Qeexo AutoML

Qeexo

TRIAL

Concept Videos

  • Qeexo AutoML

    Qeexo AutoML is Qeexo’s one-click, fully-automated platform that allows customers to leverage sensor data to rapidly build machine learning solutions for highly constrained environments with applications in mobile, IoT, wearables, automotive, and more.
    Delivering high performance, solutions built with Qeexo AutoML are optimized to have ultra-low latency, ultra-low power consumption, and an incredibly small memory footprint. As billions of sensors collect data on every device imaginable, Qeexo can equip them with machine learning to discover knowledge, make predictions, and generate actionable insights.
    For more information, please visit: automl.qeexo.com.

  • Qeexo Embedded Machine Learning

    Qeexo AutoML uses sensor data to automatically build machine learning models that generate actionable insights at the Edge. It can be used for anomaly detection and predictive maintenance in a factory setting.
    For more information, please visit: automl.qeexo.com.

Demo Videos

  • Live Demo: Automating Machine Learning for Embedded Devices

    Qeexo AutoML is Qeexo’s one-click, fully-automated platform that allows customers to leverage sensor data to rapidly build machine learning solutions for highly constrained environments with applications in mobile, IoT, wearables, automotive, and more.
    Delivering high performance, solutions built with Qeexo AutoML are optimized to have ultra-low latency, ultra-low power consumption, and an incredibly small memory footprint. As billions of sensors collect data on every device imaginable, Qeexo can equip them with machine learning to discover knowledge, make predictions, and generate actionable insights.
    For more information, please visit: automl.qeexo.com.

  • Anomaly Detection Part 1: Data Collection, Model Training & Deployment

    In this video, we apply Qeexo AutoML to an Anomaly Detection use case. Part 1 shows the data collection and visualization process, as well as how the machine learning models are trained and deployed.
    To learn more, please visit: automl.qeexo.com.

  • Anomaly Detection Part 2: Simple Imbalance

    In this video, we apply Qeexo AutoML to an Anomaly Detection use case. Part 2 puts the machine learning model we built in Part 1 to the test, detecting system imbalances.
    To learn more, please visit: automl.qeexo.com.

  • Anomaly Detection Part 3: Eccentric Rotor

    In this video, we apply Qeexo AutoML to an Anomaly Detection use case. Part 3 puts the machine learning model we built in Part 1 to the test, detecting an eccentric rotor.
    To learn more, please visit: automl.qeexo.com.

  • Anomaly Detection Part 4: Bent Rotor Shaft

    In this video, we apply Qeexo AutoML to an Anomaly Detection use case. Part 4 puts the machine learning model we built in Part 1 to the test, detecting a bent shaft.
    To learn more, please visit: automl.qeexo.com.

Application Videos

  • Environment-Aware Countertop

    Using Qeexo AutoML with sensor data, we automatically built machine learning models to make our kitchen counter smart. Equipped with machine learning, the counter is able to tell what appliances are running on it at a given time. The machine learning inference is done at the Edge without requiring connectivity.
    For more information, please visit: automl.qeexo.com.

  • Intelligent Shipping

    Using Qeexo AutoML with sensor data, we automatically built machine learning models to develop a smart shipping box that can track what’s happening to it during its entire journey. The machine learning inference is done at the Edge without requiring connectivity.
    For more information, please visit: automl.qeexo.com.

  • Predictive Maintenance

    Using Qeexo AutoML with sensor data, here we demonstrate anomaly detection (used for predictive maintenance) in our fan system. The machine learning inference is done at the Edge without requiring connectivity.
    For more information, please visit: automl.qeexo.com.

  • Interactive Wall

    Using Qeexo AutoML with sensor data, we automatically built machine learning models to control lighting. The machine learning inference is done at the Edge without requiring connectivity.
    For more information, please visit: automl.qeexo.com.

  • Qeexo FingerSense

    This video provides an overview of FingerSense, Qeexo's touch interaction platform. For more information, please visit: http://www.qeexo.com/.

  • Qeexo EarSense

    EarSense is Qeexo’s software-only replacement for the traditional hardware proximity sensor, allowing for true bezel-less and notch-less design.

  • Qeexo TouchTools - Tablet

    TouchTools allows users to instantly summon and manipulate virtual tools with ease and precision. Editing, creating, working, and collaborating on touch surfaces have never been so intuitive.

  • Qeexo TouchTools - Automotive

    TouchTools can significantly reduce the need for precise targeting of small buttons, creating a better UX and a safer driving environment. Drivers can now keep their eyes on the road while changing stations.