Abstract
Recent scientific studies indicate that attention should be paid to the indoor spread of the Covid-19 virus. It is recommended to reduce the number of visitors to the premises and to provide frequent ventilation of the premises. The problem is that it is not known what the risk of infection is in a particular room at a specific time, when and what actions should be taken to reduce the risk. We offer a system that helps monitor the conditions in the premises with the help of sensors, calculate the risk of infection and provide information to reduce the infection risk. We give an insight into the created prototype with data collection from public spaces and data visualization according to user needs.
Supported by the National Research Program of Latvia, Project No. VPP-COVID-2020/1-0025.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Ahlawat, A., Wiedensohler, A., Mishra, S.K., et al.: An overview on the role of relative humidity in airborne transmission of SARS-CoV-2 in indoor environments. Aerosol Air Qual. Res. 20(9), 1856–1861 (2020)
Ali, A.S., Coté, C., Heidarinejad, M., Stephens, B.: Elemental: an open-source wireless hardware and software platform for building energy and indoor environmental monitoring and control. Sensors 19(18), 4017 (2019)
Asadi, S., Bouvier, N., Wexler, A.S., Ristenpart, W.D.: The coronavirus pandemic and aerosols: does COVID-19 transmit via expiratory particles? (2020)
Chamola, V., Hassija, V., Gupta, V., Guizani, M.: A comprehensive review of the COVID-19 pandemic and the role of IoT, drones, AI, blockchain, and 5G in managing its impact. IEEE Access 8, 90225–90265 (2020)
Comba, J.L.: Data visualization for the understanding of COVID-19. Comput. Sci. Eng. 22(6), 81–86 (2020)
Dietz, L., Horve, P.F., Coil, D.A., Fretz, M., Eisen, J.A., Van Den Wymelenberg, K.: 2019 novel coronavirus (COVID-19) pandemic: built environment considerations to reduce transmission. mSystems 5(2), e00245-20 (2020)
Few, S.: Blog post: there’s nothing mere about semantics. https://www.perceptualedge.com/blog/?p=2793. Accessed 14 Apr 2021
Few, S.: Information Dashboard Design: The Effective Visual Communication of Data, vol. 2. O’Reilly, Sebastopol (2006)
Logre, I., Mosser, S., Collet, P., Riveill, M.: Sensor data visualisation: a composition-based approach to support domain variability. In: Cabot, J., Rubin, J. (eds.) ECMFA 2014. LNCS, vol. 8569, pp. 101–116. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-09195-2_7
Marques, G., Miranda, N., Kumar Bhoi, A., Garcia-Zapirain, B., Hamrioui, S., de la Torre Díez, I.: Internet of Things and enhanced living environments: measuring and mapping air quality using cyber-physical systems and mobile computing technologies. Sensors 20(3), 720 (2020)
Marques, G., Roque Ferreira, C., Pitarma, R.: A system based on the Internet of Things for real-time particle monitoring in buildings. Int. J. Environ. Res. Public Health 15(4), 821 (2018)
Minoli, D., Sohraby, K., Occhiogrosso, B.: IoT considerations, requirements, and architectures for smart buildings–energy optimization and next-generation building management systems. IEEE Internet Things J. 4(1), 269–283 (2017)
Morawska, L., Milton, D.K.: It is time to address airborne transmission of coronavirus disease 2019 (COVID-19). Clin. Infect. Dis. 71(9), 2311–2313 (2020)
Mumtaz, R., et al.: Internet of Things (IoT) based indoor air quality sensing and predictive analytic–a COVID-19 perspective. Electronics 10(2), 184 (2021)
Pieš, M., Hájovskỳ, R., Velička, J.: Design, implementation and data analysis of an embedded system for measuring environmental quantities. Sensors 20(8), 2304 (2020)
Protopsaltis, A., Sarigiannidis, P., Margounakis, D., Lytos, A.: Data visualization in Internet of Things: tools, methodologies, and challenges. In: Proceedings of the 15th International Conference on Availability, Reliability and Security, pp. 1–11 (2020)
Rinaldi, S., Flammini, A., Tagliabue, L.C., Ciribini, A.L.C.: An IoT framework for the assessment of indoor conditions and estimation of occupancy rates: results from a real case study. Acta Imeko 8(2), 70–79 (2019)
Saini, J., Dutta, M., Marques, G.: Indoor air quality monitoring systems based on Internet of Things: a systematic review. Int. J. Environ. Res. Public Health 17(14), 4942 (2020)
Salman, N., Kemp, A.H., Khan, A., Noakes, C.: Real time wireless sensor network (WSN) based indoor air quality monitoring system. IFAC-PapersOnLine 52(24), 324–327 (2019)
Setti, L., et al.: Airborne transmission route of COVID-19: why 2 meters/6 feet of inter-personal distance could not be enough (2020)
Somsen, G.A., van Rijn, C., Kooij, S., Bem, R.A., Bonn, D.: Small droplet aerosols in poorly ventilated spaces and SARS-CoV-2 transmission. Lancet Respir. Med. 8(7), 658–659 (2020)
Telicko, J., Vidulejs, D.D., Jakovics, A.: A monitoring system for evaluation of COVID-19 infection risk. J. Build. Phys. (2021). IOP Conference Series: Materials Science and Engineering (MSE), in press
Umair, M., Cheema, M.A., Cheema, O., Li, H., Lu, H.: Impact of COVID-19 on adoption of IoT in different sectors. arXiv preprint arXiv:2101.07196 (2021)
Virbulis, J., Sjomkane, M., Surovovs, M., Jakovics, A.: Numerical model for prediction of indoor COVID-19 infection risk based on sensor data. J. Build. Phys. (2021). IOP Conference Series: Materials Science and Engineering (MSE), in press
Yang, X., Yang, L., Zhang, J.: A WiFi-enabled indoor air quality monitoring and control system: the design and control experiments. In: 2017 13th IEEE International Conference on Control & Automation (ICCA), pp. 927–932. IEEE (2017)
Zhang, R., Li, Y., Zhang, A.L., Wang, Y., Molina, M.J.: Identifying airborne transmission as the dominant route for the spread of COVID-19. Proc. Natl. Acad. Sci. 117(26), 14857–14863 (2020)
Zhao, L., Wu, W., Li, S.: Design and implementation of an IoT-based indoor air quality detector with multiple communication interfaces. IEEE Internet Things J. 6(6), 9621–9632 (2019)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 IFIP International Federation for Information Processing
About this paper
Cite this paper
Arnicans, G., Niedrite, L., Solodovnikova, D., Virbulis, J., Zemnickis, J. (2021). Towards a System to Monitor the Virus’s Aerosol-Type Spreading. In: Byrski, A., Czachórski, T., Gelenbe, E., Grochla, K., Murayama, Y. (eds) Computer Science Protecting Human Society Against Epidemics. ANTICOVID 2021. IFIP Advances in Information and Communication Technology, vol 616. Springer, Cham. https://doi.org/10.1007/978-3-030-86582-5_9
Download citation
DOI: https://doi.org/10.1007/978-3-030-86582-5_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-86581-8
Online ISBN: 978-3-030-86582-5
eBook Packages: Computer ScienceComputer Science (R0)