Reduces power consumption with neural binary trees running directly where data are generated
The first industrial-grade IMU embedding Machine Learning Core (MLC), the ISM330DHCX offers a new revolutionary feature able to run neural binary trees inside the sensor, while keeping the main application processor in sleep mode.
Key features of ISM330DHCX
- 3D accelerometer with selectable full scale: ±2/±4/±8/±16 g
- 3D gyroscope with extended selectable full scale: ±125/±250/±500/±1000/±2000/±4000 dps
- Extended temperature range from -40 to +105 °C
- SPI/I²C serial interface
- Auxiliary SPI serial interface for data output of gyroscope and accelerometer (OIS and other stabilization applications)
- Sensor hub feature to efficiently collect data from additional external sensors
- Embedded smart FIFO up to 9 kbytes
- Programmable Finite State Machine to process data from accelerometer, gyroscope, and external sensors
- Machine Learning Core
- Embedded pedometer, step detector and counter for healthcare applications
- Analog supply voltage: 1.71 V to 3.6 V
- Embedded temperature sensor
- ECOPACK, RoHS and Green compliant
Application examples
Asset tracking 
Factory automation 
Home and professional appliances 
Industrial power and tools How to test & prototype with ISM330DHCX
Choose a development kit to start testing the capabilities and features of ISM330DHCX:
iNEMO inertial module evaluation kit based on ISM330DHCX
Evaluation kit includes a main board embedding the ISM330DHCX 3D accelerometer and 3D gyroscope sensor in addition to an adapter board for use with ST's ready-to-use MEMS motherboard (STEVAL-MKI109V3) development platform.
ISM330DHCX adapter board for a standard DIL24 socket
Designed to facilitate the evaluation of ISM330DHCX IMUs, the adapter board offers an effective solution for fast system prototyping directly within the user’s own application.
STWIN SensorTile Wireless Industrial Node development kit and reference design
Built to simplify the prototyping and testing of advanced industrial IoT applications including condition monitoring and predictive maintenance, this multi-sensing wireless platform benefits from a rich set of software packages and optimized firmware libraries, as well as a cloud dashboard application, all provided to help speed up design cycles for end-to-end solutions.
Predictive maintenance using AI at the edge in MEMS sensors
Webinar summary
- Condition monitoring at the edge
- ST Sensors and ecosystem for smart industry
- Edge AI: machine learning in ISM330DHCX
- Practical use case: fan rack condition monitoring with MLC
