Industrial Predictive Maintenance

To address the Industry 4.0 initiative to make “Smart Factories”, Predictive Maintenance has been a key area where investment is made to monitor machines, pumps, motors, etc.

Sensor Use Cases

Here is a high level application for the monitoring of these machines where the HW components are part of a sensor module that is attached to the machine that is being monitored.


The sensor module has an MCU that is typically combined with BT/BLE or Wifi or other connectivity along with sensors that are ideal for detecting different performance issues or anomalies.

  • Accel/Gyro vibration sensors sense the movement of the machine and can detect when it is not operating correctly.
  • Acoustic Emission sensor is a high frequency microphone that can “listen” to a bearing falling apart.
  • Temp/Humidity sensors are used to sense the ambient surrounding.
  • A microphone can be used to “listen” to the machine and detect when an abnormal condition is happening.

Qeexo AutoML

One sensor data ML model doesn’t fit all machines as they are mounted on different surface (rubber, concrete, wood). Collecting data onsite and building models quickly and efficiently will allow each machine to have its own unique AI model that runs on the “endpoint” and “edge”. Qeexo AutoML is an end-to-end Platform that can create these unique models quickly and efficiently.


Industrial Structural Health Monitoring

As low power MCU and low power connectivity has become more prevalent, so has the growth of structural health monitoring. In Japan for example, there are many tremors and earthquakes regularly which are hurting the fatigue of bridges, railroad tracks, roads, and buildings.

Sensor Use Cases

The Japanese government is investing in putting these small sensor modules on the bridges, buildings, etc. to monitor the “health” of the structure.

These sensor modules would consist of high precision, low drift/bias accelerometers as well as a low power MCU and a low data bandwidth connectivity technology like LoRa.

Qeexo AutoML

These accelerometer ML algorithms will require machine learning, that is easily delivered by the Qeexo AutoML Platform.

Railroad Tracks

Smart Home Appliances

In smart home appliances, the microphone has proven to be an important sensor to make these devices matter.

Audio Use Cases

Some use cases for a microphone that can benefit smart home appliances include:

  • A smart stove top detects when a frying pan is “burning” or “over frying” by listening to the sizzling sound and turn off the heat when needed.
  • A smart stove top would also detect when the water is boiling too high and overflowing by just the sound signature.
  • For a smart washer & dryer using an accelerometer, it would be able to detect when there is a load imbalance so the machine can adjust itself automatically instead of stopping and sounding an alarm. It can also detect when the motor is not performing optimally by the vibration signature and send a message to call a maintenance person.

Qeexo AutoML

All these uses cases need machine learning algorithms to make sense of the sensor data. Qeexo AutoML can automate this process for OEMs.

Stove Top
Coffee Machine

Consumer/IoT Wearable Devices

Sensor Use Cases

Qeexo AutoML can automate the creation of machine learning sensor algorithms for the following wearable and IoT applications:

  • The wrist worn wearable devices, sensors are used for the Bring-to-See gesture as well as activity classification (i.e. walk, run, bike) as well as contextual awareness (are you inside a car or in an elevator).
  • Smart farming is a big trend nowadays and tracking your cattle’s estrous cycle and activities is vital in maximizing the profit for your animals.
  • More and more consumers are spending money on tracking their pets’ activities to keep them happier, well-rounded and healthy.
  • As the world’s population ages, many countries like Japan and Korea are investing heavily in tracking the activities and health of their elderly whether at home with a smart watch or medallion worn around a neck or in an assisted living facility.

Qeexo AutoML

All of these applications have the same architecture in common: An MCU with connectivity and sensors. Qeexo AutoML can create the ML algorithms quickly and efficiently that can run on these small battery powered devices.

Pet Tracking
Elderly Tracking
Cattle Tracking
Gait Analysis

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