IOTech and Lotus Labs Partner to Deliver AI and Visual Inference at the IoT Edge
September 01, 2021
An edge software platform combined with computer vision technology provides a more accurate real-time operational picture from the fusion of video analytics and conventional sensor data.
IOTech announced its partnership with Lotus Labs to deliver AI and visual inference solutions at the IoT edge. The partnership enables IOTech to integrate Lotus Labs’ computer vision technology into its edge software solutions.
This combination provides a functionality that is useful for companies building intelligent solutions across vertical use cases. These include loss prevention in retail, crowd management in entertainment venues, manufacturing component fault detection, COVID safe-distancing management, and smart safety systems within industrial plants.
The integrated solution will enable the data from conventional sensors and OT endpoints to be combined with the results from the latest AI and video inference technologies to provide an accurate real-time operational picture and make smarter decisions from the fusion of data.
IOTech has pilot programs underway at major sporting venues and anticipates soon deploying AI and visual inference solutions for a number of these.
Lotus Labs, based in Arizona, provides visual inference through its AI platform Padmé, which will be integrated with IOTech’s Edge Xpert. The solution will support a range of use cases including people counting, predictive maintenance, product quality checking and theft detection.
The global video analytics market size was valued at $4,102.0 million in 2019, and is projected to reach $21,778.0 million by 2027, registering a CAGR of 22.7% from 2020 to 2027.
IOTech’s Edge Xpert edge computing platform is supported by a pluggable open architecture for computer vision that allows users to run their AI algorithms and vision models. Edge Xpert allows users to control camera devices, collect video streams, and automatically apply AI and vision inference right at the edge. The platform supports deploying models that can include object detection, classification, and recognition; it passes the inference results to other services for real-time decision making.