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Accelerate Computer Vision Solution with Shabodi’s Network-Aware AEP

Network Aware Deep Learning Use Case

Computer Vision technology is not new. It utilizes machine learning techniques and aids in analyzing digital media like photos and videos, benefiting industries with use cases such as industrial quality control, surveillance, augmented reality, and autonomous vehicles, among others. Recently, it has emerged as one of the leading enterprise applications of 5G networks. The fusion of 5G and computer vision amplifies digital transformation, extending its reach beyond traditional sectors like manufacturing and logistics to newer domains.

Consider a scenario where real-time media is crucial for business operations. Here, network reliability is paramount. Although 5G promises all the features the scenario demands, the convergence of computer vision, 5G, and network-aware applications can do more. The combination enhances the accuracy of the application and user experience by understanding all the network parameters, guaranteeing the success of computer vision even in challenging network conditions. Therefore, this synergy boosts confidence in enterprise private 5G adoption across industries like manufacturing, mining, ports, and entertainment.

Shabodi believes that working with the ecosystem is critical to bring vertical appl ications to private 5G customers. As a part of this effort, Shabodi enabled a network-aware video analytics solution that enhances video analytics accuracy and performance through the 5G network’s Quality on Demand (QoD) service invoked through Shabodi’s simplified API.

Download the Solution Brief to know more about:


Detailed benefits of network-aware AI/ML-driven solutions


The solution applicability across diverse industries


Potential outcomes from partnering with Shabodi


Download an example of network-aware computer vision using Intel’s OpenVINO Toolkit

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