The expansion project of the West New Territories landfill has complex geology and a large site area, involving multi-stage blasting operations and slope excavation. Construction top+180mPD to final formation+10mPD. The energy generated by explosive blasting of rocks has a significant impact on sensitive receptors. At the same time, the project involves a large amount of earthwork development, resulting in various types of multi-level slopes such as soil slopes, rock slopes, rock slopes, reinforced earth retaining (RE) walls, and temporary slopes for transportation operations. Real time monitoring and control of slope safety status is a challenge for this project.

This project addresses the significant need for expansion of numerous high and steep slopes in Hong Kong. Guided by the safety of high slopes, it utilizes advanced technologies such as the IoT, Big Data, cloud computing, image recognition, AI, and 5G to build a multi-source monitoring network for high slope safety perception. It conducts multi-source heterogeneous data fusion analysis, establishes a high slope deformation prediction and early warning model, develops a remote intelligent monitoring and early warning system for landslide unbalanced thrust, and creates an IoT platform and intelligent monitoring system for high slopes. This enables early identification, monitoring, early warning, prediction, and intelligent management of landfill slope hazards, enhancing safety risk control and accident prevention capabilities, and improving the management efficiency and safety level of the project.

Based on the high slope of the West New Territories Landfill Expansion Project, this project reveals the feedback mechanism between the slope, soil, and structure during high slope construction. It establishes a digital and intelligent risk control system and emergency response platform for high slopes, enabling the identification, early warning, and management of engineering risks in landfill high slope expansion projects. This improves the safety and intelligent management of high slope expansion projects, reduces construction interference with existing structures, and mitigates damage caused by uneven settlement and secondary landslides. Real-time monitoring and early warning systems promptly detect and address precursory information of slope instability, effectively preventing slope instability disasters. Based on multi-source monitoring data and evolutionary law research results, a more scientific and reasonable slope stability analysis method and early warning model are proposed. This can provide theoretical and technical references for risk management and emergency response in similar high slope expansion projects, promoting the application and industrialization of related technologies.