Most cities react to the maintenance of infrastructure such as roads, bridges, and street lighting issues once a fault has already occurred. This can be expensive and disruptive, especially in cities grappling with aging infrastructure.
Goals and Objectives
Predictive maintenance enables a proactive approach, using sensors to monitor the condition of infrastructures such as roads, bridges, and lighting and applying data analytics to predict the required maintenance.
Vibration, pressure, humidity, pressure and temperature sensors, cloud-based platform, digital twins, GIS, and predictive analytics including through AI and ML
Use Case Summary
Predictive infrastructure maintenance includes instrumenting a city’s critical infrastructure with sensors and using the data generated, along with cloud-based platforms and analytics, to respond to and predict future faults. Digital twin solutions of infrastructure are increasingly being developed to support predictive maintenance.