Thursday, July 18, 2024

Energy-Efficient Autonomous Inertial Measurement Unit

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The sensor technology targets vibration sensing and motion tracking in industrial and robotics applications, enhancing precision and energy efficiency.


The ISM330BX 6-axis inertial measurement unit (IMU) from STMicroelectronics incorporates edge-AI processing, an analogue sensor expansion hub, and ST’s Qvar technology for sensing electric charge variations. The company claims the IMU ensures product longevity, making it ideal for energy-efficient industrial sensing and motion-tracking applications.

Equipped with a 3-axis gyroscope and a 3-axis accelerometer, the IMU offers a low-noise architecture and a bandwidth of up to 2kHz, which is optimal for vibration detection in condition monitoring of machine tools. It is also well-suited for various applications, including industrial and domestic robots, automated guided vehicles (AGVs), intelligent appliances, and motion trackers. The IMU targets a broad range of users, including industrial automation manufacturers, robotics companies, smart appliance and safety equipment producers, and innovators in sensor technologies. 

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The device integrates ST’s edge-processing engine, combining a machine-learning core (MLC) with AI algorithms and a finite state machine (FSM), significantly reducing the host processor’s workload and conserving energy. The embedded Sensor Fusion Low-Power (SFLP) algorithm aids in 3D orientation tracking, enhancing energy efficiency in robotics and smart safety helmets. Its adaptive self-configuration feature allows the sensor to adjust its settings in real-time for optimal performance and energy usage.

The IMU’s autonomous functionalities reduce data transmission needs between the IMU and the host system, thus decreasing latency and power consumption. The integrated analogue hub directly connects external analogue sensors to the edge-processing engine for data filtering and AI inference. This enables more energy-efficient system integration and the development of innovative industrial sensors and battery-powered smart devices for upgrading existing industrial assets towards Industry 5.0.

Additionally, the built-in Qvar electric charge variation detector enhances system integration and energy efficiency by enabling functionalities such as touch and proximity detection or advanced features like water leak sensing.

For more information, click here.

Nidhi Agarwal
Nidhi Agarwal
Nidhi Agarwal is a journalist at EFY. She is an Electronics and Communication Engineer with over five years of academic experience. Her expertise lies in working with development boards and IoT cloud. She enjoys writing as it enables her to share her knowledge and insights related to electronics, with like-minded techies.


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