Now that the IoT is a reality, the next step is to leverage this connectivity and transform pieces of information into real problem solvers. One example is the ability to predict failures before they happen; failure prevention allows for reduced maintenance costs, flexibility on intervention time, and fewer emergencies to deal with. Furthermore, it is easy to picture how gathered data, when managed properly, can improve the way devices are used by reducing power consumption, thus becoming more environment-friendly and extending the product life overall. This is made possible by two elements: monitoring how objects are being used (sensors, user actions, failures, etc.) and modeling how and when these objects and components fail (machine learning, AI). This session will focus on how to achieve so-called predictive maintenance, describing various technologies and tools involved, as well as how Qt fits and helps in this space.