Edge AI for Video Analytics and IoT Edge AI for Video Analytics and IoT

The Flexible Edge AI Platform for Fast Computer Vision

Embedded Vision, Radically Improved

Designed for video analytics and IoT applications, the Chooch Edge AI Platform can be deploy computer vision in minutes and delivers responses every few milliseconds on a variety of platforms with high accuracy.  Standard AI models and applications are prepackaged for remote devices and ready now.

The Chooch Edge AI Platform provides embedded vision for many solutions in AIoT, geospatial, safety and security, media, healthcare, retail and more – from workplace safety to touchless check-in, fall detection to inventory analysis. Any visual task can be replicated with AI training and be quickly added to existing video systems.

Chooch AI provides complete solutions, from data collection, to AI training, to  deployments. Edge AI is managed from the cloud, with standard AI models and custom AI models that include image classification, object detection, facial authentication, action logging, tracking and more.

  • Chooch Edge AI inference engine generates responses in milliseconds, and processes multiple video feeds simultaneously
  • Standard AI models are ready now and customer AI models are quickly trained and deployed
  • Chooch AI Integrates with industry leading NVIDIA GPU processors designed for AI and robotic applications
  • Edge devices and cameras are remotely managed and updated from the Chooch AI Dashboard

Need To Deploy Fast, Accurate Edge AI?

Chooch Edge AI Deployments

Chooch offers standard AI models for many general use cases, including common requirements such as PPE detection, demographic analysis, and fall detection. All AI models and applications are dockerized and installed remotely from the Chooch Edge AI Platform to devices with NVIDIA GPUs to provide fully functional edge AI in minutes.

Chooch AI can also generate and deploy new AI models with training data that is very quickly processed. The results are custom AI models with high accuracy. These AI models can be trained for further iterations when deployed into client environments. 

All Chooch AI models are installed remotely onto GPU-based devices, which are purpose-built for AI and robotics applications. These lightweight devices easily integrate with existing video systems.

Video Resource

Watch a short 15-minute presentation that explains the Edge AI Platform and the entire process from dataset generation to edge AI deployment.

Watch Now

EDGE DEVICE CAPABILITIES AND MANAGEMENT

Even the smallest of these edge devices, the NVIDIA Jetson Nano, is capable of running multiple models with multiple classes in each model.  Chooch’s edge AI inference engines generate highly accurate responses in milliseconds and process simultaneous feeds per device. 

With the edge AI platform, users can remotely manage and update all of their edge devices from a single tool on the Chooch AI dashboard, including connecting cameras to their edge devices. Depending on your use case, you can configure your edge AI devices to generate alerts or send JSON response outputs to business intelligence and analytics tools.

  • Learn more about setting up an Edge Device Deployment on a PC or Jetson device.
  • What are Edge Devices? A device that is physically located close to the source of the data and performs computations itself rather than sending data to the cloud.

What is Edge AI?

Edge computing is a paradigm in which you perform as much computation as possible on “edge” devices that are located close to the source of the data, rather than on remote servers running in the cloud.

There are many advantages edge computing has over a “traditional” Internet of Things and cloud computing, especially with computer vision because there’s no need to send video and images to the cloud when you can process data on the edge.

  • Edge devices increase data privacy and security by storing data locally instead of in the cloud.
  • Edge computing has lower latency than cloud computing, since you don’t have to wait for results to return from the cloud.
  • For the same reason, edge computing can be cheaper than cloud IoT: you don’t have to pay for additional data traffic and cloud computing. 
  • Edge computing can be more reliable than cloud IoT in the event of an outage that disrupts operations in the cloud.

Thanks to recent technological advancements in GPUs, it’s become easier to run powerful AI models on the edge, a trend which is expected to accelerate in the next few years.  Chooch AI has unique capabilities deploying and managing AI models in complete packages on the Edge.

  • What is Edge Computing? Edge computing is the use of “edge” devices that are physically located close to data sources, rather than in a remote location in the cloud.

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