i-PRO “transforms” AI analytics development for edge cameras

Docker containers directly support i-PRO’s open platform development initiatives by providing a standardised way in which application developers can rapidly advance the AI capabilities of the company’s edge devices.

Docker provides a secure and ‘containerised’ environment in which to run custom applications, while in parallel facilitating easy integration with cloud services. The environment offers a protective barrier, duly preventing direct access to the core operating functions of the camera and ensuring cyber security, while also allowing maximum flexibility.

Using Docker containers enables the modularisation of different AI components. By encapsulating various functionalities within separate containers, it becomes easier to manage and maintain the overall system.

In addition, Docker allows for easy scaling of the AI components by running multiple instances of containers across distributed edge devices.

Reduced development cycles

“Thanks to Docker, third party app providers can reduce development cycles and costs to develop customised AI apps,” explained Hideo Noguchi, chief technical officer at i-PRO. “Docker containers make tailored analytics development far more accessible for everyone.”

Building applications couldn’t be easier. For example, Microsoft’s Azure Internet of Things (IoT) Edge allows developers to design intelligent apps in the cloud and deploy them directly to IoT devices using Docker containers.

A Docker layer not only improves accessibility for traditional analytics providers, but also extends a given camera’s utility as an IoT data collection point, thereby enabling companies to associate video and AI metadata with additional digital transformation initiatives.

AI innovations

With support for up to nine AI applications, the X Series line is “the most powerful AI camera to date” from i-PRO. It’s the first camera to support AI on-site learning, while also providing powerful AI features to additional non-AI network cameras.

AI on-site learning allows operators to teach the camera about unique objects they wish to identify, search for or track. For example, the camera might be taught to recognise a logo on a truck and send out an alert when it arrives at the loading dock. Likewise, it could count pallets being unloaded from a lorry.

The AI processing relay application enables a single X Series camera to add AI metadata to up to three additional, non-AI cameras (even including those from other manufacturers). This extends the useful life of network cameras that might be hard to reach and replace without realising any significant interruption to operations. Processing multiple AI-based analytics on the edge reduces the need for expensive back-end servers and, further, minimises notification delays.

*Further information is available online at https://i-pro.com/products_and_solutions/en/surveillance/products/new-products/new-x-series-camera-ai-site-learning-analytics

**Visit the i-PRO website at www.i-pro.com