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Ren C, Zhu HC, Wang J, Feng Z, Chen G, Haghighat F, Cao SJ. Intelligent operation, maintenance, and control system for public building: Towards infection risk mitigation and energy efficiency. Sustain Cities Soc 2023; 93:104533. [PMID: 36941886 PMCID: PMC10017170 DOI: 10.1016/j.scs.2023.104533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 02/07/2023] [Accepted: 03/14/2023] [Indexed: 06/18/2023]
Abstract
During the post-COVID-19 era, it is important but challenging to synchronously mitigate the infection risk and optimize the energy savings in public buildings. While, ineffective control of ventilation and purification systems can result in increased energy consumption and cross-contamination. This paper is to develop intelligent operation, maintenance, and control systems by coupling intelligent ventilation and air purification systems (negative ion generators). Optimal deployment of sensors is determined by Fuzzy C-mean (FCM), based on which CO2 concentration fields are rapidly predicted by combing the artificial neural network (ANN) and self-adaptive low-dimensional linear model (LLM). Negative oxygen ion and particle concentrations are simulated with different numbers of negative ion generators. Optimal ventilation rates and number of negative ion generators are decided. A visualization platform is established to display the effects of ventilation control, epidemic prevention, and pollutant removal. The rapid prediction error of LLM-based ANN for CO2 concentration was below 10% compared with the simulation. Fast decision reduced CO2 concentration below 1000 ppm, infection risk below 1.5%, and energy consumption by 27.4%. The largest removal efficiency was 81% when number of negative ion generators was 10. This work can promote intelligent operation, maintenance, and control systems considering infection prevention and energy sustainability.
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Affiliation(s)
- Chen Ren
- School of Architecture, Southeast University, Nanjing, 210096, China
| | - Hao-Cheng Zhu
- School of Architecture, Southeast University, Nanjing, 210096, China
| | - Junqi Wang
- School of Architecture, Southeast University, Nanjing, 210096, China
- School of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou, 215009, China
| | - Zhuangbo Feng
- School of Architecture, Southeast University, Nanjing, 210096, China
| | - Gang Chen
- The Third Construction Co., Ltd of China Construction Eighth Engineering Division, Nanjing, 210046, China
| | - Fariborz Haghighat
- Energy and Environment Group, Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, H3G 1M8, Canada
| | - Shi-Jie Cao
- School of Architecture, Southeast University, Nanjing, 210096, China
- Global Centre for Clean Air Research, Department of Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, GU2 7XH, United Kingdom
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