Classify beers of differents brands and types using a gaz sensor Marjo versus the Machines.In a world, where the machines are about to take over the world, one woman rise to fight them off. One beer at a time!In this use case, we are using a multichannel gas sensor to act as a electronic
Predict heating and cooling load of a building In this dataset, they simulated 768 different building shapes. They made vary the following attributes: X1 Relative Compactness X2 Surface Area X3 Wall Area X4 Roof Area X5 Overall Height X6 Orientation X7 Glazing Area X8 Glazing Area Distribution Then they performed energy analysis
Predict the remaining useful life based on telemetry This dataset comes from a fleet of a hundred machines. Every 24h, telemetry sends volt, pressure and vibration data. We also have the age and model of the machine, if it has been maintained in the past, or if it reported errors in the last 24h.
Detect if your vacuum bag is empty or full (at different regimes) We will use a clamp meter to capture data. A classification library will be created using NanoEdge AI Studio. By measuring the electric current flowing into the vacuum cleaner, we will detect if it is empty or full. The NanoEge AI
Predict the stator temperature of an electric car with a thermal sensor The data comes from a permanent magnet synchronous motor on a test bench. The PMSM represents an electric car prototype and multiple sensors are present on the bench.Multiple driving cycles were performed, randomly varying speed and torque to imitate real world driving.The
Predict if your drill bit departed from a pre-selected trajectory Deviation from the pre-selected path can be a huge problem for oil drilling operations, from higher cost to legal issues. The causes of hole deviation is complex and depend on multiple factors. To try to predict such deviation, we will be using well logs.
This tutorial will guide you through the process of building a vibrational anomaly detector using NanoEdge AI Studio and deploying it to the SAMD21 development board. You'll be capturing accelerometer data using the IMU2 Click board and using NanoEdge AI Studio to train a library that can model the nominal behavior of the USB case
Predicting if the grid will be stable given a few features Determine if an electric grid is stable or not. We try to predict if the grid will be stable given a few relevant features such as nominal power produced and consumed or reaction time of participants. A classification library will be
Make equipment AI smart - Easily, quickly, affordably Product: Any instrument such as mechanical equipment, gearing, ATM, circuit breaker, pump… Problem: The aging of machines is virtually impossible to anticipate, leading to costly production stoppages. Solution: NanoEdge AI is loaded into an MCU controlling the mechanism to learn normal patterns of the
Learn and infer dynamically inside any arm Cortex-M MCU NanoEdge™ AI Studio will easily let you create a machine learning static library to embed your main program running on any ARM© Cortex© M microcontroller. When embedded in microcontrollers, it gives them the ability to locally