Measure magnetic fields in micro teslas using the device's magnetometer. Detect ferromagnetic materials like iron, magnets, and metals. Adjust feedback level for vibration alerts. Visualize field strength with a graph.
Capture and document utility pole data with GPS-based location marking. Input and organize pole details, including dimensions and equipment. Generate reports and export data for analysis.
Collects sample data using Near-Infrared Spectroscopy to authenticate raw materials. It sends data to a server for machine learning model training. Users can predict material quality based on trained models.
Tune PI/PID controllers using experimental data. Analyze process loop data to determine optimal controller settings. Adjust proportional, integral, and derivative parameters. Export tuning results for use in industrial systems.
