Machine Learning in Telemetry

Machine learning in telemetry involves using algorithms to analyze large amounts of data collected from remote sensors and devices. These algorithms identify patterns and trends without being explicitly programmed for specific tasks. In practical terms, this helps predict equipment failures, optimize performance, or detect anomalies in real-time. By learning from historical data, machine learning makes telemetry systems smarter, enabling proactive maintenance and better decision-making, ultimately improving system reliability and efficiency.