Abstract
In recent years, with the propose of balanced development goal among the eastern, central, and western regions in China, the Chinese government has carried out a series of transportation infrastructure projects in the complex terrain areas, such as the central and western regions. The infrastructure construction in the western mountainous areas would produce a large number of spoil, which is prone to landslides, posing threats to the lives and property safety of local residents, as well as the damage to the local vegetation and water pollution. In order to solve the situation efficiently, this paper would construct a framework of spoil yard operational monitoring and risk early warning system. Combined with national standards and relevant documents, indicators and corresponding standards are designed for the data acquisition system. Then, the author selects the sensors as data collection device for getting first-hand data and a transmission mechanism is built with Beidou satellite navigation and positioning system (BDS). Furthermore, the data processing system has adopted big data technology and hierarchical analysis. Additionally, this paper synthesizes the evaluation results based on weighted average principle and fuzzy comprehensive evaluation method, with the BP neural network algorithm applied to modify and optimize the prediction model. Based on above, WebGIS and 3D modeling techniques are used to exhibit the security status of the spoil yards. The contributions of this paper are mainly to propose the practical system which could accurately monitor the safety condition in real time and suit for early warning. It is beneficial for decision-makers to conduct post-disaster management, summarize the causes of risk accidents, and improve the management efficiency of subsequent spoil yards.
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Ma, A., Lin, J., Li, Y. (2022). The Management Mechanism Design of Operational Monitoring and Risk Early Warning for Large-Scale Spoil Yard: Based on Integration of Beidou Navigation Satellite System and Big Data Technologies. In: Guo, H., Fang, D., Lu, W., Peng, Y. (eds) Proceedings of the 26th International Symposium on Advancement of Construction Management and Real Estate. CRIOCM 2021. Lecture Notes in Operations Research. Springer, Singapore. https://doi.org/10.1007/978-981-19-5256-2_56
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