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Favorit blandt kunder – LattePanda IOTA M.2 M-Key Expansion Board (NVMe SSD & AI Accel)

Den oprindelige pris var: 140,00 kr..Den aktuelle pris er: 58,80 kr..

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Varenummer (SKU): SKOT9503Y3N Kategori:

The LattePanda IOTA M.2 M-Key Expansion Board is a dedicated interface adapter designed to unlock the full potential of the LattePanda IOTA single-board computer. It functions by converting the board’s native 16-pin FPC PCIe interface into a universally recognized M.2 M-Key slot. This direct conversion enables two critical performance upgrades: the integration of high-speed M.2 NVMe solid-state drives for expanded storage, or the addition of M.2 AI accelerator modules for powerful edge computing. Key specifications include a PCIe 3.0 1 communication rate (8 GT/s), support for both 2230 and 2280 M.2 form factors, and a plug-and-play design for effortless installation. This makes this adapter an essential component for developing compact servers, advanced embedded systems, and edge AI applications.

Seamless Integration with LattePanda IOTA

Engineered exclusively for the LattePanda IOTA, this expansion module guarantees perfect electrical compatibility and precise physical alignment. Its purpose-built design eliminates concerns about signal integrity or instability that can arise from generic adapters. This dedicated integration ensures a stable, reliable connection, allowing developers to focus on their projects without troubleshooting hardware compatibility.

Unlocks High-Performance Expansion

The primary function of this M.2 expansion board is to serve as a gateway to high-performance peripherals. By connecting an M.2 NVMe SSD, users can dramatically boost storage capacity and achieve read/write speeds far exceeding the onboard eMMC, ideal for running a full desktop OS or managing large datasets. Alternatively, the slot can house an M.2 AI acceleration card, offloading complex machine learning and computer vision tasks from the main CPU to enable efficient, real-time AI inference at the edge.

Flexible M.2 Device Compatibility

Support for both the compact 2230 and standard 2280 M.2 form factors provides significant deployment flexibility. This allows users to select from a wide range of commercially available NVMe SSDs and AI modules based on their specific performance, capacity, or size requirements. This versatility is especially valuable for creating custom-sized embedded solutions or adapting to different project constraints.

Effortless Plug-and-Play Installation

The module is designed for simplicity and rapid implementation. It connects to the LattePanda IOTA via a simple FPC flex cable, and the M.2 device is automatically recognized by the system upon power-up without the need for complex driver installations or configuration. This plug-and-play functionality streamlines the development and prototyping process, making advanced hardware expansion accessible to all skill levels.

Important Notes

  • Designed EXCLUSIVELY for LattePanda IOTA
  • For M.2 SSD devices, only NVMe SSDs are supported; SATA SSDs are not supported.
  • Maximum Communication Rate: PCIe 3.0 1 (8 GT/s)
  • Applications

  • Compact NAS or Home Server: Building a small-footprint server with fast NVMe storage for rapid data access.
  • Edge AI Development: Creating intelligent devices for real-time object detection, facial recognition, or industrial automation.
  • High-Performance Embedded Systems: Designing systems that require a responsive operating system and the capacity to store and process large amounts of data locally.
  • Advanced Robotics: Prototyping robots that depend on low-latency data retrieval and on-device AI processing for autonomous navigation and interaction.
  • Specification

  • Compatible Board: LattePanda IOTA only
  • Expansion Interface: M.2 M-Key (PCIe x1)
  • Host Interface: 16-Pin FPC (0.5mm pitch)
  • Supported Devices: M.2 NVMe SSD, M.2 AI Acceleration Card
  • Supported Sizes: 2230 / 2280
  • Communication Rate: PCIe 3.0 1 (8 GT/s)
  • Board Dimensions: 88mm 31.5mm
  • Installation: FPC flex cable connection
  • Documents

  • Product wiki