| Specification | Details |
|---|
| Product Name | Plink Y-C7-DEV-NANO Jetson Nano Development Kit |
| Module | NVIDIA Jetson Nano 4GB or 2GB SoM (depending on variant) |
| CPU | Quad-core ARM Cortex-A57 @ 1.43 GHz |
| GPU | 128-core Maxwell GPU |
| Memory | 4GB or 2GB LPDDR4 (depending on model) |
| Storage | microSD card slot for OS and data |
| Networking | 1× Gigabit Ethernet |
| USB Ports | 4× USB 3.0 ports, 1× USB 2.0 Micro-B |
| Camera Interface | 1× MIPI CSI-2 connector |
| Display Interface | HDMI 2.0, DisplayPort (via carrier board if available) |
| I/O Interfaces | GPIO, I2C, SPI, UART, PWM, I2S |
| Power Supply | 5V/4A via barrel jack or Micro-USB (depending on board) |
| Software Support | NVIDIA JetPack SDK (Linux + CUDA, TensorRT, cuDNN) |
| Form Factor | Compact development board for domestic AI/IoT projects |
| Development Focus | AI, robotics, computer vision, edge computing, education |
Description:
The Plink Y-C7-DEV-NANO Jetson Nano Domestic Development Kit is an accessible AI development platform designed for hobbyists, educators, and developers building entry-level AI and robotics applications. At its core, the kit leverages the Jetson Nano SoM, featuring a Quad-core ARM Cortex-A57 CPU and a 128-core Maxwell GPU, providing sufficient compute power for edge AI workloads such as image recognition, object detection, and smart automation.
With 4GB LPDDR4 memory, the platform can efficiently handle small to medium-sized AI models. It provides a flexible microSD slot for storage, multiple USB ports, and a Gigabit Ethernet interface for connectivity. The board also exposes a MIPI CSI-2 camera connector, GPIO, I2C, SPI, UART, and PWM interfaces, making it ideal for integrating sensors, cameras, and other peripherals in domestic and educational projects.
Display options include HDMI 2.0, allowing users to connect high-definition monitors for AI visualization tasks. The kit is powered via a 5V/4A barrel jack or Micro-USB, ensuring low power consumption suitable for home or classroom use. Supported by the NVIDIA JetPack SDK, it allows developers to access Linux, CUDA, TensorRT, and cuDNN libraries, enabling efficient deployment of AI models and rapid prototyping for domestic AI, robotics, and IoT projects.