Trusselsintel

Trusselsintel is a term used to describe an integrated system concept that merges truss-based structural elements with intelligent sensing, data processing, and autonomous decision-making to monitor and manage structural health in real time. It appears in civil engineering, architecture, and aerospace contexts where truss frameworks predominate.

Origin and scope: The term emerged in scholarly discussions of smart structural systems in the 2010s. It is not a single standard framework; rather it denotes a family of approaches that embed sensors in truss members, deploy networked communications, and apply machine learning or edge computing to interpret data and guide maintenance.

Design and components: Typical architectures include sensor-equipped truss members (strain gauges, accelerometers, temperature, corrosion sensors), wireless or wired networks, edge processing nodes, and a centralized analytics platform. Digital twins and predictive maintenance models are often used to translate sensor data into actionable insights.

Applications and benefits: Trusselsintel concepts target bridges, high-rise frames, towers, roofs, and aerospace trusses. Benefits include real-time condition monitoring, improved load assessment, early fault detection, and optimized maintenance planning, which can extend service life and reduce downtime.

Challenges and outlook: Challenges include sensor durability and power management, data management, cybersecurity, cost, and the lack of universal standards. Research continues to integrate trusselsintel with BIM and digital twins and to explore scalable learning approaches across infrastructure networks.