Benefits of Edge processing
- Confidentiality: data is not sent to the cloud and is locally stored on the device or the equipment
- Cost reduction: latency and throughput of high-volume time-series asset data is significantly optimized. Reducing the amount of useless machine data sent and stored in the cloud leads to significant benefits, as it enables real-time distributed applications and eliminates the need for complex systems
- Lower latency: minimal delay in the repair of equipment is essential for assets which are mission-critical.
AI ecosystem for STM32 MCUs and MPUs
To easily implement Predictive Maintenance algorithms on MCU and MPU edge devices, STM32 Tools were enriched with the STM32Cube. AI ecosystem, extending STM32CubeMX software capabilities with the automatic conversion of pre-trained Neural Networks. STM32Cube. AI supportsing several deep learning frameworks and includes optimized libraries which can be used to implement AI algorithms in embedded applications level.
STMicroelectronics also provides a complete offer of microprocessors and optimized Power Management solutions for industrial gateways as key enablers of aggregated processing in the field. Software development kits and cloud applications for Edge and Cloud processing (starter kits) as well as AI studio tools, like STM32Cube. AI software and code examples, are included our function packs and solutions.
| Picture | Solution |
|---|---|
 | Vibration, ultrasound and environmental sensor nodes for condition monitoring with Wi-Fi and cellular connectivity to cloud applications SL-PREDMNT-S2C 批量生产 |
 | A Condition monitoring cloud gateway solution, using smart sensor nodes and edge processing SL-PREDMNT-E2C NRND |
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