Smart Geotechnical Asset Management (SGAM) is an innovative framework integrating external systems via a cloud-based Software as a Service (SaaS) platform or API. It leverages advanced data-fusion algorithms and satellite Earth Observation (EO) technologies, such as A-DInSAR and PhotoMonitoring™, to enable a semi-automatic decision-making process for asset management and predictive maintenance. This approach significantly enhances the financial resilience and operational efficiency of structures and infrastructures by optimizing maintenance investments through sophisticated, data-driven insights. SGAM focuses on identifying, analyzing, and mitigating risks to assets by examining their interactions with local geological and environmental settings. It systematically evaluates both direct and potential interferences with geohazards, including landslides, floods, subsidence, and earthquake-induced effects, which could compromise asset integrity. By integrating vast quantities of archived and newly acquired EO data, SGAM provides Decision Makers with detailed and actionable insights, enabling them to define, prioritize, and schedule maintenance operations more effectively based on comprehensive asset vulnerability and loss scenario analyses. The EO data is further enriched and validated through field surveys as well as Geotechnical/Geomorphological Monitoring technologies sourced from extensive regional and global geodatabases. A core feature of SGAM is its adaptability and forward-looking design, which allows seamless integration of satellite data from different space missions, ensuring its long-term relevance, scalability, and technological advancement. AI-driven Process Automation solutions enhance its capabilities by performing first-level risk assessments, facilitating cost-effective, optimized prioritization of maintenance activities, and enabling decision-making underpinned by redundancy and precision. By seamlessly combining advanced satellite EO technologies, AI algorithms, and ground-based monitoring data, SGAM empowers organizations to proactively address structural and geotechnical risks. It not only reduces the likelihood of asset failure but also ensures sustainable, informed, and timely decision-making. Through prioritization of maintenance operations founded on comprehensive risk evaluations, SGAM is instrumental in enhancing infrastructure resilience, safety, and long-term sustainability amidst both current and future geohazards.
SGAM: Smart Geotechnical Asset Management / Valerio, Emanuela; Brunetti, Alessandro; Di Renzo, Maria Elena; Gaeta, Michele; Mazzanti, Paolo. - (2025). ( Living Planet Symposiumm Vienna (Austria) ).
SGAM: Smart Geotechnical Asset Management
Valerio Emanuela;Di Renzo Maria Elena
;Mazzanti Paolo
2025
Abstract
Smart Geotechnical Asset Management (SGAM) is an innovative framework integrating external systems via a cloud-based Software as a Service (SaaS) platform or API. It leverages advanced data-fusion algorithms and satellite Earth Observation (EO) technologies, such as A-DInSAR and PhotoMonitoring™, to enable a semi-automatic decision-making process for asset management and predictive maintenance. This approach significantly enhances the financial resilience and operational efficiency of structures and infrastructures by optimizing maintenance investments through sophisticated, data-driven insights. SGAM focuses on identifying, analyzing, and mitigating risks to assets by examining their interactions with local geological and environmental settings. It systematically evaluates both direct and potential interferences with geohazards, including landslides, floods, subsidence, and earthquake-induced effects, which could compromise asset integrity. By integrating vast quantities of archived and newly acquired EO data, SGAM provides Decision Makers with detailed and actionable insights, enabling them to define, prioritize, and schedule maintenance operations more effectively based on comprehensive asset vulnerability and loss scenario analyses. The EO data is further enriched and validated through field surveys as well as Geotechnical/Geomorphological Monitoring technologies sourced from extensive regional and global geodatabases. A core feature of SGAM is its adaptability and forward-looking design, which allows seamless integration of satellite data from different space missions, ensuring its long-term relevance, scalability, and technological advancement. AI-driven Process Automation solutions enhance its capabilities by performing first-level risk assessments, facilitating cost-effective, optimized prioritization of maintenance activities, and enabling decision-making underpinned by redundancy and precision. By seamlessly combining advanced satellite EO technologies, AI algorithms, and ground-based monitoring data, SGAM empowers organizations to proactively address structural and geotechnical risks. It not only reduces the likelihood of asset failure but also ensures sustainable, informed, and timely decision-making. Through prioritization of maintenance operations founded on comprehensive risk evaluations, SGAM is instrumental in enhancing infrastructure resilience, safety, and long-term sustainability amidst both current and future geohazards.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


