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AIoT TH

Machine Monitoring

See every machine before someone reports it

The gateway reads status from the PLC or digital inputs, and values from sensors on the machine, and sends them to the cloud — so you see which machine is running, which has stopped, and which value is starting to drift.

Common problems

  • You only learn when and how long a machine stopped once someone reports it
  • Downtime and OEE figures come from spreadsheets filled in after the fact
  • A machine starts running hot, vibrating or drawing more current and nobody sees the trend

What we measure

Values read from your equipment

Read through the gateway, shown on the dashboard, with history charts.

  • Run / stop status
  • Cycle count
  • Temperature
  • Motor current
  • Vibration

Calculated indicators

Coming soon

These indicators are in development and will be enabled step by step. You can preview them in the demo.

  • Runtime
  • Downtime
  • Availability
  • OEE

Data path

From shop-floor equipment to dashboards and alerts.

  1. PLC / Sensor

    The machine's PLC or added sensors

  2. Modbus / DI

    Modbus RTU / TCP or digital inputs

  3. AIoT Gateway

    Reads values; buffers when the connection drops

  4. 4G

    Dual SIM or site LAN, encrypted with TLS

  5. AIoT TH Cloud

    Time-series storage, isolated per organization

  6. Dashboard / Alerts

    On the web; alerts via LINE and email

What you get today

Available as soon as the gateway is installed.

  • Dashboards

    Latest values and charts for every data point, on desktop and mobile.

  • History

    Detailed data for 30 days on every package; longer history is kept as summarised data, by package.

  • Threshold alerts

    Set a high / low limit per data point. When a value goes out of range, you are alerted via LINE and email.

  • Offline alerts

    Get alerted when a gateway or device stops sending data — no need to wait for someone to notice.

AI Insights

Coming soon

AI capabilities are on our roadmap. They are not available yet.

  • Anomaly detection based on each data point's usual pattern
  • An AI-written daily summary report
  • An AI assistant that answers questions from your data, citing the actual readings

Example: surface vibration or temperature trends that drift from that machine's usual behaviour.

See an example, or talk to our team

The demo uses simulated data from a sample plant. Our team can assess your actual equipment and site.