Abstract
The opinion about the difficulties of maintaining appropriate climatic conditions at sports facilities is quite popular among athletes of various disciplines. This problem can lead to health and economic problems. First of all, users of the facilities are not provided with proper conditions for sports, which can lead to bruises. Secondly, the cost of using the object increases. With the increasing number of sports facilities, maintaining internal thermal comfort in them, while ensuring low operating costs, is becoming increasingly important. The article presents the work on modeling the microclimate in a multifunctional sports hall with the most maximum mode of its use and a detailed analysis of the maintenance of thermal comfort in the hall and cognitive-utilitarian conclusions.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Escandón, R., Ascione, F., Bianco, N., Mauro, G.M., Suárez, R., Sendra, J.J.: Thermal comfort prediction in a building category: artificial neural network generation from calibrated models for a social housing stock in southern Europe. Appl. Thermal Eng. 150, 492–505 (2019)
Altayeva, A., Omarov, B., Suleimenov, Z., Im Cho, Y.: Application of multi-agent control systems in energy-efficient intelligent building. In: 2017 Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems (IFSA-SCIS), pp. 1–5. IEEE, June 2017
Omarov, B., Altayeva, A., Im Cho, Y.: Smart building climate control considering indoor and outdoor parameters. In: Saeed, K., Homenda, W., Chaki, R. (eds.) CISIM 2017. LNCS, vol. 10244, pp. 412–422. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-59105-6_35
Moshkalov, A.K., Baimuhkanbetov, B.M., Baikulova, A.M., Anarbayev, A.K., Ibrayev, A.Z., Mynbayeva, A.P.: The content-structure model of students’ artistic selfdevelopment through the use of information and communications technology. Astra Salvensis—Rev. Hist. Cult. VI (12), 363–383 (2018)
Hilliard, T., Swan, L., Qin, Z.: Experimental implementation of whole building MPC with zone based thermal comfort adjustments. Build. Environ. 125, 326–338 (2017)
Kabrein, H., Yusof, M.Z.M., Hariri, A., Leman, A.M., Afandi, A.: Improving indoor air quality and thermal comfort in office building by using combination filters. In: IOP Conference Series: Materials Science and Engineering, vol. 243, No 1, p. 012052. IOP Publishing, September 2017
Omarov, B., et al.: Agent based modeling of smart grids in smart cities. In: Chugunov, A., Misnikov, Y., Roshchin, E., Trutnev, D. (eds.) EGOSE 2018. CCIS, vol. 947, pp. 3–13. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-13283-5_1
Altayeva, A., Omarov, B., Im Cho, Y.: Towards smart city platform intelligence: PI decoupling math model for temperature and humidity control. In: 2018 IEEE International Conference on Big Data and Smart Computing (BigComp), pp. 693–696. IEEE, January 2018
Buyak, N.A., Deshko, V.I., Sukhodub, I.O.: Buildings energy use and human thermal comfort according to energy and exergy approach. Energy Build. 146, 172–181 (2017)
Gaonkar, P., Aadhithan, N.A., Bapat, J., Das, D.: Energy budget constrained comfort optimization for smart buildings. In: 2017 IEEE Region 10 Symposium (TENSYMP), pp. 1–5. IEEE, July 2017
Lin, C.M., Liu, H.Y., Tseng, K.Y., Lin, S.F.: Heating, ventilation, and air conditioning system optimization control strategy involving fan coil unit temperature control. Appl. Sci. 9(11), 2391 (2019)
Hao, J., Dai, X., Zhang, Y., Zhang, J., Gao, W.: Distribution locational real-time pricing based smart building control and management. In: 2016 North American Power Symposium (NAPS), pp. 1–6. IEEE, September 2016
Brissette, A., Carr, J., Juneau, P.: The occupant comfort challenge of building energy savings through HVAC control. In: 2017 IEEE Conference on Technologies for Sustainability (SusTech), pp. 1–7. IEEE, November 2017
Ding, Y., Wang, Q., Kong, X., Yang, K.: Multi-objective optimisation approach for campus energy plant operation based on building heating load scenarios. Appl. Energy 250, 1600–1617 (2019)
Shektibayev, N.A., et al.: A model of the future teachers’ professional competence formation in the process of physics teaching. Man India 97(11), 517–529 (2017)
Omarov, B., Orazbaev, E., Baimukhanbetov, B., Abusseitov, B., Khudiyarov, G., Anarbayev, A.: Test battery for comprehensive control in the training system of highly Skilled Wrestlers of Kazakhstan on National wrestling “Kazaksha Kuresi”. Man India 97(11), 453–462 (2017)
Narynov, S., Mukhtarkhanuly, D., Omarov, B.: Dataset of depressive posts in Russian language collected from social media. Data Brief 29, 105195 (2020)
Zhang, C., Kuppannagari, S.R., Kannan, R., Prasanna, V.K.: Building HVAC scheduling using reinforcement learning via neural network based model approximation. In: Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, pp. 287–296, November 2019
Omarov, B., et al.: Fuzzy-PID based self-adjusted indoor temperature control for ensuring thermal comfort in sport complexes. J. Theor. Appl. Inf. Technol. 98(11) (2020)
Haniff, M.F., Selamat, H., Khamis, N., Alimin, A.J.: Optimized scheduling for an air-conditioning system based on indoor thermal comfort using the multi-objective improved global particle swarm optimization. Energy Effi. 12(5), 1183–1201 (2018). https://doi.org/10.1007/s12053-018-9734-5
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Omarov, B. et al. (2020). Ensuring Comfort Microclimate for Sportsmen in Sport Halls: Comfort Temperature Case Study. In: Hernes, M., Wojtkiewicz, K., Szczerbicki, E. (eds) Advances in Computational Collective Intelligence. ICCCI 2020. Communications in Computer and Information Science, vol 1287. Springer, Cham. https://doi.org/10.1007/978-3-030-63119-2_51
Download citation
DOI: https://doi.org/10.1007/978-3-030-63119-2_51
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-63118-5
Online ISBN: 978-3-030-63119-2
eBook Packages: Computer ScienceComputer Science (R0)