Ready-made GStreamer AI plugins for fast processing at the Edge

Modern call centers and Business Process Outsourcers (BPOs) increasingly rely on video for customer service. Agents often work from home or in dense hubs using thin clients and virtualized desktops (DaaS & VDI). In these environments, video calls could expose distracting backgrounds and reduce perceived trust. A solution would require applying professional branding to all company agents’ screen backgrounds and allowing central management by the IT team without increasing server-side costs. However, integrating these solutions into DaaS & VDI environments poses a significant technical challenge due to the complexities of real-time video redirection and resource constraints.

In highly regulated sectors such as healthcare, finance, and government, the shift to remote work has introduced significant security liabilities. A remote worker’s webcam background could accidentally broadcast sensitive information, such as patient data on a whiteboard, confidential financial charts, or unauthorized personnel in the frame. Traditional server-side background removal solutions require raw, unedited physical video to traverse the network before AI processing, creating risks of accidental data breaches and regulatory non-compliance. While endpoint-based solutions can sanitize video before it enters the network, they face two primary hurdles: first, standard DaaS and VDI protocols do not natively recognize these processed streams as valid local camera devices; second, the intensive AI processing required often exceeds the computational capacity of thin clients and consumer hardware.

Traditional digital signage often delivers static content regardless of who is watching. This use case explores integrating AI-powered audience measurement to transform passive displays into interactive, adaptive marketing tools. By leveraging edge-based computer vision, displays would identify viewer demographics and engagement levels in real time.

The proposed solution would enable advertisers to serve highly relevant content based on the immediate audience profile. This approach would not only increase conversion rates but also provide granular analytics on campaign performance, all while maintaining strict data privacy through on-device processing.

In large-scale industrial facilities, such as steel factories and heavy manufacturing plants, maintaining strict control over personnel movement is a critical requirement for both safety and operational efficiency. The presence of unauthorized staff in hazardous zones or prolonged exposure to dangerous areas (loitering) poses significant risks of workplace accidents and regulatory non-compliance.

Most facilities still rely on traditional CCTV and manual oversight. However, human-led monitoring could lead to critical flaws in safety strategy, such as attention fatigue, risk response latency and blind spots causing coverage gaps.

To comply with EU-OSHA guidelines and the Framework Directive 89/391/EEC on health and safety at work, industrial leaders are moving toward proactive, automated systems. Computer vision would turn your cameras into active safety tools, getting a full picture of the floor in real-time, with a system that identifies and stops unauthorized access before it leads to an accident.