Authors:
Marina Dement'eva,Ekaterina Pliusnina,DOI NO:
https://doi.org/10.26782/jmcms.spl.13/2026.05.00010Keywords:
Smart Systems,Control Sensors,Sewer Systems,The Internet of Things,Blockages,Abstract
The increasing depreciation of the housing stock leads to an increase in the failure rate of utility systems. Consequently, losses of utility resources and operating costs increase, and social stability declines. Therefore, a relevant area of research is improving the quality of utility system operation by changing the maintenance planning strategy. The transition from planned to predictive maintenance is possible using smart systems. In this context, this study aimed to develop the architecture of an event-driven system for monitoring violations arising during the operation of utility systems, based on a predictive approach using IoT. This study addressed the scientific and practical problem of developing a system of criteria for detecting violations based on the analysis of IoT sensor signals. It also developed a system of rules for their activation for automated decision-making based on a deterministic approach. The study is based on analytical modeling and predictive analytics. The scientific novelty of the study lies in the proposed conceptual analytical model for decision-making in the event of an emergency during the operation of a residential sewerage system, based on formalized rules for the activation of weight sensors. The practical significance of the study lies in the development of recommendations for adapting the IoT monitoring system to various design solutions for domestic sewerage systems using the example of two countries, Russia and China.References:
I. Dai, Xilei, et al. “Building Gym: An Open-Source Toolbox for AI-Based Building Energy Management Using Reinforcement Learning.” Building Simulation, vol. 18, 2025, pp. 1909–1927. 10.1007/s12273-025-1306-y.
II. Dement’eva, Marina. “Development of Building Exploitation Programs in the Concept of Energy-Sustainable Urban Development.” E3S Web of Conferences, vol. 164, 2020, p. 08016, 10.1051/e3sconf/202016408016.
III. Dement’eva, Marina. “Planning of Operational and Technological Measures based on Logical and Graphical Modeling.” IOP Conference Series: Earth and Environmental Science, vol. 988, 2022 p. 052026, 10.1088/1755-1315/988/5/052026.
IV. Deshpande, Sujit, and Rashmi M. Jogdand. “A Survey on Internet of Things (IoT), Industrial IoT (IIoT) and Industry 4.0.” International Journal of Computer Applications, vol. 175, no. 27, 2020, pp. 20–27, 10.5120/ijca2020920790.
V. Hajjaj, Sami Salama Hussen, et al. “Review of Implementing the Internet of Things (IoT) for Robotic Drones (IoT Drones).” E3S Web of Conferences, vol. 477, 2024, p. 00016. 10.1051/e3sconf/202447700016.
VI. Han, Jize, and Yonglin Zhang. “IoT USN System and Hybrid Architecture Application.” Conference: 2020 Chinese Automation Congress (CAC), 2020, pp. 514–518. 10.1109/CAC51589.2020.9327732.
VII. Huang, Min. “Frequently Asked Questions about Building Water Supply and Drainage Design.” Urban Architecture and Development, vol. 5, no. 13, 2024, pp. 196–198. 10.37155/2717-557X-0513-66.
VIII. Lee, Hyejon, Namje Park, and Hyo-Chan Bang. “The Architecture Design of Semantic Based Open USN Service Platform Model.” Lecture Notes in Electrical Engineering, vol. 274, 2014, pp. 457–462. 10.1007/978-3-642-40675-1-68.
IX. Liu, Lei, et al. “Application of Internet of Things Technology in the Field of Environmental Engineering.” International Conference on Big Data Analytics for Cyber-Physical System in Smart City, 2022, pp. 1149–1156. 10.1007/978-981-16-7466-2_127.
X. Malekloo, Arman, et al. “Machine Learning and Structural Health Monitoring Overview with Emerging Technology and High-Dimensional Data Source Highlights.” Structural Health Monitoring, vol. 21, no. 4, 2021, pp. 1906–1955. 10.1177/14759217211036880.
XI. Maliping. “Research on Application of Key IoT Technology and Computer IoT Technology.” Journal of Physics Conference Series, vol. 1453, no. 1, 2020, p. 012098. 10.1088/1742-6596/1453/1/012098.
XII. Morgenthal, Guido, and Norman Hallermann. “Quality Assessment of Unmanned Aerial Vehicle (UAV) Based Visual Inspection of Structures.” Advances in Structural Engineering, vol. 17, no. 3, 2016, pp. 289–302. 10.1260/1369-4332.17.3.289.
XIII. Mostafa, Basma, et al. “Towards the Enhancement of Buildings’ Sustainability: IoT-Based Building Management Systems (IoT-BMS).” IOP Conference Series: Earth and Environmental Science, vol. 1396, no. 1, 2024, pp. 012020. 10.1088/1755-1315/1396/1/012020.
XIV. Mu, Tong. “Research on the Application of Building Electrical Automation in Modern Buildings.” Smart City Applications, vol. 7, no. 11, 2024, pp. 88–90. 10.33142/sca.v7i11.14204.
XV. Pan, Jianli, et al. “An Internet of Things Framework for Smart Energy in Buildings: Designs, Prototype, and Experiments.” IEEE Internet of Things Journal, vol. 2, no. 6, 2015, pp. 527–537. 10.1109/JIOT.2015.2413397.
XVI. Ranasinghe, Damith, Mark Harrison, and Peter H. Cole. “EPC Network Architecture.” Networked RFID Systems and Lightweight Cryptography. Springer, Berlin, Heidelberg, 2008, pp. 59–78. 10.1007/978-3-540-71641-9_4.
XVII. Shi Xiao-Bing, and Hai-Gang Jiang. “Research on the Application of IoT Data in Construction Operation and Maintenance Management.” Smart Buildings and Smart Cities, vol. 4, 2022, pp. 157–159, 10.13655/j.cnki.ibci.2022.04.047.
XVIII. Xi, Hu, and Rayan H. Assaad. “The Use of Unmanned Ground Vehicles (Mobile Robots) and Unmanned Aerial Vehicles (Drones) in the Civil Infrastructure Asset Management Sector: Applications, Robotic Platforms, Sensors, and Algorithms.” Expert Systems with Applications, vol. 232, 2023. pp. 120897. 10.1016/j.eswa.2023.120897.