
Preinstalled Computer Vision Software
Use the Intel® Distribution of OpenVINO™ toolkit for hardware acceleration of deep learning inference for computer vision applications.

Hardware Acceleration
Harness the performance of Intel®-based accelerators for deep learning inference with the CPU and GPU included in this kit.

Reduce Time to Field Trial
The included mountable aluminum chassis and camera are field ready with an operating temperature range of 0° C to 40° C.
Who Needs This Product
Information and operational technologists who:
- Are new to IoT commercial platforms and need a simple path without a steep learning curve
- Need a quicker path to deployment
Use Cases
- Face detection and analysis
- Retail audience analytics
- Pedestrian detection and analysis
- Traffic monitoring and license plate recognition
Brand Recognition and Inventory Management (video)
Personal Protective Equipment Analysis (video)
Reference Implementations
Build a Facial Recognition Access Application
Create a People Counter Application
Hardware
- UP Squared board with Intel Atom® X7-E3950 processor and 4 GB of RAM and 64 GB eMMC
- USB camera with a maximum resolution of 1920p x 1080p at 30 frames per second
- Power supply for the UP Squared board
- Aluminum enclosure
Preinstalled Software
- Ubuntu* 16.04 desktop
- Intel® Distribution of OpenVINO™ toolkit for Linux* version 2018 R1.2
- Intel® System Studio 2018 Community Edition with Eclipse* IDE
- Drivers for Intel® VTune™ Amplifier, Intel® Energy Profiler, Intel® Graphics Performance Analyzers
- MRAA and UPM I/O and sensor libraries for C++, Python*, Java*, and JavaScript*
Optional Add-ons

System Requirements
HDMI* or DisplayPort* compatible monitor
USB keyboard and mouse
Ethernet connection (for internet connectivity)
Dimensions (in chassis)
Height: 49mm
Width: 105mm
Depth: 100mm
System Board
Intel Atom x7-E3950 processor (1.6 GHz quad core, burst up to 2.0 GHz)
Integrated Intel HD Graphics 505 with 18 execution units
4 GB LPDDR4 system memory
64 GB eMMC
Available I/O Interfaces
GPIO
I2C
SPI
UART
PWM
i2s
HDMI and DisplayPort
Dual gigabit Ethernet ports
USB 3.0
Additional Accessories Available for Purchase
Expansion Slots
1 - SATA 3
1 - mini PCIe*
1 - M.2 2330
UP Squared AI Vision Development Kit | UP Squared* Grove* IoT Development Kit | |
---|---|---|
Processor | Intel Atom® x7-E3950 processor | Intel® Celeron® processor N3350 |
Target Usage | Computer vision | General purpose |
Works with OpenVINO™ toolkit | Yes | Yes, but with reduced performance due to lower CPU and GPU core count |
Included accessories | USB HD camera with mount | Grove interface board with 5 sensors |
Memory/eMMC | 4GB/64GB | 2GB/32GB (potential space limitations) |
Customize Your Up Squared for Production
Advance your prototype to the next stage through custom software and hardware offered by AAEON and Canonical.
- Explore the different UP Squared board configurations to fit your specific workload.
- Find out more about Customization Services for Hardware from AAEON.
- Learn more about Ubuntu Customization and Deployment from Canonical.