- A probabilistic-based all-weather, round-the-clock, multi-tiered landslide warning system and green risk mitigation measures;
- An advanced meteorology-based AI system for predicting extreme weather conditions that would affect the stability of slopes in HK;
- A unique multi-source stereoscopic monitoring system that applies deep learning analysis to characterize slope failure mechanisms and vegetation effects using data obtained from remote sensing satellites, unmanned aerial vehicles (UAVs) and terrestrial sensors;
- A dynamic data-driven stress-testing method using AI techniques for managing landslide risks and enhancing community resilience;
- MOOCs to educate (a) the general public about slope safety and (b) practitioners about scientific advancements and technologies in a stimulating, real-time learning environment;
- Multi-scale, world-class physical testing facilities and an advanced constitutive model incorporating the multi-phase material point method (MPM) for simulating the effects of cyclic drying and wetting and heating and cooling on slope stability.