To ensure the sustainability of critical infrastructures, such as public infrastructure, dams, bridges, etc., a holistic monitoring approach is required. With regard to this, European Union (EU) and the Hellenic government are financially supporting a project for the multiparametric monitoring of the Enceladus Hellenic Supersite (EHS), entitled “PROION”. A building on the Patras University campus, a dam, and an active landslide within the EHS area constitute the three main case studies of the project and are being monitored using Remote Sensing (RS) and in-situ instrumentation. InSAR data, GNSS and micro-accelerometer measurements are collected and evaluated with reference to 3D point clouds, developed from TLS and UAV. In addition, Fuzzy Logic Networks (FLN) methods and Machine Learning (ML) algorithms are applied for the final control of the data and decision-making support. A web-based Geographic Information System (Web GIS) platform is designed and developed in order to concentrate and disseminate the diverse and multidimensional data and methodology outcomes of “PROIΟΝ”. Modern web architecture frameworks, and geo-visualization technologies (e.g., SaaS, React JS, Flask, WebGL, Mapbox GL JS, etc.) are combined into a robust Web GIS platform, providing an augmented end-user interaction and enhanced geospatial tools through a 4D web map environment. Furthermore, big data spatiotemporal analysis, geospatial data overlaying/fusion, and near real-time earthquake events feed are included, achieving the optimal monitoring of high-priority infrastructures.