Introducing the ODROID-M1S Kit: Empowering Your Embedded Systems

The ODROID-M1S Kit, meticulously developed during the summer of 2023, is poised to meet the evolving demands of the market. Designed as a comprehensive solution, this kit equips you with essential components for building efficient and sustainable embedded systems.

Kit Contents:

1. Odroid M1S: The heart of the kit, the Odroid M1S, boasts several enhancements over its predecessor. Notably, it is 20% thinner, resulting in a sleeker profile. Additionally, we’ve achieved a 20% reduction in power consumption, ensuring optimal efficiency.
2. Power Supply: A reliable power source is crucial for seamless operation. The included power supply ensures stable performance and longevity.
3. Black Case: The sleek black case not only provides protection but also adds a touch of elegance to your setup.

Key Features of the ODROID-M1S:

• Quad-Core Cortex-A55 CPU: The main CPU, featuring a quad-core Cortex-A55 cluster, operates at a robust 2.0GHz. Thermal throttling is effectively managed using the stock heat sink, resulting in a quiet and dependable computing experience.
• Built-in 64GB eMMC Chip: We’ve integrated a 64GB eMMC chip directly onto the board, streamlining storage and enhancing overall performance.
• Expanded Connectivity: With 14 header pins, the ODROID-M1S offers greater flexibility for connecting peripherals and customizing your system.
• Industrial Longevity: Recognizing the importance of longevity for industrial applications, we commit to supplying this product until at least 2036.

!ODROID-M1S Kit

Whether you’re a hobbyist, developer, or industrial user, the ODROID-M1S Kit empowers you to create cost-effective and sustainable solutions. Explore the possibilities today!

Top of Board with I/O Pins	Bottom of Board with I/O Pins

On-Board eMMC Storage

For the first time in the ODROID board series, an eMMC chip was soldered to the PCB by default instead of using a removable eMMC module. We think 64GB capacity is sufficient for building most embedded systems.

The speed of eMMC measured with the I/O command is approximately 180MiB/s, which is about 3~5 times faster than typical microSD cards.

On-board M.2 NVMe slot

In case the 64GB storage space of the soldered eMMC memory is insufficient, consider using an industry standard 2280 form factor NVMe SSD. An on-board M.2 NVMe slot is provided to access large amounts of data storage.

Unlike the original M1 model’s PCIe 3.0 x 2 lanes configuration, M1S has PCIe 2.1 x 1 lane. The NVMe transfer speed of the M1S has been reduced by about 1/4. However, we still believe that ~400 MiB/s of storage access speed is sufficient for building various high-end embedded systems.

Note that M.2 SATA storage devices can not be used. The M.2 slot supports only a PCIe interface (M-Key).

Board Detail

GPIO Header

There are 40-pin and 14-pin header pin connectors for general purpose input and output functions. Digital IOs, UARTs, I2Cs, PWMs, ADCs, SPI, USB 2.0 host, Analog audio output, Power-on and Reset signals are available.

What we heard from many B2B and B2C customers is that they often didn’t use the actual GPIO functionality. Therefore, to lower production costs and product price, we decided to make GPIO header pin installation an option. If you choose the option to install 40-pin and 14-pin GPIO headers, $3 will be added to the price. An IO-labels board for easier DIY tinkering will also be provided.

MIPI-DSI

-The four-lane MIPI-DSI port can be directly connected to an LCD panel.

-The ODROID-Vu8S kit with an 8 inch, 800×1280 wide viewing angle LCD and capacitive multi-touch screen is an available option. Note that LCD connector is different from the one on the ODROID-M1.

-If you assemble the ODROID-M1S single board computer on the rear side of the Vu8S kit, you can easily implement a Human-Machine-Interface (HMI) device with Android as well as Linux.

NPU

Since Machine Learning has been a trend in this industry, there is a neural network processing unit (NPU) which can deliver up to 0.8 TOPS on the M1S single board computer.

We could run various TensorFlow Lite and ONNX models on Ubuntu Linux OS. Here is an example of object detection.

– Input image and Output image ( The input image source : https://commons.wikimedia.org/wiki/File:Traffic_in_Brasilia_before_Brazil_%26_Chile_match_at_World_Cup_2010-06-28_1.jpg )

As shown in the test results below, the object detection speed of the NPU is nearly 20 times faster than that of the CPU. For reference,

the NPU performance of M1S is about 10% lower than that of M1. We believe this is due to the difference in DRAM clocks.

Conf=0.25     CPU (ms)     NPU (ms)     NPU: Cam (fps)

M1S             1288.3         70                     11.8

M1                     1225.7         64.3             13

CPU governor = performance

AI model = yolov5s.onnx(cpu) / yolov5s.rknn(npu)

Confidence threshold = 0.25

USB Camera = Logitech BRIO

Software Support

Android 11

• AOSP based on Rockchip BSP
• Customized raw GPIO access framework : Android Things with various examples https://wiki.odroid.com/common/android_things
• GPIO toggling
• Rotary encoder with GPIO IRQ
• PWM outputs
• I2C (Color sensor, Temperature, Humidity, OLED, RTC)
• SPI ( CAN receiver, LED strip lights, IO expander)
• UART ( Loopback test, Barcode scanner, Thermal printer)

Ubuntu 20.04 LTS 

• Kernel 5.10.160
• Wayland based GNOME desktop
• ARM Mali Bifrost GPU OpenGL-ES / EGL driver
• MIPI DSI driver
• GPIO drivers and WiringPi library
• NPU driver and Neural Network APIs
• VPU driver with MPP/Gstreamer APIs

Ubuntu 22.04 LTS

• Kernel 6.1.60
• Wayland based Gnome/KDE desktop
• ARM Mali Panfrost GPU driver for desktop OpenGL 3.x
• MIPI DSI driver
• GPIO drivers and WiringPi library

Representative Application Examples and Videos

M1S + 6 channel stepper motor board and actual 3D printer operation video (via YouTube)

M1S + 4 Channel Relay board controlling a home system.

Documentation

We provide comprehensive documentation for nearly 100 items through our WiKi pages and Github.

• Features of the OS images and installation guides for Ubuntu, Android, ROS2 and so on
• Hardware: Specification, Full schematics, Datasheet, 3D models, Add-on board PCB design template for KiCad and over 10 add-on peripherals
• Software Board-Support-Package : Boot-loader, Kernel, Partition table, How-to-build, Boot-sequence, USB-UART console debugging and so on
• Application Notes : Device-Tree Overlay, WiringPi and Python libraries for GPIO, Basic GPIO access, ADC, UART, PWM, I2C, LCD, Sensors, SPI, CAN-Bus, 1-Wire, How-to use NPU accelerator for AI application, How-to use VPU for video decoding and encoding, How to use MIPI-DSI interface with 5 inch or 8 inch MIPI LCD.