7. Technologies and data used in predictive maintenance

Since the 1950s, the technologies used for predictive maintenance have evolved with industry. In Industry 3.0, they relied on simple wired sensors and static thresholds based on classical models. Industry 4.0 introduced IoT, AI and cloud computing, enabling real-time data collection and adaptive predictive models. For almost a decade, Industry 5.0 has been taking up these technologies, putting people at the center of decision-making, with a resilient and sustainable approach. This section presents the characteristics of smart sensors and IoT, as well as an inventory of sensors and key data for predictive maintenance.