This study presents the case of a landslide triggered by a high groundwater level caused by several days of continuous rainfall in the northeastern region of Taiwan. The slope where this landslide occurred consists of closely jointed and weathered bedrock. By means of finite element limit analysis and the Hoek–Brown failure criterion, this study performed a slope failure simulation similar to the actual landslide and deduced the reasonable value range for the combination of key Hoek–Brown failure criterion parameters through back analyses. The results indicate that the key parameters affecting the bedrock’s slope stability were the geological strength index (GSI) and the disturbance factor (D), whereas the effects of the unconfined compressive strength (σ_ci) were less significant. The results of the back analysis reveal that the suitable D-value range and GSI of closely jointed and weathered sandstone in the northeastern region of Taiwan are 0.8 to 0.9 and 20 to 30, respectively. These back-analyzed value ranges can serve as a reference for broader applications in the preliminary stability analysis of similar rock slopes where it is difficult to perform in situ investigation.

Using circulating groundwater to cool air-conditioning is not new in high latitude regions but difficult in subtropical areas. Different from only using fans to remove the heat from indoor air for drier air in the high latitude region, the latent heat inside the humid air in subtropical areas makes the operation more difficult. Latent heat inside the humid air must remove away by air-conditioning including compressor and fan for cooling indoor air, which means more electrical power is required for the operation. To save total electrical power for the air-conditioning system is the main goal of this study. To use the advantage of groundwater with lower temperature to lower down the work of compressor, this research compared two ways, close/open types of water/groundwater circulation, both using groundwater to remove the heat generated by a 15RT (45 kW) air-conditioning. Full-scale tests and simulations were performed in this study to evaluate the efficiency of transferring the heat produced by air-conditioning systems to stably flowing groundwater in a grave stratum under Taipei Basin. With a closed circulating cooling water system, this study found that a 15RT air conditioner could only operate continuously for 4 h before it had to be shut down due to overheating. Additionally, groundwater must carry the heat away within the following 20 h. In changing the closed circulating water system to an open one, a system that uses a circulatory method to extract groundwater upwards and conduct heat exchange with an air conditioning system can enable the continuous operation of such a system with the same heat production condition. Numerical simulations for the heat dissipation behavior of two circulatory systems were performed herein. The results verified the aforementioned phenomena observed from both tests. The result showed both systems can provide air-conditioning working well. The total electrical power for a 15RT air-conditioning in sub-tropical areas can be reduced by 22% using circulating groundwater. Considering the system optimization, the total power consumption can be reduced by about 28%.

Monitoring slope stability in mountainous regions is often constrained by limited power supply and communication capacity. Under such conditions, low-power wireless transmission technologies, such as LoRa and NB-IoT, become indispensable for ensuring reliable data delivery in long-term monitoring systems. Real-time image monitoring of slope deformation, combined with automated image recognition and early-warning mechanisms, has emerged as a rapidly advancing approach in geotechnical hazard mitigation. These technologies enable continuous observation of slope variability and provide timely alerts that can significantly reduce the risk of catastrophic slope failures. However, the enormous volume of image data generated by continuous monitoring poses substantial challenges for transmission efficiency, data storage, and timely analysis. To address these issues, edge computing is increasingly employed at the monitoring site. By processing data locally, edge devices can filter and preserve only critical events before transmitting them to central servers for further recognition and decision-making. This strategy not only accelerates the early-warning process but also reduces false alarms, thereby enhancing the reliability of hazard detection. Furthermore, integrating edge computing with low-power wireless transmission creates a synergistic framework that balances energy efficiency, communication constraints, and analytical accuracy. Such integration is particularly valuable in remote or resource-limited environments where conventional high-bandwidth communication is impractical. The proposed approach highlights the importance of combining advanced sensing technologies with intelligent data management to achieve robust slope monitoring systems. Ultimately, this framework contributes to improving disaster preparedness, reducing misjudgment in early-warning systems, and supporting sustainable infrastructure development in mountainous regions.