Gain predictive maintenance of public physical infrastructure

The maintenance of public physical infrastructures is a complex and often costly challenge, usually accompanied by urgency to resolve issues that arise. The maintenance of structural infrastructure is characterized by non-transparent data, unclear conditions, and scarce resources. Consequently, maintenance predictions are hard to achieve as the data needed for risk analysis and damage avoidance is not available.

Achieving the predictive maintenance of physical infrastructure such as bridges, buildings, roads, and street lighting, can be achieved with a modern, cloud-native software architecture that uses technologies such as machine learning (ML) and real-time analysis of data based on comprehensive monitoring to recommend actions to avoid defects and damage before they occur.

PROinfra is a ML model that recognizes patterns from a set of data, which can then be used to make predictions. Powered by geographic information system (GIS), a system for capturing, storing, checking, and displaying data related to positions on Earth’s surface, it uses modern technologies to facilitate the maintenance of public physical infrastructure.