iModGATE-AI uses basic ModBerry 500’s resources, such as industrial grade custom motherboard, with a variety of interfaces and Raspberry Pi Compute Module 3+/4 processor module. On top of that iModGATE-AI is designed to work as an AI-aided environment monitor, thanks to Analog Inputs with up to 24-bit resolution to support most of market sensors, such as tensometric beams.
iModGATE-AI has been designed for purposes of Machine Learning and failure prediction, then it is obvious that AI TPU module is on board. The device works seamlessly with Coral from Google via M.2 slot and with the use of programmable 9-axis MotionTracking module offers the possibility to monitor and analyze conditions on site and prevent accidents and system failures on-site.
iModGATE-AI main features and characteristics
For many possible applications, the iModGATE-AI device has been equipped with ultimate set of resources to fulfill almost every project on the market:
- Raspberry Pi Compute Module 4 with up to 32GB eMMC
- Ethernet 1Gbps, USB2.0, HDMI, 2×16 pin block terminal
- Coral from Google AI module (Coral Edge TPU)
- Advanced Analog Inputs (up to 24bit) with tensometric input support
- 9-axis MotionTracking module:
- 3-Axis Gyroscope with Programmable FSR
- 3-Axis Accelerometer with Programmable FSR
- 3-Axis Compass (Magnetometer)
- RTC with battery on-board
Machine learning with 9-axis MotionTracking module
Utilized 9-axis MotionTracking module is ideally suited for IoT applications. DMP (Digital Motion Processor) offloads traffic processing algorithm calculations from the host CPU – Raspberry Pi Compute Module, to improve system power efficiency.
The gyroscope has a programmable scale range of ±250 ~ ± 2000 dps. The accelerometers have a range of ±2g ~ ±16g, programmable by the user. The initial sensitivity of both sensors reduces the requirements for calibration of the production line. Other key features include on-chip 16-bit ADCs, programmable digital filters, a temperature sensor embedded onto chip and programmable interrupts.
Possible system adaptations and applications
iModGATE-AI can be programmed to alert with certain rules, to prevent failures and enforce rapid maintenance. Data analysed from the 9-axis MotionTracking module serve as a resource for predictive maintenance of the system. Thanks to Coral AI module and machine learning introduced to the end-point of the installation can minimise downtime and repair costs of machines, therefore maximising the performance.
Fields of application:
- wind farm monitoring
- Smart Building & Cities
- conveyor systems
- and many more
Due to pandemic and global electronics market shortages the availability is dependent on supply of Raspberry Pi Compute Modules, Coral from Google, 9-axis module and optional wireless modems.