lighting Interface), specified by IEC 62386
- DSI (Digital Serial Interface for the controlling of lighting in buildings), precursor to DALI
- Dynet, lighting and automation control protocol developed in Sydney, Australia, by the company Dynalite
- EnOcean, low-power wireless protocol for energy harvesting and very-low-power devices
- European Home Systems Protocol (EHS), merged into KNX
- European Installation Bus (EIB) (also known as Instabus), merged into KNX
- INSTEON, SmartHome Labs Pro new two-way protocol, based on Power-BUS
- KNX (also known as Konnex), resulting from Batibus, EHS, and EIB
- LonTalk, protocol for LonWorks technology by Echelon Corporation
- Modbus RTU or ASCII or TCP
- oBIX (Open Building Information Exchange), a standard for RESTful Web Services-based interfaces to building control systems developed by OASIS
- UPB, two-way peer to peer protocol
- VSCP (Very Simple Control Protocol), a free protocol with main focus on building or home automation
- xAP, open protocol
- X10, open standard for communication among electronic devices used for home automation
- Z-Wave, wireless RF protocol
- ZigBee, open protocol for mesh networks
7.3. Buildings Analytics
- consider investing in sensors,
- fine-tune your existing building analytics platform,
- introduce compliance reporting,
- communicate results.
7.4. Case Study
- Case A: healthcare building built in 2001, with subsequent extensions and upgrades to the ventilation system design.
- Case B: healthcare building constructed in 2000, with a deep energy retrofit in 2020/2021, including new ventilation and cooling systems and BACS design.
- Case C: healthcare building completed and opened in 2019.
8. Local Energy Generation and Storage
Case Study
9. Discussion
Economics
10. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Acknowledgments
Conflicts of Interest
References
- UNDP. An Integrated Global Response Is an Investment in Our Future. Available online: https://www.undp.org/coronavirus (accessed on 29 May 2022).
- Ibn-Mohammed, T.; Mustapha, K.B.; Godsell, J.; Adamu, Z.; Babatunde, K.A.; Akintade, D.D.; Acquaye, A.; Fujii, H.; Ndiaye, M.M.; Yamoah, F.A.; et al. A critical analysis of the impacts of COVID-19 on the global economy and ecosystems and opportunities for circular economy strategies. Resour. Conserv. Recycl. 2021, 164, 105169. [Google Scholar] [CrossRef] [PubMed]
- HereWorks. A Timeline in the History of Smart Buildings. Available online: https://hereworks.ie/tech-talk/a-timeline-in-the-history-of-smart-buildings/ (accessed on 29 May 2022).
- Pinheiro, M.D.; Luís, N.C. COVID-19 Could Leverage a Sustainable Built Environment. Sustainability 2020, 12, 5863. [Google Scholar] [CrossRef]
- Web of Science. Available online: www.webofknowledge.com (accessed on 1 March 2021).
- ScienceDirect. Available online: www.sciencedirect.com (accessed on 1 March 2021).
- Manganelli, M.; Leonowicz, Z.; Martirano, L. Domotics. In Power Engineering; CRC Press: Boca Raton, FL, USA, 2018; pp. 370–390. [Google Scholar]
- Cheshmehzangi, A. COVID-19 and household energy implications: What are the main impacts on energy use? Heliyon 2020, 6, e05202. [Google Scholar] [CrossRef] [PubMed]
- Santiago, I.; Moreno-Munoz, A.; Quintero-Jiménez, P.; Garcia-Torres, F.; Gonzalez-Redondo, M. Electricity demand during pandemic times: The case of the COVID-19 in Spain. Energy Policy 2020, 148, 111964. [Google Scholar] [CrossRef]
- Bielecki, S.; Skoczkowski, T.; Sobczak, L.; Buchoski, J.; Maciąg, L.; Dukat, P. Impact of the Lockdown during the COVID-19 Pandemic on Electricity Use by Residential Users. Energies 2021, 14, 980. [Google Scholar] [CrossRef]
- Snow, S.; Bean, R.; Glencross, M.; Horrocks, N. Drivers behind Residential Electricity Demand Fluctuations Due to COVID-19 Restrictions. Energies 2020, 13, 5738. [Google Scholar] [CrossRef]
- Mustapa, S.I.; Rasiah, R.; Jaaffar, A.H.; Abu Bakar, A.; Kaman, Z.K. Implications of COVID-19 pandemic for energy-use and energy saving household electrical appliances consumption behaviour in Malaysia. Energy Strat. Rev. 2021, 38, 100765. [Google Scholar] [CrossRef]
- Manganelli, M.; Soldati, A.; Dalboni, M.; Ramakrishna, S. COVID-19 impact on energy uses and the need for an energy transition. Analysis 2021, 3, 5–10. [Google Scholar]
- Rouleau, J.; Gosselin, L. Impacts of the COVID-19 lockdown on energy consumption in a Canadian social housing building. Appl. Energy 2021, 287, 116565. [Google Scholar] [CrossRef]
- Mastropietro, P. Measures to Tackle the COVID-19 Outbreak Impact on Energy Poverty. 2020. Available online: https://fsr.eui.eu/measures-to-tackle-the-covid-19-outbreak-impact-on-energy-poverty/ (accessed on 1 March 2021).
- Cuerdo-Vilches, T.; Navas-Martín, M.Á.; Oteiza, I. Behavior Patterns, Energy Consumption and Comfort during COVID-19 Lockdown Related to Home Features, Socioeconomic Factors and Energy Poverty in Madrid. Sustainability 2021, 13, 5949. [Google Scholar] [CrossRef]
- Barbosa, R.; Bouzarovski, S.; Castaño-Rosa, R. European Energy Poverty: Agenda Co-Creation and Knowledge Innovation. Call for Action; European Energy Poverty: Brussels, Belgium, 2020. [Google Scholar]
- Hesselman, M.; Varo, A.; Guyet, R.; Thomson, H. Global Map of COVID-19 Household Energy Services Relief Measures. Available online: http://www.engager-energy.net/covid19/ (accessed on 1 December 2021).
- Hesselman, M.; Varo, A.; Guyet, R.; Thomson, H. Energy poverty in the COVID-19 era: Mapping global responses in light of momentum for the right to energy. Energy Res. Soc. Sci. 2021, 81, 102246. [Google Scholar] [CrossRef]
- Igleheart, A.; McMichale, C. The Energy Policy Response to COVID-19: Lessons Learned and Policy Considerations for State Legislatures. Available online: https://www.ncsl.org/research/energy/the-energy-policy-response-to-covid-19-lessons-learned-and-policy-considerations-for-state-legislatures.aspx (accessed on 2 December 2021).
- Microsoft. Update #2 on Microsoft Cloud Services Continuity. 2020. Available online: https://azure.microsoft.com/en-us/blog/update-2-on-microsoft-cloud-services-continuity/ (accessed on 1 March 2021).
- Facebook. Keeping Our Services Stable and Reliable during the COVID-19 Outbreak—About Facebook. 2020. Available online: https://about.fb.com/news/2020/03/keeping-our-apps-stable-during-covid-19/ (accessed on 1 March 2021).
- Yuan, E.S. A Message to Our Users. 2020. Available online: https://blog.zoom.us/a-message-to-our-users/ (accessed on 1 March 2021).
- Klebnikov, S. 5 Big Numbers That Show Amazon’s Explosive Growth during the Coronavirus Pandemic. 2021. Available online: https://www.forbes.com/sites/sergeiklebnikov/2020/07/23/5-big-numbers-that-show-amazons-explosive-growth-during-the-coronavirus-pandemic/ (accessed on 1 March 2021).
- Ong, D.; Moors, T.; Sivaraman, V. Complete life-cycle assessment of the energy/CO2 costs of videoconferencing vs face-to-face meetings. In Proceedings of the 2012 IEEE Online Conference on Green Communications (GreenCom), Piscataway, NJ, USA, 25–28 September 2012; pp. 50–55. [Google Scholar]
- Manganelli, M.; Soldati, A.; Martirano, L.; Ramakrishna, S. Strategies for Improving the Sustainability of Data Centers via Energy Mix, Energy Conservation, and Circular Energy. Sustainability 2021, 13, 6114. [Google Scholar] [CrossRef]
- UNDP. The Evolving Digital Divide. Available online: https://www.undp.org/blog/evolving-digital-divide (accessed on 29 May 2022).
- CSO. Impact of COVID-19 on ICT Usage by Households. Available online: https://www.cso.ie/en/releasesandpublications/ep/p-ictc19/impactofcovid-19onictusagebyhouseholds/introductionandkeyfindings/ (accessed on 29 May 2022).
- UN DESA. Policy Brief #89: Strengthening Data Governance for Effective Use of Open Data and Big Data Analytics for Combating COVID-19. Available online: https://www.un.org/development/desa/dpad/publication/un-desa-policy-brief-89-strengthening-data-governance-for-effective-use-of-open-data-and-big-data-analytics-for-combating-covid-19/ (accessed on 29 May 2022).
- CDC. Ventilation in Buildings. 2022. Available online: https://www.cdc.gov/coronavirus/2019-ncov/community/ventilation.html (accessed on 29 May 2022).
- Hattrup-Silberberg, M.; Hausler, S.; Heineke, K.; Laverty, N.; Möller, T.; Schwedhelm, D.; Wu, T. Five COVID-19 Aftershocks Reshaping Mobility’s Future. Available online: https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/five-covid-19-aftershocks-reshaping-mobilitys-future (accessed on 7 December 2021).
- McClone, G.; Kleissl, J.; Washom, B.; Silwal, S. Impact of the coronavirus pandemic on electric vehicle workplace charging. J. Renew. Sustain. Energy 2021, 13, 025701. [Google Scholar] [CrossRef]
- Palomino, A.; Parvania, M.; Zane, R. Impact of COVID-19 on Mobility and Electric Vehicle Charging Load. In Proceedings of the 2021 IEEE Power & Energy Society General Meeting (PESGM), Washington, DC, USA, 26–29 July 2021; pp. 1–5. [Google Scholar]
- Wen, W.; Yang, S.; Zhou, P.; Gao, S. Impacts of COVID-19 on the electric vehicle industry: Evidence from China. Renew. Sustain. Energy Rev. 2021, 144, 1110. [Google Scholar] [CrossRef]
- Ma, L.; Li, H.; Lan, J.; Hao, X.; Liu, H.; Wang, X.; Huang, Y. Comprehensive analyses of bioinformatics applications in the fight against COVID-19 pandemic. Comput. Biol. Chem. 2021, 95, 107599. [Google Scholar] [CrossRef]
- Gunasekeran, D.V.; Tseng, R.M.W.W.; Tham, Y.-C.; Wong, T.Y. Applications of digital health for public health responses to COVID-19: A systematic scoping review of artificial intelligence, telehealth and related technologies. NPJ Digit. Med. 2021, 4, 40. [Google Scholar] [CrossRef]
- Garfan, S.; Alamoodi, A.; Zaidan, B.; Al-Zobbi, M.; Hamid, R.A.; Alwan, J.K.; Ahmaro, I.Y.; Khalid, E.T.; Jumaah, F.; Albahri, O.; et al. Telehealth utilization during the Covid-19 pandemic: A systematic review. Comput. Biol. Med. 2021, 138, 104878. [Google Scholar] [CrossRef]
- Whitelaw, S.; Mamas, M.A.; Topol, E.; Van Spall, H.G.C. Applications of digital technology in COVID-19 pandemic planning and response. Lancet Digit. Health 2020, 2, e435–e440. [Google Scholar] [CrossRef]
- Dettori, M.; Altea, L.; Fracasso, D.; Trogu, F.; Azara, A.; Piana, A.; Arghittu, A.; Saderi, L.; Sotgiu, G.; Castiglia, P. Housing Demand in Urban Areas and Sanitary Requirements of Dwellings in Italy. J. Environ. Public Health 2020, 2020, 1–6. [Google Scholar] [CrossRef] [Green Version]
- Johnson Controls. Hospital HVAC Systems Play Crucial Role in Mitigating Diseases like COVID-19. Available online: https://www.johnsoncontrols.com/media-center/news/press-releases/2020/03/30/hospital-hvac-systems-play-crucial-role-in-mitigating-diseases-like-covid-19 (accessed on 4 June 2022).
- O’Brien, L. How Can We Use Smart City Technology to Help in the COVID-19 Outbreak? Available online: https://www.arcweb.com/blog/how-can-we-use-smart-city-technology-help-covid-19-outbreak (accessed on 4 June 2022).
- Enriko, I.K.A.; Pramono, S.; Adrianto, D.; Alemuda, F. COVID-19 Vaccine Distribution Tracking and Monitoring Using IoT. In Proceedings of the 2021 International Conference on Green Energy, Computing and Sustainable Technology (GECOST), Miri, Malaysia, 7–9 July 2021; pp. 1–5. [Google Scholar]
- Pargaien, A.V.; Pargaien, S.; Adhikari, M.; Maan, M.; Sharma, S.; Joshi, H. The Role of IOT for Monitoring the Wastage of Vaccines Due to Poor Cold Chain Management. In Proceedings of the 2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Palladam, India, 11–13 November 2021; pp. 78–86. [Google Scholar]
- Bhardwaj, T. Vaccines are sensitive products, maintaining robust cold-chain system utmost important: Sanjay Jain, Elanpro|The Financial Express. Financial Express, 11 May 2021. [Google Scholar]
- Dey, S. 25% of vaccines go waste due to lack of cold chain. The Times of India, 1 July 2016. [Google Scholar]
- Yang, G.-Z.; Nelson, B.J.; Murphy, R.R.; Choset, H.; Christensen, H.; Collins, S.H.; Dario, P.; Goldberg, K.; Ikuta, K.; Jacobstein, N.; et al. Combating COVID-19-The role of robotics in managing public health and infectious diseases. Sci. Robot. 2020, 5, 40. [Google Scholar] [CrossRef] [Green Version]
- IEEE. ROBOTS: Your Guide to the World of Robotics. 2022. Available online: https://robots.ieee.org/robots/ (accessed on 1 March 2022).
- Vicente, R.; Mohamed, Y.; Eguíluz, V.M.; Zemmar, E.; Bayer, P.; Neimat, J.S.; Hernesniemi, J.; Nelson, B.J.; Zemmar, A. Modelling the Impact of Robotics on Infectious Spread Among Healthcare Workers. Front. Robot. AI 2021, 8, 652685. [Google Scholar] [CrossRef]
- Javaid, M.; Haleem, A.; Vaish, A.; Vaishya, R.; Iyengar, K.P. Robotics Applications in COVID-19: A Review. J. Ind. Integr. Manag. 2020, 5, 441–451. [Google Scholar] [CrossRef]
- Guizzo, E.; Klett, R. How Robots Became Essential Workers in the COVID-19 Response. Available online: https://spectrum.ieee.org/how-robots-became-essential-workers-in-the-covid19-response (accessed on 14 January 2022).
- Zhao, Z.; Ma, Y.; Mushtaq, A.; Rajper, A.M.A.; Shehab, M.; Heybourne, A.; Song, W.; Ren, H.; Tse, Z.T.H. Applications of Robotics, Artificial Intelligence, and Digital Technologies During COVID-19: A Review. Disaster Med. Public Health Prep. 2021, 16, 1634–1644. [Google Scholar] [CrossRef]
- Sarker, S.; Jamal, L.; Ahmed, S.F.; Irtisam, N. Robotics and artificial intelligence in healthcare during COVID-19 pandemic: A systematic review. Robot. Auton. Syst. 2021, 146, 103902. [Google Scholar] [CrossRef]
- Samani, H. Robotics for Pandemics; Chapman and Hall/CRC: New York, NY, USA, 2021. [Google Scholar]
- LRB Telifon. Abano Hospital in Italy Uses UV-C Robots to Disinfect. 2022. Available online: https://www.regencyrobotics.com/abano.html (accessed on 1 March 2021).
- Weekes, S. How 5G-Powered Robots Are Helping China Fight Coronavirus. 2022. Available online: https://www.smartcitiesworld.nui888et/news/news/how-5g-powered-robots-are-helping-china-fight-coronavirus-5154 (accessed on 1 March 2021).
- Vincent, J. Spot the Robot Is Reminding Parkgoers in Singapore to Keep Their Distance from One Another. 2020. Available online: https://www.theverge.com/2020/5/8/21251788/spot-boston-dynamics-robot-singapore-park-social-distancing (accessed on 1 March 2021).
- Battineni, G.; Chintalapudi, N.; Amenta, F. AI Chatbot Design during an Epidemic like the Novel Coronavirus. Healthcare 2020, 8, 154. [Google Scholar] [CrossRef]
- Erazo, W.S.; Guerrero, G.P.; Betancourt, C.C.; Salazar, I.S. Chatbot Implementation to Collect Data on Possible COVID-19 Cases and Release the Pressure on the Primary Health Care System. In Proceedings of the 2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), Vancouver, BC, Canada, 4–7 November 2020; pp. 0302–0307. [Google Scholar]
- Pranathi, B.S.; Nair, A.; Anushree, C.S.; Chandar, T.S. Sahayantra—A Patient Assistance Robot. In Proceedings of the 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT), Kharagpur, India, 1–3 July 2020; pp. 1–6. [Google Scholar]
- Tsai, S.C.; Samani, H.; Kao, Y.W.; Zhu, K.; Jalaian, B. Design and Development of Interactive Intelligent Medical Agent. In Proceedings of the 2018 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR), Taichung, Taiwan, 10–12 December 2018; pp. 210–215. [Google Scholar]
- SenseTime. Smart AI Epidemic Prevention Solution’ Helps Control Coronavirus Cross-Infection. Available online: https://www.sensetime.com/me-en/news-detail/23783?categoryId=21072 (accessed on 29 May 2022).
- Cheng, Z.; Savarimuthu, T.R. A disposable force regulation mechanism for throat swab robot. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. 2021, 2021, 4792–4795. [Google Scholar]
- Wang, S.; Wang, K.; Tang, R.; Qiao, J.; Liu, H.; Hou, Z.-G. Design of a Low-Cost Miniature Robot to Assist the COVID-19 Nasopharyngeal Swab Sampling. IEEE Trans. Med. Robot. Bionics 2020, 3, 289–293. [Google Scholar] [CrossRef]
- Hornbeck, T.; Naylor, D.; Segre, A.M.; Thomas, G.; Herman, T.; Polgreen, P.M. Using sensor networks to study the effect of peripatetic healthcare workers on the spread of hospital-associated infections. J. Infect. Dis. 2012, 206, 1549–1557. [Google Scholar] [CrossRef] [Green Version]
- Isella, L.; Romano, M.; Barrat, A.; Cattuto, C.; Colizza, V.; Van den Broeck, W.; Gesualdo, F.; Pandolfi, E.; Ravà, L.; Rizzo, C.; et al. Close Encounters in a Pediatric Ward: Measuring Face-to-Face Proximity and Mixing Patterns with Wearable Sensors. PLoS ONE 2011, 6, e17144. [Google Scholar] [CrossRef]
- Vanhems, P.; Barrat, A.; Cattuto, C.; Pinton, J.-F.; Khanafer, N.; Régis, C.; Kim, B.-A.; Comte, B.; Voirin, N. Estimating potential infection transmission routes in hospital wards using wearable proximity sensors. PLoS ONE 2013, 8, e73970. [Google Scholar] [CrossRef]
- SocioPatterns. Available online: http://www.sociopatterns.org/ (accessed on 29 May 2022).
- ABarrat, A.; Cattuto, C.; Kivelä, M.; Lehmann, S.; Saramäki, J. Effect of manual and digital contact tracing on COVID-19 outbreaks: A study on empirical contact data. J. R. Soc. Interface 2021, 18, 20201000. [Google Scholar] [CrossRef] [PubMed]
- Cencetti, G.; Santin, G.; Longa, A.; Pigani, E.; Barrat, A.; Cattuto, C.; Lehmann, S.; Salathé, M.; Lepri, B. Digital proximity tracing on empirical contact networks for pandemic control. Nat. Commun. 2021, 12, 1655. [Google Scholar] [CrossRef] [PubMed]
- Standards for Intelligent Buildings: A Quick Guide|Sterling. Available online: https://www.sterling.tech/standards-intelligent-buildings/ (accessed on 21 July 2022).
- List of Automation Protocols—Wikipedia. Available online: https://en.wikipedia.org/wiki/List_of_automation_protocols#Building_automation_protocols (accessed on 21 July 2022).
- Wilson, J. Building Analytics Strategies for COVID-19 Building Operations. 2022. Available online: https://www.healthcarefacilitiestoday.com/posts/Building-Analytics-Strategies-For-COVID-19-Building-Operations--25400 (accessed on 1 March 2021).
- Pedersen, J.M.; Jebaei, F.; Jradi, M. Assessment of Building Automation and Control Systems in Danish Healthcare Facilities in the COVID-19 Era. Appl. Sci. 2022, 12, 427. [Google Scholar] [CrossRef]
- Dalboni, M.; Manganelli, M.; Soldati, A. Assessing the Economic Feasibility of PV-BESS Systems in Connection with Pandemic-induced Loads. In Proceedings of the 2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), Bari, Italy, 7–10 September 2021; pp. 1–6. [Google Scholar]
- Statista. Data Collected by Smart Buildings Worldwide 2010–2020. Available online: https://www.statista.com/statistics/631151/worldwide-data-collected-by-smart-buildings/ (accessed on 29 October 2021).
- Tišler, V.; Jandl, D. Smart Buildings in the Light of COVID-19 Pandemic. 2022. Available online: https://www.cms-lawnow.com/ealerts/2020/11/smart-buildings-in-the-light-of-covid-19-pandemic?cc_lang=en (accessed on 1 March 2021).
- Why Healthy Buildings Matter to Global Real Estate Investors—And to Architects—Omrania. Available online: https://omrania.com/insights/why-healthy-buildings-matter-to-global-real-estate-investors-and-to-architects/ (accessed on 21 July 2022).
Paper Number | ||||||
‘COVID-19’ | and ‘Buildings’ | and ‘Robotics’ | and ‘Healthcare’ | and ‘Automation’ | and ‘AI’ | |
2019 | 62 | 1 | 4 | |||
2020 | 86,013 | 1019 | 218 | 6372 | 240 | 472 |
2021 | 164,807 | 3061 | 540 | 13,150 | 666 | 1418 |
2022 | 74,211 | 1543 | 191 | 5978 | 285 | 650 |
2023 | 43 | 5 | 2 | 2 | ||
2024 | 2 | |||||
Correlation | ||||||
and ‘buildings’ | and ‘robotics’ | and ‘healthcare’ | and ‘automation’ | and ‘AI’ | ||
2019 | 1.61% | 6.45% | ||||
2020 | 1.18% | 0.25% | 7.41% | 0.28% | 0.55% | |
2021 | 1.86% | 0.33% | 7.98% | 0.40% | 0.86% | |
2022 | 2.08% | 0.26% | 8.06% | 0.38% | 0.88% | |
2023 | 11.63% | 4.65% | 4.65% |
‘COVID-19’ | ‘COVID-19’ and ‘Buildings’ | ‘COVID-19’ and ‘Robotics’ | |||
Mahase, E. | 290 | Li, Y. | 11 | Rocco, B. | 7 |
Wiwanikit, V. | 275 | Guney, M. | 6 | Cornejo, J. | 4 |
Lippi, G. | 232 | Karaca, F. | 6 | Elara, M.R. | 4 |
Iacobucci, G. | 216 | Tleuken, A. | 6 | Hameed, I.A. | 4 |
Mungmunpbtipantip, R. | 171 | Tokazhanov, G. | 6 | Nelson, B.J. | 4 |
Dhama, K. | 167 | Turkyimaz, A. | 6 | Patel, V. | 4 |
Wiwanikit, V. | 164 | Aguilar, A.J. | 5 | Peng, C. | 4 |
Baden, L.R. | 151 | Aletta, F. | 5 | Tavakoli, M. | 4 |
Henry, B.M. | 147 | Chen, W. | 5 | Ye, R. | 4 |
Rezaei, N. | 145 | Cowling, B.J. | 5 | Atashzarm S.F. | 3 |
‘COVID-19’ and Healthcare’ | ‘COVID-19’ and ‘Automation’ | ‘COVID-19’ and ‘AI’ | |||
Essar, M.Y. | 26 | Carroll, K.C. | 4 | Saba, L. | 12 |
Javaid, M. | 24 | Dogné, J.M. | 3 | Suri, J.S. | 11 |
Temsah, M.H. | 23 | Douxfils, J. | 3 | Al-Turjman, F. | 10 |
Haleem, A. | 22 | Franke, J. | 3 | Viskovic, K. | 10 |
Lin, C.Y. | 22 | Haleem, A. | 3 | Agarwal, V. | 9 |
Lucero-Prisno, D.E. | 22 | Javaid, M. | 3 | Balestrieri, A. | 9 |
Griffiths, M.D. | 21 | Lin, W. | 3 | Fatemi, M. | 9 |
Al-Tawfuq, J.A. | 20 | Lippi, G. | 3 | Naidu, S. | 9 |
Bragazzi, N.L. | 20 | Lutgehetmann, M. | 3 | Alizad, A. | 8 |
Khunti, K. | 20 | Faa, G. | 8 |
‘COVID-19’ | ‘COVID-19’ and ‘Buildings’ | ‘COVID-19’ and ‘Robotics’ | |||
Medicine | 191,849 | Social Sciences | 1807 | Computer Science | 467 |
Social Sciences | 48,527 | Medicine | 1746 | Engineering | 371 |
Biochemistry, Genetics, and Molecular Biology | 29,568 | Engineering | 999 | Medicine | 292 |
Computer Science | 26,304 | Computer Science | 884 | Mathematics | 149 |
Immunology and Microbiology | 21,084 | Environmental Science | 748 | Social Sciences | 120 |
Engineering | 20,159 | Business, Management, and Accounting | 542 | Physics and Astronomy | 67 |
Environmental Science | 17,779 | Energy | 336 | Decision Sciences | 58 |
Nursing | 14,631 | Mathematics | 276 | Business, Management, and Accounting | 52 |
Psychology | 13,642 | Arts and Humanities | 268 | Materials Science | 49 |
Pharmacology, Toxicology, and Pharmaceutics | 13,107 | Psychology | 260 | Energy | 47 |
‘COVID-19’ and ‘Healthcare’ | ‘COVID-19’ and ‘Automation’ | ‘COVID-19’ and ‘AI’ | |||
Medicine | 18,531 | Computer Science | 468 | Computer Science | ### |
Social Sciences | 2128 | Medicine | 375 | Medicine | 771 |
Computer Science | 2095 | Engineering | 371 | Engineering | 714 |
Nursing | 1922 | Biochemistry, Genetics, and Molecular Biology | 145 | Mathematics | 347 |
Engineering | 1637 | Social Sciences | 142 | Social Sciences | 301 |
Biochemistry, Genetics, and Molecular Biology | 1621 | Mathematics | 140 | Decision Sciences | 280 |
Immunology and Microbiology | 1348 | Decision Sciences | 115 | Biochemistry, Genetics, and Molecular Biology | 244 |
Environmental Science | 1184 | Business, Management, and Accounting | 82 | Physics and Astronomy | 160 |
Pharmacology, Toxicology, and Pharmaceutics | 1032 | Immunology and Microbiology | 73 | Business, Management, and Accounting | 131 |
Health Professions | 901 | Energy | 69 |
No Improvements | Technical Improvements | Comfort Improvements | Energy Efficiency Improvements | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Domains | A | B | C | A | B | C | A | B | C | A | B | C |
Heating | D | B | C | C | B | B | C | A | B | B | A | B |
Domestic Hot Water | D | D | D | C | D | D | D | D | D | C | C | C |
Cooling | D | B | B | D | B | B | C | A | A | B | B | A |
Ventilation | C | A | A | B | A | A | B | A | A | A | A | A |
Lighting | E | A | B | E | A | B | A | A | A | A | A | A |
Dynamic Envelope | E | C | D | E | C | D | E | C | D | E | C | D |
Electricity | D | E | B | D | C | B | D | E | B | D | E | B |
Monitoring and Control | C | A | B | B | A | B | C | A | B | C | A | B |
Scenario | Daily Energy (kWh) | Annual Cost (EUR) | Annual Saving (EUR) | |||
---|---|---|---|---|---|---|
PV-BESS | EV | Lockdown | From Grid | To Grid | ||
No | No | No | 13 | 0 | 1094 | - |
No | No | Yes | 19 | 0 | 1458 | - |
No | Yes | No | 25 | 0 | 1860 | - |
No | Yes | Yes | 30 | 0 | 2225 | - |
Yes | No | No | 6 | 20 | 448 | 645 |
Yes | No | Yes | 7 | 18 | 552 | 906 |
Yes | Yes | No | 16 | 19 | 1155 | 706 |
Yes | Yes | Yes | 17 | 17 | 1264 | 961 |
Solutions | References | Results | Advantages | Inconveniences |
---|---|---|---|---|
ICT | [21,22,23,24,25,26,27,28,29] | Overcomes the inconvenience for distance working | Working/communication at home, reduce chance of exposition | Not everyone has the proper tools, has requirements on internet |
HVAC improvements | [30] | Improved interior air quality | Enhanced air cycle, decrease the chance for infection | Some buildings may have difficulties to carry out modifications on HVAC system; also, some improvements require a specific filter that may be hard to find |
Refrigeration/Cold chain | [42,43,44,45] | Management and surveillance for storage and supply of medical equipment | Reduce the waste of medical equipment | The system still has space to improve, and not all the countries have high standard cold chain system |
Robotics | [46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63] | Help people improve living quality in many ways | Ease the work load for humans; can perform better on some long repetitive tasks or highly dangerous tasks | Significant increase in input costs, need time to train, limit ability to deal with unexpecting situation |
Sensor networks | [64,65,66] | Establishing models of contagion; analysis and surveillance of building performance | Help people better understand disease’s spread pattern; keep the building work in high efficiency | Cost: different building has different situations; sensor systems may require custom design |
Building automation | [73] | Efficient use of energy and optimal comfort | Improvements in energy efficiency and comfort | Not similar improvements in all sectors (needs attention) |
Local energy generation and storage/PV-BESS | [74] | Significantly reduced energy consumption | Could reduce annual cost on energy bills; have positive effects on sustainability | PV-BESS require suitable location and weather environment to set, cannot apply globally |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Xie, X.; Ramakrishna, S.; Manganelli, M. Smart Building Technologies in Response to COVID-19. Energies 2022, 15, 5488. https://doi.org/10.3390/en15155488
Xie X, Ramakrishna S, Manganelli M. Smart Building Technologies in Response to COVID-19. Energies. 2022; 15(15):5488. https://doi.org/10.3390/en15155488
Chicago/Turabian StyleXie, Xiaoxiong, Seeram Ramakrishna, and Matteo Manganelli. 2022. "Smart Building Technologies in Response to COVID-19" Energies 15, no. 15: 5488. https://doi.org/10.3390/en15155488