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Portwell PJAI-100-ON rugged Edge AI embedded system features NVIDIA Jetson Orin Nano for industrial quality control

Portwell PJAI-100-ON

Portwell has launched the PJAI-100-ON, a rugged and compact embedded system powered by the NVIDIA Jetson Orin Nano SOM and designed for demanding industrial environments. It operates reliably across a wide temperature range of -20Β°C to 60Β°C with a fanless, quiet design that requires minimal maintenance. Equipped with dual Gigabit Ethernet LAN ports and M.2 slots for wireless connectivity, the PJAI-100-ON is tailored for Edge AI applications. This system enhances quality control in manufacturing by using advanced optical inspection technology to detect defects, improving quality assurance and reducing production errors. Previously, we covered other Jetson Orin Nano embedded systems, including Aetina’s AIE-KO21, AIE-KO31, AIE-KN31, and AIE-KN41 and DFI X6-MTH-ORN fanless Edge AI Box computer, as well as Portwell’s WEBS-21J0-ASL another rugged embedded system built around an Intel Atom x7000RE Amstom Lake Nano-ITX motherboard and equipped with an Hailo-8 AI accelerator. Portwell PJAI-100-ON specifications: SoM – NVIDIA Jetson Orin Nano CPU [...]

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Seeed Studio at Smart City Expo 2024: Empowering the Future of Urban AI Hardware Solutions

By: Elaine Wu

Join Seeed Studio at Smart City Expo World Congress (SCEWC) 2024 in Barcelona! As urban areas worldwide continue to evolve, the demand for smarter, more connected solutions is driving advancements in AI hardware and edge AIoT.

From November 5-7 at Gran Via, Hall 2, Booth F71, we’re excited to showcase our latest lineup of sensing, networking, and edge AI devices, designed to transform cities through real-time data, seamless connectivity, and high-speed AI processing at the edge.

1. AI Sensors: Multimodal Sensing for a Smarter Environment

A smart city depends on the ability to sense, monitor, and respond to its surroundings. Our AI sensors offer versatile environmental monitoring, long-range connectivity, and advanced scene detection. With over 100 open-source, pre-trained models, these sensors bring multimodal sensing to urban spaces, capturing data from air quality to traffic flow in real time to support an adaptable and responsive city environment.

Stay Connected in Remote Areas

Offering 4G, 5G, or WiFi connection even in remote areas, SenseCAP Card Tracker T1000-E is the world’s first IP65-rated Meshtastic device. Compact and card-sized, it easily fits in your pocket or attaches to assets, operating seamlessly on the Meshtastic LoRa mesh network. It offers high-precision, low-power positioning and communication. Additionally, the T1000-E features onboard sensors to provide temperature and light data, making it ideal for remote connectivity in unpredictable environments.

2. AI Gateways for Seamless Connectivity and Control

Cities are powered by data, and our AI IoT gateways function as hubs for data collection and connectivity. These gateways provide versatile connectivity options and advanced AI capabilities, collecting, processing, and distributing data across urban areas. By facilitating real-time adjustments and insights, our AI gateways help cities operate more efficiently and respond instantly to changing conditions.

3. Generative AI at the Edge with reThings Devices Powered by NVIDIA Jetson Orin

With reThings, powered by NVIDIA Jetson Orin modules, you can now deploy generative AI directly to the edge. Supporting advanced generative AI models such as Llama, LLaVA, and VLA, these devices push the boundaries of robotics intelligence and multimodal interactions. The deployment of generative AI at the edge enables cities to integrate more interactive and autonomous systems, streamlining everything from traffic management to public safety.

Develop Generative AI-Powered Visual AI Agents for the Edge

Powered by NVIDIA Jetson Orin modules, which deliver up to 275 TOPS AI performance for edge AI and robotics, visual AI agents can help unlock new possibilities for real-time video analytics in urban settings. These agents can analyze both recorded and live video, answer questions in natural language, summarize scenes, trigger alerts, and extract actionable insights. They support a wide range of applications, from object detection to security monitoring, making it easier to maintain safety and efficiency across city landscapes.

Jetson Platform Services (JPS) provides an AI service that allows optimized visual language models (VLMs) to run locally on the NVIDIA Jetson platform. This AI service can be combined with other components of JPS to build a mobile app integrated alert system. This system is capable of monitoring live streams for user-defined events and sending push notifications when the VLM detects the events.
Combined Vision AI and Generative AI with reCamera and Jetson Orin.


reCamera, our newly released vision AI platform, delivers next-gen video intelligence when paired with Jetson Orin. This configuration, running NVIDIA Metropolis software development kits for vision AI applications and VLMs, provides building blocks to quickly deploy fully functional systems for vision and other edge AI applications. Using the β€œTinyML + LLM” architecture demonstrated at NVIDIA GTC earlier this year, reCamera captures critical frames while Jetson Orin extracts insights through a VLM. For instance, if a user asks, β€œHow many objects are in front of me on the right?”, the system will automatically adjust the camera with a gimbal, capture an image, and respond via speaker: β€œThere are 3 objects in front of you on the right.” This seamless integration of vision and generative AI provides real-time, context-aware insights.

Join Us at Smart City Expo 2024

Explore how Seeed Studio’s AI hardware and edge AIoT solutions can transform urban spaces at Smart City Expo 2024. From multimodal sensing to generative AI at the edge, Seeed is here to empower the cities of tomorrow. Stop by Booth F71 in Hall 2 to see our demonstrations, connect with our team, and discover how our hardware solutions can help create a more connected, efficient, and responsive urban landscape.
πŸ“… Date: November 5-7, 2024
πŸ“ Location: Gran Via, Hall 2, Booth F71

We look forward to connecting with you at SCEWC 2024 and advancing the future of smart cities!

The post Seeed Studio at Smart City Expo 2024: Empowering the Future of Urban AI Hardware Solutions appeared first on Latest Open Tech From Seeed.

Giveaway Week 2024 – Mixtile Core 3588E development kit with RK3588 SoM

Mixtile Core 3588E Ubuntu 22.04 review

Day 4 of Giveaway Week 2024 will be for a development kit comprised of the Mixtile Core 3588E SoM based on Rockchip RK3588 octa-core Cortex-A76/A55 SoC and a Leetop A206 carrier board compatible with NVIDIA Jetson SO-DIMM modules. This development kit is mostly useful to evaluate the Mixtile Core 3588E system-on-module, but it can be used just like any Rockchip RK3588 SBC with the company providing a Ubuntu 22.04 Desktop image for the board. Since it relies on the same edge connector as the NVIDIA Jetson TX2 NX module, the Core 3588E module can also be connected to other compatible carrier boards. I reviewed the Mixtile Core 3588E development kit last December running Ubuntu 22.04. At the time, I found the Mixtile Core 3588E system-on-module performs well with the pre-loaded Ubuntu 22.04 image with a similar performance as on other Rockchip RK3588 hardware platforms. 3D graphics acceleration was working with [...]

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Orbbec Gemini 335Lg 3D depth and RGB camera features MX6800 ASIC, GMSL2/FAKRA connector for multi-device sync on NVIDIA Jetson Platforms

Gemini 335Lg 3D Camera

The Orbbec Gemini 335Lg is a 3D Depth and RGB camera in the Gemini 330 series, built with a GMSL2/FAKRA connector to support the connectivity needs of autonomous mobile robots (AMRs) and robotic arms in demanding environments. As an enhancement of the Gemini 335L, the 335Lg features a GMSL2 serializer and FAKRA-Z connector ensuring reliable performance in industrial applications requiring high mobility and precision. The Gemini 335Lg integrates with the Orbbec SDK, enabling flexible platform support across deserialization chips, carrier boards, and computing boxes, including NVIDIA’s Jetson AGX Orin and AGX Xavier. The device can operate in both USB and GMSL (MIPI) modes, which can be toggled via a switch next to the 8-pin sync port, with GMSL as the default. The GMSL2/FAKRA connection provides high-quality streaming with synchronized multi-device capability, enhancing adaptability for complex setups. Previously, we covered several 3D cameras from Orbbec, including the Orbbec Femto Mega 3D [...]

The post Orbbec Gemini 335Lg 3D depth and RGB camera features MX6800 ASIC, GMSL2/FAKRA connector for multi-device sync on NVIDIA Jetson Platforms appeared first on CNX Software - Embedded Systems News.

NVIDIA Jetson Orin NX development kit comes with up to 16GB RAM, 128GB NVMe SSD, WiFi 5

Jetson Orin NX AI Development Kit

Waveshare’s Jetson Orin NX Development Kit is an AI edge computing platform tailored for robotics and AI-driven applications built around the NVIDIA Jetson Orin NX module 8GB/16GB delivering up to 70 TOPS and 100 TOPS of AI performance, respectively. It features the JETSON-ORIN-IO-BASE base board, which provides essential interfaces like an M.2 socket, DisplayPort (DP) video output, and USB ports, making it easy for users to connect multiple sensors and peripherals for high-performance AI tasks. The kit includes a 128GB NVMe SSD for high-speed storage and comes pre-installed with the AW-CB375NF wireless network card, which supports dual-band Wi-Fi 5 and Bluetooth 5.0. The Jetson Orin NX module operates within a configurable power range of 10W to 25W, delivering up to 5x the performance of the Jetson Xavier NX module. This development kit is suitable for large-scale AI projects requiring multiple concurrent inference pipelines and high-speed data processing. Previously, we covered [...]

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Firefly introduces Rockchip RK3576 SoM and All-in-One carrier board compatible with NVIDIA Jetson Orin Nano and Orin NX modules

AIO 3576JD4 Mainboard or devboard

Firefly has released a Rockchip RK3576 SoM and development board called the Core-3576JD4 Core Board with a SO-DIMM edge connector and the AIO-3576JD4 carrier board respectively. The core board or the SoM is built around an octa-core 64-bit processor with a Mali G52 MC3 GPU and a 6 TOPS NPU, so it can handle demanding AI tasks while maintaining low power consumption. The AIO-3576JD4 is a full-fledged carrier board with a wide range of on-board interfaces, like dual Gigabit Ethernet ports, MIPI-CSI, HDMI 2.1, USB 3.0, USB 2.0, USB Type-C, a Phoenix connector for serial, dual-row pin headers (SPI, I2C, Line in, and Line out), an M.2 socket for 5G, a mini PCIe for 4G LTE, an M.2 socket for WiFi 6/BT 5.2, and a third M.2 socket for SATA/PCIe NVMe SSD expansion. RK3576 AI SoM and dev board specification Core-3576JD4 specifications SoC – Rockchip RK3576 CPU – Octa-coreΒ  CPU [...]

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Vecow RAC-1000 rugged Edge AI systems feature NVIDIA Jetson AGX Orin, waterproof ports, GMSL2 camera connectors

Vecow RAC 1000 Jetson AGX Orin computing system

Vecow’s RAC-1000 series Edge AI systems are powered by NVIDIA Jetson AGX Orin 32GB or 64GB system-on-modules, offering up to 275 TOPS of AI performance. These systems are energy-efficient and come with rugged I/O options and an IP67-rated enclosure, making them suitable for AI and robotics applications such as automated agricultural machinery, construction automation, and mobile robotics in extreme outdoor conditions. The series includes two models: the RAC-1000, which supports 8 GMSL2 cameras through FAKRA-Z connectors for autonomous mobile robots, agricultural vehicles, and ADAS; and the RAC-1100, which features 6 GigE LAN ports with 4 PoE+ for vision AI applications. Both models are built for industrial environments and support various AI-driven tasks. As you may know, we’ve previously covered several Vecow AI computing systems, including EAC-5000, EVS-3000, TGS-1000 Series, SPC-9000 fanless embedded system, ECX-3200, and EPBC-1000. Feel free to explore these options if you’re interested. The Vecow RAC-1000 series specifications: [...]

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