STMicroelectronics STEVAL-BFA001V1B - predictive maintenance kit with sensors and IO-Link capability
Designed for condition monitoring and predictive maintenance, the smart and compact STEVAL-BFA001V1B industrial reference design kit consists of a 3D digital accelerometer, several environmental and acoustic MEMS sensors, and offers IO-Link capability. Hence it is ideally suited for industrial applications like monitoring motors, pumps and fans.
- 32-bit ARM® Cortex®-M4 core for signal processing and analysis (STM32F469AI)
- iNEMO 6DoF (ISM330DLC)
- Absolute digital pressure sensor (LPS22HB)
- Relative humidity and temperature sensors (HTS221)
- Digital microphone sensors (MP34DT05-A)
- IO-Link PHY device (L6362A)
How AI accelerates multi-camera solutions
From passive video capturing devices to fully autonomous vision systems, recent advances in embedded vision triggered an evolution. Self-driving cars, drones, or autonomous guided robots require real-time parallel processing, low-latency, and in some cases low current consumption.
Building autonomous vision systems grows increasingly challenging, requiring multi-disciplinary expertise in optics, image sensors, computer vision and deep learning. Selecting the right development platform and design methodology is crucial for a successful implementation. Let us introduce you to a solution - the multi-camera methodology.
Multiple camera modules provide surround view. Sensor fusion improves the overall vision system, while artificial intelligence and machine learning drive tremendous improvements for recognition and learning tasks in autonomous vision systems.