What is Edge Computing Concept?

What is Edge Computing Concept?

Edge computing is gaining popularity as more IoT devices are deployed and 5G fast connectivity is introduced. Edge computing brings compute, storage, and analytics closer to the source of data and is transforming how billions of devices around the world handle, process, and send data. The increasing proliferation of internet-connected devices (the IoT), as well as new applications that require real-time computing capability, are driving the growth of edge computing systems.

The arrival of real-time applications that necessitate edge processing is moving the technology ahead. Due to the rise of IoT-generated data, one of the first goals of edge computing were to reduce the cost of bandwidth for data navigating vast distances. The goal is to make it possible to send data from one location to another in a matter of seconds.

Edge Computing

Edge computing is a type of computing in which processing power and data storage are brought closer to the source of the data. Edge computer systems, in most cases, can process data locally without ever connecting to the internet. This is because data is analyzed locally, which allows the edge computer to make real-time decisions in milliseconds.

Edge AI Computing

Edge AI computing involves running AI algorithms locally on an edge AI computer that is close to the data source being processed by the algorithm. AI Edge computing is advantageous because it allows you to process data in milliseconds rather than seconds in the cloud, providing you with real-time data and decision-making skills for machine learning intelligence.

Benefits of Edge AI Computing

• Real-time data processing
• Privacy
• Reduction in Internet Bandwidth
• Less Power


NVIDIA® Jetson AGX Xavier™ Edge AI Platform

Edge AI computers powered by NVIDIA® Jetson AGX Xavier™ from Neousys offer considerable inference performance while requiring only 30W of electricity. The NRU Series is completely fanless and capable of operating at a wide range of temperatures thanks to Neousys' excellent thermal design.

The NRU is suitable for various mobile deployments and edge AI applications since it can be installed with a damping bracket, has ignition power control, and supports wide-range voltage power input.

The NRU series also supports a wide range of cameras, including IP, GigE, and GMSL cameras. It also has a plethora of interfaces that can connect to various sensors to fulfill perception and planning functions on the same platform, making it ideal for AI-based vision applications that require continuous interactions with the environment, such as UGV/AMR, predictive maintenance, law enforcement, intelligent V2X, and so on.

NRU Series Platforms

NRU Series Core Features

30W Fanless Edge AI Computer

NRU Series has GPU computing power equivalent to 120W graphic cards while consuming only 30W of power, thanks to the design of NVIDIA® Jetson AGX Xavier™.

Robust and Reliable

The NRU series can operate in temperatures ranging from -25°C to 70°C due to its unique mechanical and thermal design. Furthermore, it features a patented dampening bracket that can absorb shock and vibration in harsh environments.

Camera Support

The NRU series supports IP, GigE, and GMSL cameras to serve a wide range of edge computing image analysis applications, including visual defect detection, security monitoring, autonomous machines,etc.

Ready for Mobile/ In-Vehicle Applications

The NRU Series offers a variety of in-vehicle capabilities, including ignition control, CAN bus, DIO, and one mini-PCIe socket for a WiFi/ 4G module, making it ideal for mobile or in-vehicle deployments.

Applications

The NRU series can be utilized as an AI NVR (Network Video Recorder) all-in-one solution. To accomplish analytic findings with recognizing, identifying, and finding objects in an image utilizing a deep learning neural network on a GPU computer, for example, law enforcement, security alert, dangerous object detection, etc.

The NRU series can be utilized as an AI NVR (Network Video Recorder) all-in-one solution. To accomplish analytic findings with recognizing, identifying, and finding objects in an image utilizing a deep learning neural network on a GPU computer, for example, law enforcement, security alert, dangerous object detection, etc.

V2X communication is a critical component of the future ITS design. The NRU can be positioned by the roadside as an edge AI platform in a smart city for real-time traffic analysis, accident detection, or function as autonomous driving sensors to provide cars with comparable edge AI technology with a preview of traffic conditions ahead.


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