Jetson Orin Nano New Generation Embedded Smart T201S AI Edge Computer

Waveshare UGV Rover ROS 2 Open-source 6 Wheels 4WD AI Robot With Jetson Orin Nano 4GB Kit, Dual controllers, 360° Flexible Omnidirectional Pan-Tilt Waveshare UGV Rover ROS 2 Open-Source 6-Wheel 4WD AI Robot is a powerful mobile robotics platform designed for Jetson Orin series boards. Built for advanced AI, perception, and autonomous navigation tasks, it features a rugged 6-wheel 4WD design, dual controllers, and a 360° flexible omnidirectional pan-tilt system for full-range vision. Ideal for research, prototyping, and robotics development, this UGV offers seamless ROS 2 integration and high performance for real-world robotic applications Features Supports Pan-Tilt drag-and-drop control via mouse or touch panel of the laptop, providing a better control experience as FPS games Powered by Jetson Orin series computer Supports Jetson Orin Nano 4GB Kit, provides up to 20 TOPS AI Performance. High-speed reading/writing, to meet the development needs of large AI projects Advanced AI Recognition & Tracking Based on OpenCV, supports color recognition and automatic targeting with one-key Pan-Tilt control and auto LED lighting. Expandable for additional AI functions. Face Detection & Recognition Automatically captures photos or records videos when a face is detected, providing enhanced security and AI interaction. Cross-Platform Web Control No app installation required! Simply connect via a web browser on mobile, tablet, or PC. Supports WASD keyboard shortcuts and mouse control for seamless navigation. WebRTC real-time video transmission Adopts Flask lightweight web application, based on WebRTC ultra-low latency real-time transmission, using Python language and easy to extend, working seamlessly with OpenCV Features at a glance Multiple Autonomous Navigation Modes UGV Rover supports multiple autonomous navigation modes, allowing it to navigate complex environments with precision. Whether following predefined paths, avoiding obstacles, or performing AI-assisted route planning, the robot adapts intelligently to real-world terrains. Dimensions

reComputer J401 – Carrier Board for Jetson Orin Nano & Orin NX The reComputer J401 is an advanced NVIDIA Jetson Orin NX carrier board, purpose-built to support both Jetson Orin Nano and Orin NX modules. Designed as an open-source extension board, it breaks out a comprehensive range of I/O interfaces from the SoM, offering seamless high-speed and low-speed connectivity to meet diverse development needs. With its compact form factor, reliable performance, and developer-friendly architecture, the J401 simplifies the process of building, testing, and scaling embedded systems. Ideal for prototyping, edge deployments, and long-term product updates, it accelerates time-to-market while providing the flexibility required for robotics, computer vision, and AI-powered edge applications. Features: NVIDIA Elite Partner certified – ensuring reliable quality and compatibility. 260-pin Jetson module connector – supports both Jetson Orin NX and Orin Nano modules. Open-source hardware – flexible and developer-friendly for customization. Compact form factor – measures just 100mm x 80mm for space-saving integration. Wide operating temperature range – works reliably from -10°C to 60°C. Wireless connectivity – M.2 Key E slot for WiFi and Bluetooth expansion. Storage expansion – M.2 Key M slot supports SSD integration. High-speed networking – RJ-45 GbE port with 10/100/1000M support. Camera and display support – includes 2x CSI camera interfaces and 1x HDMI 2.1. Versatile USB options – 1x USB 2.0 Type-C (device mode) + 4x USB 3.2 Type-A (10Gbps). Stable power input – DC Jack 12V/5A for dependable operation. Optimized for edge applications – ideal for robotics, computer vision, and generative AI projects. Applications: AI Video Analytics Machine Vision Autonomous Mobile Robot (AMR) Generative AI Hardware Overview: Applications Gallery – Sample Edge AI Setups AI Video Analytics Rig : Orin NX + J401 + CSI camera + NVMe SSD for real-time video inference and storage. Autonomous Mobile Robot (AMR) : Combine wheel motors (via MCU or controller board), sensors, camera feed, and edge-AI inference on Orin for navigation, obstacle detection, and decision-making. Industrial Automation & Monitoring : Use Gigabit Ethernet, CAN port, multiple sensors, and AI inference to monitor machines, detect anomalies or control actuators. Generative AI / Edge ML Server : Use Orin NX with SSD and cooling via J401 to run heavy ML workloads locally ideal for edge-AI deployments without cloud dependency. Computer Vision + Robotics Laboratory Setup : Multiple cameras via dual CSI, USB 3.2 devices, external sensors build a flexible AI-powered research or prototyping station.

reComputer J4012B Edge AI Computer Powered by NVIDIA Jetson Orin NX 16GB 100 TOPS AI The reComputer J4012B Edge AI Computer, built on the NVIDIA Jetson Orin NX 16GB module, is engineered for high-performance AI at the edge, delivering up to 100 TOPS of AI compute for robotics, automation, vision systems, and industrial AI deployments. With a powerful 8-core Arm CPU, Ampere GPU with Tensor Cores, and 16GB LPDDR5 memory, this compact edge device is ideal for tasks such as real-time inference, multi-camera processing, deep learning, and edge analytics. The pre-installed JetPack 5.1.3 ensures a ready-to-deploy development environment with optimized CUDA, cuDNN, and TensorRT support. Designed for both prototyping and large-scale production, the reComputer J4012B includes a rich set of interfaces - USB 3.2, HDMI, Gigabit Ethernet, M.2 Key M for SSD, M.2 Key E for Wi-Fi, mini-PCIe for LTE, CAN bus, and 40-pin expansion header. With a durable aluminum case, active cooling, 128GB NVMe SSD, and certifications including CE, FCC, KC, ROHS, REACH, this device is ready for industrial, commercial, and AIoT applications. Guaranteed long-term availability until 2032, the J4012B is a future-proof platform for next-generation edge computing. Features: Powered by NVIDIA Jetson Orin NX 16GB, delivering up to 100 TOPS for advanced AI workloads. Features a 1024-core NVIDIA Ampere GPU with 16 Tensor Cores for accelerated deep learning and computer vision tasks. Built with a high-efficiency 8-core Arm Cortex-A78AE CPU for reliable real-time edge processing. Comes pre-installed with a 128GB NVMe SSD for fast storage and ready-to-deploy performance. Offers rich connectivity: 2× USB 3.2, HDMI, Gigabit Ethernet, M.2 Key M, M.2 Key E, mini-PCIe, CAN, 40-pin GPIO and more. Includes JetPack 5.1.3 preloaded for immediate development in Linux, CUDA, and AI frameworks. Robust aluminum enclosure with active cooling for stable 24/7 operation. Certified with CE, FCC, KC, UKCA, ROHS, REACH for industrial and commercial use. Long-term supply availability until 2032, ideal for scalable deployments. Applications: Smart Lamppost Systems Smart lampposts use integrated sensors to monitor traffic flow, pedestrian movement, and environmental conditions. The collected data helps city authorities optimize traffic control and improve public safety. Many smart lampposts also operate on solar energy, storing power for nighttime illumination and even feeding surplus electricity back into the grid to support sustainable urban infrastructure EV Battery Swapping & Charging Infrastructure Modern EV charging and battery-swapping stations connect directly to smart grid networks, enabling efficient load balancing and optimized charging schedules. This reduces strain on the grid during peak hours and ensures faster turnaround times for EV users. Advanced systems even allow certain electric vehicles to return power to the grid, contributing to a more resilient and flexible energy ecosystem. Smart Recycling & Waste Management Centers Smart recycling hubs utilize sensors embedded in collection bins to track fill levels, minimizing unnecessary collection trips and reducing operational costs. Energy-efficient sorting machines operate during off-peak hours, lowering power consumption. Recycled materials collected through these systems are often further utilized in manufacturing components for EVs, renewable energy setups, and other smart grid technologies, promoting a circular and sustainable industrial cycle. Hardware Overview:

ACEBOTT QD107 AI Vision For TinkerBott Car V1.1 (Car Kit is Not Included) ACEBOTT QD107 AI Vision Module for TinkerBott Car V1.1 enhances your robot with smart image recognition, object tracking, and AI-powered interaction capabilities. Built around an ESP32 camera system, this upgrade allows students and makers to explore computer vision, machine learning, and intelligent robotics in a hands-on way. Whether used in STEM classrooms or home robotics projects, the QD107 adds exciting new functionality to the TinkerBott platform, making coding and learning more engaging and interactive. Features AI-powered vision module enables object detection, recognition, and tracking. Built-in ESP32 camera provides fast image processing and wireless communication. Plug-and-play upgrade designed specifically for TinkerBott Car V1.1. Supports multiple programming platforms, making it ideal for beginners and advanced learners. Enhances STEM learning with hands-on experience in computer vision and AI robotics. Lightweight and modular design allows easy installation without affecting robot mobility.

SmartElex Ai Thinker Ai M62 32S Development Kit The SmartElex AI Thinker Ai-M62-32S Development Kit is a powerful and versatile solution designed for modern wireless and IoT applications. Built around the BL616 RISC-V CPU, it delivers high performance with a maximum operating frequency of 320 MHz, making it suitable for real-time data processing and edge computing. This AI thinker modules platform supports Wi-Fi 6, BLE 5.3, and Thread protocol, ensuring fast, stable, and low-power connectivity. The Ai-M62-32S Development Kit features a wide range of interfaces including USB 2.0, SPI, UART, I2C, I2S, PWM, ADC, DAC, and GPIO, enabling seamless integration with sensors, displays, and peripherals. With built-in hardware security engines supporting AES, SHA, PKA, and TRNG, along with secure boot and encrypted firmware startup, it meets strict security requirements for IoT deployments. This makes the Ai-M62-32S Development Kit an excellent choice for smart home systems, wearable electronics, multimedia devices, and next-generation IoT solutions. Features: Supports the 2.4GHz operational frequency band. Support IEEE 802.11 B/G/N/AX. Support BLE 5.3. Wi-Fi Security Support WPS/WEP/WPA/WPA2/WPA3 Supports 20/40MHz bandwidth, 1T1R, maximum rate of 229.4 Mbps Supports STA, SoftAP, STA+SoftAP, and sniffer modes. A 32-bit RISC-V CPU with FPU and DSP has a maximum dominant frequency of 320M. 532KB SRAM, 128KB ROM, 4KB eFuse. Supports USB2.0, SDU, SD/MMC (SDH), SPI, UART, I2C, I2S, PWM, GPDAC, GPADC, ACOMP, and GPIO, among others.

reComputer J3010 Edge AI Computer with NVIDIA Jetson Orin Nano 4GB Brains of a genius, size of a sandwich - The reComputer J3010 Edge AI Computer by Seeed Studio is a high-performance and compact solution designed for AI applications at the edge. Powered by the NVIDIA Jetson Orin Nano 4GB SoM, it delivers robust processing capabilities optimized for machine learning and AI workloads. The device comes pre-installed with Jetpack 5.1.1 (Super Mode JP6.2), enabling advanced AI features and superior performance. It includes a 128GB SSD for ample storage, along with versatile connectivity options such as 4x USB 3.2 ports, HDMI output, and Gigabit Ethernet. The carrier board expands flexibility with M.2 Key E for WiFi, M.2 Key M for additional SSD storage, RTC, CAN interface, and a 40-pin GPIO header. As a dedicated Edge AI computer, the reComputer J3010 is ideal for industrial automation, robotics, smart vision, and other AI-driven applications where compactness and performance are critical. (Power adapter not included). Related Searches - Orin Nano Accesories Features: Capable of Bringing Generic AI to the Edge You can now create AI agents capable of analyzing enormous amounts of live or archived videos and images using Vision-Language Models (VLM) such as LLaVA. These new AI agents assist practically every industry in summarizing, searching, and extracting actionable insights from video using natural language. Create Multi-stream AI Video Analytics Jetson Orin Nano uses the NVIDIA Multi-Standard Video Decoder into its video analytics architecture. This video decoder speeds up video decoding by supporting low-resolution mobile material, Standard Definition (SD), High Definition (HD), and UltraHD (8K, 4K, etc). reComputer J3010 supports 11x1080p30 streaming. See our tested YOLOv8 performance utilizing NVIDIA Deepstream for single and multi-model multi-stream scenarios. Fastest Way to Deploy Generative AI and Computer Vision Models We have prepared a Jetson example for you! It provides one-line deployment of edge AI apps such as Ollama and Llama3, as well as computer vision tools such as YOLOv8. We have configured the entire environment for you to allow a single command deployment of projects. Hardware Overview: reComputer J401 Carrier Board, Included in the Full System - reComputer J3010 Desktop, Wall Mount, Expandable, or Fit in Anywhere User Projects Made With the J3010 Smart Security Camera that detects people and tracks movement using simple CV models. Line-Following or Obstacle-Avoiding Robot for classrooms, workshops, and hobby builds. AI Face Recognition System for attendance, home automation triggers, or DIY access control. Which Jetson Is Right for You? Jetson Module AI Performance (TOPS) CUDA Cores Best For Ideal User Jetson Nano ~0.5 TOPS 128 Basic AI tasks, simple robotics, learning projects Students, hobbyists, first-time AI builders Jetson Orin Nano (4GB) Up to 20 TOPS 512 Entry-level edge AI, vision projects, DIY automation Makers and beginners upgrading from Nano Jetson Orin Nano (8GB) Up to 40 TOPS 1024 Real-time vision, robotics, AI robotics kits, compact automation Developers building smarter robots and edge AI systems Jetson Orin NX Up to 100 TOPS 1024 Heavy AI workloads, multi-model pipelines, advanced robotics Professionals needing workstation-level edge performance Jetson Orin Nano – J3010 Variant Up to 20 TOPS 1024 Efficient edge AI computing, robotics, smart cameras Users who want high performance in a small, power-efficient system Applications: AI Video Analytics Machine Vision Autonomous Mobile Robot (AMR) Generative AI

NVIDIA Jetson Orin NX 8GB RAM 70 TOPS AI Embedded Module T801 AI Developer Kit The NVIDIA Jetson Orin NX 8GB RAM 70 TOPS AI Embedded Module T801 AI Developer Kit is a compact yet powerful edge AI platform built for developers and innovators who need serious computing performance in a small footprint. Equipped with 8GB RAM and delivering up to 70 TOPS of AI performance, this module enables real-time machine learning, computer vision, and autonomous processing directly on the device—without depending on cloud connectivity. It is perfectly suited for robotics, smart surveillance systems, industrial automation, and advanced IoT solutions. With full support for popular AI frameworks like TensorFlow and PyTorch, along with NVIDIA’s JetPack SDK, the kit streamlines development, testing, and deployment of intelligent systems. Whether you are prototyping an AI concept or building a production-ready solution, this developer kit offers the performance, flexibility, and reliability required for next-generation embedded AI applications. Hardware Overview: Applications: 1. Practical Application in Security Monitoring Scenarios 2. Practical Application in Smart Gas Station 3. Practical Application in Smart Petroleum Providing simultaneous assistance for channel video analysis. Provide support for smoke, fire, personnel area monitoring, fall detection, safety helmet recognition, tools, gauges, oil level, and valve direction. 4. Practical Application | Identification of Unidentified Objects in Power Transmission Providing simultaneous support for four-channel video analysis Unidentified object recognition, fireworks, and engineering vehicles. Subsequent additions, aberrant insulators, pins, bird spikes, Features: Built on NVIDIA Jetson Orin NX architecture 8GB RAM for smooth AI model execution Up to 70 TOPS AI performance for real-time inference Optimized for edge AI and embedded systems Supports TensorFlow, PyTorch & NVIDIA JetPack SDK Low power consumption with high computational efficiency Ideal for robotics, smart vision, and industrial automation applications

NVIDIA Jetson Nano Development Kit (Alternative of B01 Kit) The NVIDIA Jetson Nano Development Kit is an advanced AI computing platform, designed as a powerful and flexible alternative to the Jetson Nano B01 Kit. Featuring compatibility with both Jetson Nano and Jetson Xavier NX core modules, this development kit maintains almost the same I/O interfaces, size, and thickness as the original Jetson Nano Developer Kit (B01), making it an ideal upgrade solution. With its robust computing power and versatile connectivity, it is suitable for a wide range of AI applications including image classification, object detection, segmentation, speech processing, and more. Whether you are working on edge AI projects or seeking a Jetson Nano Kit Alternative, this development kit empowers developers to harness the full potential of NVIDIA Jetson Nano Development Kit capabilities while offering seamless module upgrades. Features: Compatible with Jetson Nano Core Module and Jetson Xavier NX Core Module Designed as a Jetson Nano B01 Alternative with similar I/O ports, size, and form factor Easy upgrade path by swapping the core module for enhanced AI performance Supports advanced AI tasks like image classification, object detection, segmentation, and speech processing Provides powerful GPU-accelerated AI computing for edge AI and embedded applications Compact and efficient design for seamless integration into custom projects Ideal for developers looking for a Jetson Nano Kit Alternative with extended flexibility Fully utilizes the capabilities of the NVIDIA Jetson Nano Development Kit ecosystem

Seeed Studio A603 Carrier Board for Jetson Orin™ NX/Orin™ Nano The Seeed Studio A603 Carrier Board for Jetson Orin™ NX/Orin™ Nano is a powerful and versatile extension board designed to maximize the performance of NVIDIA’s Jetson modules. Equipped with a GbE port, M.2 Key M for SSD storage, and M.2 Key E for WiFi/Bluetooth connectivity, it ensures seamless integration for data-intensive applications. With MIPI CSI and HDMI support, the carrier board enables high-quality video capture and display, making it ideal for AI vision projects. It also includes 4x USB ports, a built-in cooling fan, and RTC functionality, all powered by a flexible 9–20V input. Its compact and space-saving design allows easy integration into a wide range of edge computing and embedded AI solutions. Features: Compatible with Jetson Orin™ NX/Orin™ Nano modules High-speed Gigabit Ethernet (GbE) port M.2 Key M slot for SSD storage expansion M.2 Key E slot for WiFi/Bluetooth modules MIPI CSI and HDMI interfaces for video input/output 4x USB ports for peripheral connectivity Built-in cooling fan and RTC support Wide 9–20V DC power supply input Compact design for easy integration in edge computing Applications: Autonomous Mobile Robot (AMR) AI Video Analytics Machine Vision Generative AI Hardware Overview:

Official Raspberry Pi AI Kit Unlock the power of AI with the Official Raspberry Pi AI Kit. This kit includes the Raspberry Pi M.2 HAT+ and the powerful Hailo AI acceleration module, which is specifically designed for the Raspberry Pi 5. The Hailo-8L processor can do 13 tera-operations per second, which makes it ideal for complicated AI applications. The module connects easily to the Raspberry Pi 5 through the M.2 HAT+, linking the AI module’s M.2 interface with the Raspberry Pi 5’s PCIe 2.0 interface. With the latest Raspberry Pi OS, the system automatically detects the Hailo module, making the Neural Processing Unit (NPU) ready for AI tasks. The built-in camera apps in Raspberry Pi OS also support the AI module, streamlining AI-powered projects. This Raspberry Pi 5 expansion board is mainly used for a variety of purposes, such as advanced robotics, unique home projects, deep learning artificial intelligence, and instructional support. So, It's time to transform your Raspberry Pi 5 into an effective AI workstation. Get into the fascinating field of artificial intelligence by ordering the Raspberry Pi AI Kit for Pi 5. Discover the Best Raspberry Pi Boards ! Key Features: Capable of 13 TOPS for effective neural network inference. Fully integrated into the Raspberry Pi's camera software stack for convenient use. The pre-fitted thermal pad distributes heat across components, enhancing overall performance. Conforms to the Raspberry Pi HAT+ standard for dependable operation. Comes with a 16mm stacking header, spacers, and screws for simple installation. Temperatures may range from 0? to 50?, making it suitable for a variety of applications. Best Raspberry Pi 5 HAT for advanced projects Why Choose Raspberry Pi AI Kit? Affordable Edge AI Solution: Delivers powerful AI performance at a low cost, ideal for developers and hobbyists. Powered by Hailo-8L Accelerator: Offers up to 13 TOPS for efficient object detection and pose estimation. Seamless Integration with Raspberry Pi 5: Designed for M.2 HAT+ interface, ensuring stable hardware and software compatibility. Local AI Processing: Enables on-device inference without cloud dependency—faster, private, and energy-efficient. Optimized for Vision Projects: Perfect for tasks like image recognition, tracking, and robotics. Scalable Performance: Supports upgrade to Hailo-8 (26 TOPS) for advanced AI workloads. Great for Learning & Prototyping: Easy setup for educators, students, and makers exploring AI development. Raspberry Pi AI Kit M.2 HAT+ vs AI HAT+ Feature Raspberry Pi AI Kit M.2 HAT+ Raspberry Pi AI HAT+ (13 TOPS) AI Accelerator Hailo-8L (13 TOPS) Hailo-8L (13 TOPS) Interface M.2 HAT+ (PCIe connection) Standard HAT+ (direct GPIO / PCIe bridge) Compatibility Designed for Raspberry Pi 5 (uses M.2 slot) Works with Raspberry Pi 5 via standard HAT+ connector Performance ~13 TOPS at 9–10 W ~13 TOPS at 9–10 W Cooling Requirement Requires active cooling (heat dissipation via metal plate) Passive cooling sufficient for light workloads Installation Type Mounted under the Pi using the M.2 slot Stacks directly on top of Raspberry Pi 5 Form Factor Compact and flat design (ideal for embedded systems) Slightly taller profile due to stacking header GPIO Access Limited (requires extended stacking header) Easier access to GPIO pins Upgrade Option Supports Hailo-8 (26 TOPS) upgrade Fixed Hailo-8L (13 TOPS) only Best For Performance-focused AI projects, compact builds, industrial use Educational setups, DIY AI learning, and experimentation Power Source Powered via M.2 interface Powered via Raspberry Pi board directly Example Projects with Raspberry Pi AI Kit Smart Security Camera with Object Detection Facial Recognition Door Lock AI-Powered Traffic Monitoring System Gesture-Controlled Robot Real-Time Emotion Detection System Retail Analytics Counter Industrial Defect Detection Smart Waste Sorting Machine Wildlife Monitoring Station Personal AI Assistant Device

Ai-Thinker VC-02 Offline Speech Recognition Control Module The VC-02-Kit is a development board for the Voice Recognition Module, sharing the same design as the VC-01-Kit. It features an integrated CH340C USB-to-serial chip for debugging and upgrading, with added functionality like wake-up light, cold, and cooling lamp control, along with status indicators for easy debugging and control. Developed by Shenzhen Ai-Thinker Technology Co., Ltd., the VC-02 is a cost-effective offline speech recognition module that uses the US516P6 voice chip from Unisound. This chip offers a deep integration of offline recognition algorithms, providing an ultra-low-cost speech recognition solution. It is ideal for smart homes, small household appliances, 86 boxes, toys, lamps, and more, enabling voice control. The US516P6 chip features a 32-bit RISC architecture, DSP instructions for signal processing, an FPU unit for floating-point operations, and an FFT accelerator. The VC-02 Voice Recognition Module supports 150 local offline commands and a lightweight RTOS system, making it easy to customize with a variety of peripheral interfaces. Features All GPIOs can be set up as external interrupt inputs and wake-up sources One full-duplex UART with a maximum speed of 3Mbps Supports I2C, DAC, PWM, and multiple interfaces Includes 242KB of high-speed SRAM Equipped with 2MB FLASH memory Dual-channel DAC output support 32-bit RISC core running at 240MHz Supports DSP instruction set and FPU for floating-point operations

A203 V2 Carrier Board for NVIDIA Jetson Nano/Xavier NX/TX2 NX – Compact AI Development Board for Robotics & Embedded Systems - Seeed Studio The Jetson A203 V2 Carrier Board is an upgraded version of the A203, designed as a versatile and reliable NVIDIA Jetson Nano/Xavier NX/TX2 NX carrier board (A203 V2). It provides a wide range of peripheral interfaces, including support for Wi-Fi, Bluetooth, SSD storage, and more, making it highly adaptable for diverse industrial applications. From manufacturing and logistics to retail, agriculture, and beyond, this board enables developers to build end-to-end solutions with ease. With its compact size and lightweight design, the A203 V2 is an ideal compact AI development board for robotics, video analysis, and embedded systems. It’s well-suited for advanced robotics projects such as UAVs, unmanned boats, and submarines, offering seamless integration and stable performance. When paired with NVIDIA Jetson modules (sold separately), it empowers innovators, hobbyists, and professionals to accelerate development in robotics, computer vision, and edge AI. Features: NVIDIA Elite Partner Design – Built with reliability and compatibility in mind. 260-Pin Jetson Module Connector – Compatible with Jetson Xavier NX, Nano, and TX2 NX modules. Compact & Lightweight – Dimensions: 87mm × 52mm × 26mm; Weight: only 100g. Wide Operating Temperature – Stable performance from -25°C to 65°C for industrial environments. High-Speed Connectivity – 2 × USB 3.0 Type-A ports, 1 × USB 2.0 Micro-B connector, and USB 3.0 20-pin ZIF. Flexible Storage Expansion – Supports M.2 Key M SSD (2242) and MicroSD card. Reliable Networking – RJ-45 Gigabit Ethernet port (10/100/1000M). Multimedia Support – HDMI right-angle vertical connector and CSI camera interface. Rich I/O Interfaces – Includes UART, SPI, CAN, and GPIO for versatile peripheral integration. Stable Power Supply – Powered via 12V/5A DC jack for consistent performance. Application-Ready – Optimized for robotics, computer vision, video analysis, UAVs, and embedded AI solutions. Applications: Autonomous Mobile Robot (AMR) AI Video Analytics Machine Vision Generative AI A203 V2 Carrier Board Hardware Overview

reComputer J401 Carrier Board for Jetson Orin Nano & Orin NX – Open-Source Expansion Board (Without Power Adapter) The reComputer J401 is an advanced NVIDIA Jetson Orin NX carrier board, purpose-built to support both Jetson Orin Nano and Orin NX modules. Designed as an open-source extension board, it breaks out a comprehensive range of I/O interfaces from the SoM, offering seamless high-speed and low-speed connectivity to meet diverse development needs. With its compact form factor, reliable performance, and developer-friendly architecture, the J401 simplifies the process of building, testing, and scaling embedded systems. Ideal for prototyping, edge deployments, and long-term product updates, it accelerates time-to-market while providing the flexibility required for robotics, computer vision, and AI-powered edge applications. Features: NVIDIA Elite Partner certified – ensuring reliable quality and compatibility. 260-pin Jetson module connector – supports both Jetson Orin NX and Orin Nano modules. Open-source hardware – flexible and developer-friendly for customization. Compact form factor – measures just 100mm x 80mm for space-saving integration. Wide operating temperature range – works reliably from -10°C to 60°C. Wireless connectivity – M.2 Key E slot for WiFi and Bluetooth expansion. Storage expansion – M.2 Key M slot supports SSD integration. High-speed networking – RJ-45 GbE port with 10/100/1000M support. Camera and display support – includes 2x CSI camera interfaces and 1x HDMI 2.1. Versatile USB options – 1x USB 2.0 Type-C (device mode) + 4x USB 3.2 Type-A (10Gbps). Stable power input – DC Jack 12V/5A for dependable operation. Optimized for edge applications – ideal for robotics, computer vision, and generative AI projects. Applications: AI Video Analytics Machine Vision Autonomous Mobile Robot (AMR) Generative AI Hardware Overview:

Official Raspberry Pi AI Camera with SONY IMX500 Sensor The Official Raspberry Pi AI Camera with the Great 12MP Sony IMX500 Intelligent Vision Sensor! This RPi camera lets you explore advanced AI features easily. It fits well with Raspberry Pi computers and can process information on its own, which helps your Raspberry Pi do other things without getting slow. If you’re interested in AI projects, or machine vision, or just want to experiment with smart systems, this Raspberry Pi camera with object detection is perfect for you. It works with all Raspberry Pi Model 3 and 4 computers, so you can use it in many ways. Bring your projects to life with this amazing Official Raspberry Pi AI Camera Module! Old meets new Compatible with all Raspberry Pi computers, the Raspberry Pi AI Camera features Sony’s IMX500 Intelligent Vision Sensor, enabling you to build powerful vision AI applications and neural network models with its on-module AI processor. Effortless Vision AI The IMX500 seamlessly integrates with Raspberry Pi’s camera software, making it easy to deploy your own neural network models. To help you get started, we’ve created a step-by-step guide for running both pre-built and custom AI models on the camera. Scale with AITRIOS Develop AI models and applications for the IMX500 Intelligent Vision Sensor and Raspberry Pi, then expand seamlessly to enterprise-level deployment with AITRIOS. Explore Sony’s AI Services Local Studio provides a streamlined process for labeling, training, and producing AI models efficiently. Key Features 12MP Sony IMX500 sensor for high-quality images. On-board low-power inference engine for neural networks. Pre-loaded MobileNet model for quick AI applications. 76-degree field of view for detailed shots. Adjustable focus for clarity in images. Easy setup with 200mm cables, compatible with Raspberry Pi 3 and 4. Why Choose the Raspberry Pi AI Camera? On-board Edge AI processing with the Sony IMX500 sensor. Performs real-time object detection and image classification directly on the camera. Frees up Raspberry Pi’s CPU for other tasks. High-resolution 12MP imaging with excellent clarity and detail. Seamless compatibility with Raspberry Pi boards via CSI interface. Ideal for smart vision, robotics, and real-time monitoring projects. Energy-efficient and optimized for continuous AI operation. Comparison: Raspberry Pi AI Camera vs Camera Module 3 Feature Raspberry Pi AI Camera Raspberry Pi Camera Module 3 Sensor Sony IMX500 (with built-in AI processor) Sony IMX708 (high-quality image sensor) Resolution 12 Megapixels (4056 × 3040) 12 Megapixels (4608 × 2592) AI Processing On-board Edge AI inference support No AI processing, relies on Raspberry Pi CPU Field of View Approx. 76° (Standard Lens) Wide and Standard versions available Frame Rate Up to 60 fps (lower at full resolution) Up to 120 fps (lower resolution modes) Focus Type Fixed focus Autofocus Connectivity CSI Interface CSI Interface Special Features Built-in neural network accelerator for object detection and classification Excellent low-light performance and HDR support Best For AI vision, robotics, and smart automation High-quality photography and video capture Applications Smart Surveillance and Security Systems Object and Face Recognition Projects Automated Quality Inspection in Manufacturing Traffic and Vehicle Monitoring Systems Smart Retail and Customer Analytics AI-Powered Robotics and Drones Wildlife and Environmental Monitoring Home Automation with Vision Detection

reComputer J4012-Edge AI Device with NVIDIA Jetson Orin™ NX 16GB module reComputer J4012 is the perfect solution for advanced AI applications. It is compact, expandable, high-performing, durable, easy to integrate, versatile, and of high quality. reComputer J4012 ensures the highest quality and durability. Its NVIDIA Jetson Orin NX 16GB module provides up to 100 TOPS AI performance and guarantees exceptional computing power. The aluminum case and cooling fan offer optimal performance and longevity, making it suitable for industrial conditions and perfect for robust applications. Our reComputer J4012 is easy to use with pre-installed JetPack 5.1 on 128GB NVMe SSD and designed to solve complex AI tasks. Features: Brilliant AI Performance for production: on-device processing with up to 100 TOPS AI performance with low power and low latency Hand-size edge AI device: compact size at 130mm x120mm x 58.5mm, includes NVIDIA Jetson Orin™ NX 16GB production module, a cooling fan with a heatsink, enclosure, and a power adapter. Support desktop, wall mount, fit in anywhere Expandable with rich I/Os: 4x USB 3.2, HDMI 2.1, 2xCSI, 1xRJ45 for GbE, M.2 Key E, M.2 Key M, CAN, and GPIO. Accelerate solution to market: pre-installed Jetpack with NVIDIA JetPack™ 5.1 on the included 128GB NVMe SSD, Linux OS BSP, 128GB SSD, support Jetson software and leading AI frameworks and software platforms Comprehensive certificates: FCC, CE, RoHS, UKCA Applications: Autonomous Robots & Drones Smart Surveillance Systems Industrial Automation & Inspection Edge AI Computing AI-Powered Retail & Smart Cities Healthcare Imaging & Diagnostics Generative AI Applications Autonomous Vehicles & ADAS Prototyping Agricultural Monitoring Systems AI Research & Model Deployment Comparison Table: reComputer J4012 vs reComputer J2022 Feature reComputer J4012 reComputer J2022 AI Performance 100 TOPS (with NVIDIA Jetson Orin NX 16GB) 21 TOPS (with NVIDIA Jetson Xavier NX 16GB) Module / SoM NVIDIA Jetson Orin NX 16GB NVIDIA Jetson Xavier NX 16GB Memory 16GB LPDDR5, 128-bit, 102.4 GB/s bandwidth 16GB LPDDR4x, 128-bit, 59.7 GB/s bandwidth GPU / Architecture Ampere architecture, 1024-core GPU with 32 Tensor Cores Volta architecture, 384-core GPU Storage 128GB NVMe SSD + M.2 Key M slot 16GB eMMC 5.1 + M.2 Key M slot for SSD Form Factor & Dimensions 130mm × 120mm × 58.5mm 130mm × 120mm × 50mm Power Input 9–19V DC input via barrel jack 12V/5A via barrel jack or terminal block Target Applications High-end edge AI, multiple video streams, advanced robotics, generative AI Entry to mid-level edge AI, smart devices, vision analytics, small deployments