Abstract
In this paper, we present the architecture and implementation of the environmental monitoring system, which is one of the main elements of the Smart City system, deployed in a small town in Poland – Boguchwała, Podkarpacie. The system is based on the Internet of Things devices and Cloud Native techniques, which allow for measuring several environmental parameters like pollution, EMF pollution, and acoustic threats. In addition to these parameters, characteristic of environmental monitoring, the system has been enhanced with video monitoring techniques, such as evaluating the traffic intensity on the main roads and crowd detection. In particular, a front-end application was implemented to visualize the results on a city map. The system is deployed on Raspberry Pi and NVidia Jetson using Kubernetes as resources orchestrator. We managed to design, implement, and deploy a system that makes measurements and predicts the parameters indicated. The proposed solution has no significant impact on the energy consumption of the measuring stations while increasing the scalability and extensibility of the system.
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References
Patnaik, P.: Handbook of Environmental Analysis. CRC Press, Boca Raton (2017)
Wiersma, G.B.: Environmental Monitoring. CRC Press, Boca Raton (2004)
Duangsuwan, S., Takarn, A., Nujankaew, R., Jamjareegulgarn, P.: A study of air pollution smart sensors lpwan via nb-iot for Thailand smart cities 4.0. In: 2018 10th International Conference on Knowledge and Smart Technology (KST), pp. 206–209 (2018)
Jiang, X., Zhang, P., Huang, J.: Prediction method of environmental pollution in smart city based on neural network technology. Sustain. Comput. Inf. Syst. 36, 100799 (2022)
Singh, S., et al.: A novel framework to avoid traffic congestion and air pollution for sustainable development of smart cities. Sustain. Energy Technol. Assess. 56, 103125 (2023)
Shahid, N., Shah, M.A., Khan, A., Maple, C., Jeon, G.: Towards greener smart cities and road traffic forecasting using air pollution data. Sustain. Cities Soc. 72, 103062 (2021)
Fadda, M., Anedda, M., Girau, R., Pau, G., Giusto, D.D.: A social internet of things smart city solution for traffic and pollution monitoring in Cagliari. IEEE Internet Things J. 10(3), 2373–2390 (2023)
Rappaport, T.: Wireless Communications: Principles and Practice, 2nd edn. Prentice Hall PTR, Upper Saddle River (2001)
Walfisch, J., Bertoni, H.: A theoretical model of uhf propagation in urban environments. IEEE Trans. Ant. Propagat. 36(12), 1788–1796 (1988)
Ikegami, F., Takeuchi, T., Yoshida, S.: Theoretical prediction of mean field strength for urban mobile radio. IEEE Trans. Ant. Propagat. 39(3), 299–302 (1991)
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Hajder, M., Hajder, L., Hajder, P., Kolbusz, J. (2023). Cloud Native Approach to the Implementation of an Environmental Monitoring System for Smart City Based on IoT Devices. In: Mikyška, J., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational Science – ICCS 2023. ICCS 2023. Lecture Notes in Computer Science, vol 10477. Springer, Cham. https://doi.org/10.1007/978-3-031-36030-5_41
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DOI: https://doi.org/10.1007/978-3-031-36030-5_41
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