Abstract
Because the nodes in the data transmission network are generally fixed, once there is a problem of node missing or interference, the reliability of data transmission will be reduced, which will affect the performance of the monitoring system. Therefore, a group building construction energy consumption monitoring system based on mobile nodes is designed. First, the system framework including operation layer, decision-making layer and management layer is designed. Secondly, according to the monitoring content of energy consumption data information of large-scale group buildings, the hardware structure of the system is optimized. Finally, through the wireless transmission technology of mobile nodes, the accurate collection and effective transmission of energy consumption in group building construction are carried out, so as to complete the energy consumption monitoring function of the system. Finally, the experiment proves that the energy consumption monitoring system of group building construction based on mobile nodes has high practicability in the practical application process.
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References
Fu, Q., Wu, S., Dai, D., et al.: Method of building energy consumption prediction based on transferring deep reinforcement learning. Appl. Res. Comput. 37(S1), 92–94 (2020)
Ji, T., Wang, T.: Building energy consumption prediction based on word embedding and convolutional neural network. J. South China Univ. Technol. (Nat. Sci. Edn.) 49(06), 40–48 (2021)
Xue, B., Gang, L., Lei, H., et al.: Ensemble model of building energy consumption prediction based on feature selection algorithm. Comput. Eng. Des. 41(10), 2892–2896 (2020)
Wang, S., Zhou, X., Dong, J.: Simulation of energy consumption control system for near-zero energy building based on fuzzy PID. Comput. Simul. 38(10), 263–267 (2021)
Moon, J., Park, S., Rho, S., Hwang, E., et al.: Robust building energy consumption forecasting using an online learning approach with R ranger 25(8), 116–119 (2021)
Szustak, L., Wyrzykowski, R., Olas, T., et al.: Correlation of performance optimizations and energy consumption for stncil-based application on intel xeon scalable processors. IEEE Trans. Parallel Distrib. Syst. 33(9), 19–25 (2020)
Liu, X.-J., Hu, S.-K., Li, L.-Y.: Temporal and spatial changes of building energy consumption in China's provinces and analysis of its influencing factors. Math. Pract. Theory 50(06), 74–85 (2020)
Zhang, L., Li, Y.-A., Liu, X.-L.: Research on energy consumption prediction of civil buildings based on grey relational analysis. Archit. Technol. 50(06), 74–85 (2020)
He, L.-H., Cui, X., Hu, Q.-C.: Estimation and simulation of energy consumption of public buildings based on BIM. J. Eng. Manag. 34(02), 84–89 (2020)
Wang, Z.-Q., Guo, H.-J., Wang, S., et al.: Analysis of building energy consumption and discussion on energy-saving reform in an office park. Archit. Technol. 51(06), 670–672 (2020)
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© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Zheng, Y., Yang, E., Cao, S., Zeng, K. (2023). Design of Energy Consumption Monitoring System for Group Building Construction Based on Mobile Node. In: Fu, W., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 468. Springer, Cham. https://doi.org/10.1007/978-3-031-28787-9_44
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DOI: https://doi.org/10.1007/978-3-031-28787-9_44
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