Sony’s multicore microcontroller technology with global LTE connectivity
Ideal for professional use cases on the edge
The unique combination of solid computing performance and advanced power efficiency makes Spresense ideal for edge computing. Spresense is featured in applications where there is a need for sensor analysis, machine learning, image processing and data filtering in which other microcontroller-based alternatives fall short.
- Logistics and transport
- Automatic quality inspection
- Predictive maintenance
- Wildlife monitoring
- Cell tower remote inspection
- Industrial connectivity
- Gesture recognition
- AI camera applications
- Sound diagnostics
- Home automation
- Edge computing
- FFT calculations
- Robotics and drone control
- GPS tracking
- Remote monitoring
- Image processing
- Real-time sensor analysis
- Hi-res audio solutions
Develop with Spresense
Spresense is open source and comes with full documentation, tutorials and sample projects.
- C/C++ based Spresense SDK
- NuttX real-time OS (POSIX compliant)
- Multicore application support
- Optional add-on boards (BLE, Wi-Fi, sensors etc)
- Arduino IDE support for quick prototyping
- Support for TensorFlow, NNC and Edge Impulse for professional machine learning development
TensorFlow from Google is one of the leading frameworks for machine learning on Spresense.
Get started with AI on Spresense in 10 minutes using the powerful machine learning tool by Edge Impulse.
Neural Network Libraries by Sony is a deep learning framework intended for research, development and production.
Powered by Sony's microcontroller technology
At the heart of the Spresense board, the Sony's CXD5602 microcontroller runs 6 ARM Cortex-M4F cores with a clock speed of up to 156MHz and has an integrated GPS. Thanks to the FD-SOI (Fully Depleted Silicon On Insulator) production process, the CXD5602 chip is very power efficient which enables battery dependent use cases.
Contact us if you have any questions or need specific information to get started with Spresense development.