Project 4 essentially concerns the development of technologies for the ground and environment monitoring, with particular reference to natural hazards. Natural hazards are physical phenomena caused by atmospheric, water or geologic processes that threaten people, property or the environment. They can occur within a short or long period of time. In the case of the RAISE Project, it is proposed to develop an intelligent monitoring system for geo-hydrological risk forecasting, including landslides, extreme rainfall, extreme winds and other weather and climate variables of interest. In detail, the products are aimed at monitoring meteorological, coastal and slope (landslide) hazards, also in the light of global change. The forecast products (4.1) will be produced at least at hourly temporal resolution and further processed through AI techniques aiming at further improving forecast skills for highly localized phenomena (heavy rainfall, hailstorms, severe wind etc) via hybridization or post-processing with machine learning and deep learning techniques. The processing of bathymetric data obtained by analysing images from satellites, planes or drones and the development of mathematical models that study the morphodynamic stability of coastal areas will allow the creation of a system for assessing the risk and vulnerability of these environments to climate change (4.2). With regard to ground stability, it is proposed SLHIM (SLope Health Integrated Monitoring), an intelligent, integrated system for monitoring slopes affected by landslides and assessing susceptibility to rainfall-induced landslides. It is implemented integrating a hydrological-geotechnical model, fed by sensor data, and a statistical analysis of rainfall thresholds. It includes a sensor prototype developed to continuously record the field variation of pore water capillary tensions caused by the interaction between the ground and the atmosphere to assess the slope stability. Data managed on platforms for early warning sharing (RL4).