Hands-On Deep Learning for IoT

Predictive maintenance for IoT

With advances in real-time data capture and streaming architecture, it is now possible to have real-time data monitoring, where an organization can gain real-time insight into individual components and all processes. Monitoring still requires active involvement and quick responses—for example, an oil well sensor that is indicating increased temperature or volume or a network traffic for bot-net activity or insider threats.

Let's consider a real-world example called equipment failures in industrial engineering, which is always considered a costly issue. Conducting preventative maintenance at regular intervals has always been the conventional strategy. Consequently, the schedules tend to be very unadventurous, ...