MistySOM by MistyWest: The Low Power Embedded Compute Solution for Industrial Automation and More

 MistySOM - Enabling Low Power Embedded Compute Applications with MistySOM

MistySOM by MistyWest: The Low Power Embedded Compute Solution for Industrial Automation and More

MistySOM is a family of System on Modules (SOMs) built around the Renesas RZ microprocessors, designed to enable efficient and flexible development of embedded computing applications. MistySOM comes in two versions, the MistySOM-G2L and the MistySOM-V2L, each with specific features tailored to different application requirements.
MistySOM by MistyWest: The Low Power Embedded Compute Solution for Industrial Automation and More

The MistySOM-G2L is a general-purpose SOM that is ideal for use in industrial and commercial computing applications where low power, reliability, and cost are critical. It features a dual-core Cortex-A55, a single-core Cortex-M33 CPU, Arm Mali-G31 GPU, and 2GB DDR4 RAM. Additionally, it includes a 32GB eMMC, dual Gigabit Ethernet, and support for 4-lane MIPI DSI and CSI interfaces. The SOM is ruggedized for industrial temperatures and offers super long-term firmware support via a CIP kernel-based Linux BSP.

MW-G2L-E32G-D2G-I-WX-V0 Specifications
Processor Renesas RZ/G2L (dual-core Cortex-A55, 1.0 GHz)
Memory 2 GB DDR4, 32 GB eMMC
Operating Temperature -40°C to 85°C
Dimensions 52 x 40 x 4 mm
Connectivity 1x GbE, 2x USB 2.0, 2x CAN, 1x RS-232/422/485, 1x I2C, 1x SPI, 1x SDIO, 12x GPIO
Power 5V/12V DC-in
Operating System Linux with CIP kernel

The MistySOM-V2L is a power-efficient computer vision SOM that includes all the features of MistySOM-G2L, with the addition of a DRP-AI NPU, making it well-suited for low-power object detection, classification, and localization. It features a dual-core Cortex-A55, a single-core Cortex-M33 CPU, Arm Mali-G31 GPU, and 2GB DDR4 RAM. The DRP-AI NPU enables Jetson Nano-like performance for embedded video applications while using 50% less power. It also supports multiple AI frameworks, including ONNX format models supported by the DRP-AI Translator and other formats, such as PyTorch and TensorFlow, supported via the DRP-AI TVM.

MW-V2L-E32G-D2G-I-WX-V0
Processor Renesas RZ/V2L (Pin-compatible with RZ/G2L)
CPU Dual-core Cortex-A55 + Cortex-M33
NPU 1x 4 TOPS, with INT8/INT16/FP16 support
Memory 2 GB DDR4, 32 GB eMMC
Connectivity Gigabit Ethernet, Wi-Fi 802.11 a/b/g/n/ac/ax, Bluetooth 5.2
Video Output HDMI 2.0a
Operating Temperature -40°C to 85°C
Dimensions 45mm x 45mm

MistySOM is designed to be integrated into custom solutions quickly, and to facilitate that, the MistyCarrier carrier board is also available. MistyCarrier is designed with low-power and industrial applications in mind and includes sense resistors for measuring system currents, MCU allowing ultra-low power sleep state for the system, and an industrially rated supercapacitor to support the RTC without a battery.

MistyCarrier carrier board

The applications for MistySOM are diverse, from barcode scanner systems and self-checkouts to wearable cameras and precision time synchronization. The MistySOM-G2L is ideal for industrial human-machine interface (HMI), network gateways, portable equipment, and general single-board computer applications. On the other hand, the MistySOM-V2L is well suited for sports cameras and movement tracking, retail and logistics automation, building management, people counting, smart transportation, traffic monitoring, food waste detection, construction monitoring, animal tracking, and smart agriculture.

In conclusion, the MistySOM family of SOMs offers a flexible, low-power, and cost-effective solution for embedded computing applications, with long-term firmware support and ruggedization for industrial temperatures. The MistyCarrier carrier board facilitates the integration of the SOMs into custom solutions. It is an excellent choice for developers and manufacturers looking to build reliable, low-power, and cost-effective embedded systems.

MistySOM, a powerful yet affordable System-on-Module for embedded AI applications, can now be purchased through GroupGets. In addition, the MistySOM resources, including schematics, design files, and software examples, are available on their GitHub page, making it easy for developers to get started with this impressive technology.

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