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State-of-the-art neural networks and embedded sensors are being used to accurately predict potential maintenance issues with equipment used in a variety of industrial, manufacturing, consumer, automotive and other applications. You can leverage the Internet of Things (IoT) and our combination of solutions to monitor and detect wear and tear and operational anomalies that might be affecting the performance of your product while also implementing smart control to manage load and reduce the amount of wasted power. Predictive maintenance reduces downtime and repair costs while also extending equipment life and ensuring output quality.

We have partnered with industry-leading software solution providers to offer a complete predictive maintenance solution that uses multiple sensors and advanced Artificial Intelligence/Machine Learning (AI/ML) capabilities and features: 

  • Highly accurate detection of issues and with fewer false positive triggers
  • Easy-to-use Graphical User Interface (GUI) that eliminates the need for expertise in ML or training neural networks

Which Partner Solution Is Best for Your Predictive Maintenance Design?


If you are looking for ready-to-use solutions, Cartesiam offers GUI-based selection and implementation of advanced ML solutions for variety of sensors and devices.

Edge Impulse

If you have in-house skills to implement ML neural networks, Edge Impulse offers a state-of-the-art software kit and developer friendly environment that make it easy to get started.

Find Products for Your Design

We offer a diverse portfolio of products that can help you create a closed-loop, self-sustained predictive maintenance system, including 32-bit microcontrollers (MCUs), advanced motor control and drive solutions and thermal and power management devices. Our portfolio of low-power and low-cost wireless connectivity solutions include products that support LoRa®, Zigbee® and Bluetooth® technologies.