Development Kit and Reference Design for Industrial AIoT Applications GRC Dev Board
Description
The GRC Dev Board is a development kit and reference design that simplifies prototyping and testing of advanced industrial AIoT applications such as Anomaly Detection and n-Class Classification for predictive maintenance.
High-performance speed is achieved due to the use of reservoir computing methods implemented in the GRC AI Module.
The GRC Dev Board allows
- Promptly testing ready-made, pre-configured neural network
- Checking the viability of ML algorithms in solving your particular tasks
- Selecting AI functionality which will suit best to your goals
- Developing SW, debugging and testing for your target device
The GRC Dev Board provides functionality for simple sensors connection, on-the-fly software development and debugging, i.e.
- Sensors management and control
- Data pre-processing
- Data formatting for their further processing in the GRC AI Module
- Data flow transfer onto the GRC AI Module
- GRC AI Module management and control
- GRC AI Module results output
- Data post-processing
- Results shown on OLED display and/or via LEDs
Functional Scheme
Interaction with GRC AI Module
The GRC Dev Board serves best for developing PoC, MVP, and prototypes. It communicates with GRC AI Module via API interfaces.
The work of the neural network created for the AI tasks is run on the MCU using input data gathered from sensors. The solution provides:
“Training” mode:
- With an operator
- Autonomously
- Performance speed less than 3 seconds
- No dataset and data mapping is required.
“Classification” mode:
- Up to 10 categories including anomaly
- Performance speed less than 2 seconds
GRC Dev Board Concept Design
GRC Dev Board Description
Features
GRC Dev Board is a multi-sensing module for implementing AI-driven solutions by adding Anomaly Detection and n-Class Classification functionality
Built around ESP32 C3 core system board possessing all appealing expansion, processing, computing and performance characteristics of the original MCU and even more
Processors:
Main processor: Tensilica Xtensa 32-bit LX7 microprocessor
- Cores: 2
- Clock frequency: up to 240 MHz
- Performance: up to 600 DMIPS
Easily-detachable GRC AI SW module, a tailored solution for AIoT tasks
Memory
- 384 KB ROM
- 512 KB SRAM
- 16 KB SRAM in RTC
- 16 MB of PSRAM
- 16 MB of SPI Flash
Connectivity: USB, UART to USB interface CP2102N
Rich choice of sensors:
- 2 ultra-compact, low-power, omnidirectional, digital MEMS microphone MP34DT06JTR (PDM microphones)
- A multi-chip module MPU-9250 (9-axis sensor: a gyroscope, an accelerometer, and a compass)
Modular architecture, expandable via on-board connectors:
- ESP32 USB port
- UART USB port
- Battery connector
- OLED Display port
- Arduino compatible extension port
Support of battery power supply with charge control and protection
Other Dev Board components:
- 3 RGB LEDs – SK6805
- 2 buttons: Reset and User/Boot
- Power and battery management
- OLED Display (optional)
COMPONENTS LIST
ESP32-S3-WROOM
GRC AI Module
GRC AI Digital MEMS microphone MP34DT06JTR
MPU-9250
Processors:
Recommended sensors
Condition monitoring
Predictive maintenance
Control Systems
Smart Home Systems
Security Systems
Technical Specification
Please refer to Developer’s Guide for detailed technical characteristics.
Perks of using GRC Dev Board
Saving time and resources at the development stage, as there is no need in
- Development of mathematical and statistical anomaly models
- Signal mapping and dataset preparation;
- Training model in the cloud
Reducing expenses for the end solution, as there is no need to spend money on
- Data transfer from a target device
- Storing large amounts of data
- Support of infrastructure for processing large data amounts
Development of autonomous solutions due to low power consumption * and no need in data transfer to a server.
Privacy and security are guaranteed as there is no need in transferring sensor signal from the target device to a server
Vast potential of developing flexible solutions configurable to particular hardware.
Ultra-low latency: Real-time applications