Solutions >   5G AI Video Analytics


AI-powered video analytics involves the use of machine learning algorithms to analyze video footage in real-time to detect, classify, and respond to various objects and events. AI systems are increasingly adopted across various use cases including factories (Industry 4.0), stadiums, airports, law enforcement, retail and critical infrastructure, to enhance experience, safety, security, and operational efficiency.

Some Applications of 5G Video Analytics Using AI

  • AI algorithms can be trained to recognize and detect specific objects or entities in video feeds. This can include identifying people, vehicles, animals, or even specific objects of interest such as weapons inside a stadium or defects in products in a factory's assembly line.

  • AI-powered video monitoring can perform facial recognition to identify individuals in the video footage. This can be used for security and access control, as well as for tracking the movement of specific individuals in a monitored area.

  • AI can analyze the behavior of objects or people in video streams to detect unusual or suspicious activities. This is particularly useful for security applications, such as identifying trespassing, loitering, or other suspicious behavior.

  • AI algorithms can be trained to detect specific events or actions, such as vehicle accidents, fires, break-ins, or crowd disturbances. This enables real-time alerts and rapid response to critical situations.

  • AI can track the movement of objects or people across multiple camera feeds, providing a comprehensive view of events and activities.

  • AI-powered video monitoring systems can create virtual boundaries or zones and trigger alerts when an object or person enters a restricted area.

  • Machine learning algorithms can identify anomalies or irregular patterns in video data, such as unexpected changes in traffic flow, unauthorized access to secure areas, or unusual behaviors.

  • AI can analyze historical video data to make predictions or identify trends. For example, it can help retailers optimize store layouts based on customer traffic patterns or assist in traffic management and urban planning.

  • AI-driven video monitoring plays a crucial role in smart city initiatives, enabling efficient traffic management, waste management, and public safety enhancements.

  • Real-time video streaming at an event (e.g. basketball game, music festival) can overlay or edit video (image and frames) frames with AI-processed content such as:
    - Replay Injection
    - Profanity Censoring (Obscene, Indecent and Profanities)
    - Targeted Ads

Vertically Integrated 5G AI Video Analytics Solution

Bloxtel can drastically improve the efficiency of your Video Analytics.

For customers subscribed to our Standard services, a state-of-the-art 5G AI stream processing server is integrated in the Operator dApp and allows to capture real-time video streams, create detection events (e.g. weapon, anomaly) and plan automated actions (e.g. notify security guards, notify robots in the assembly line, annotate).

With ultra-reliable and low-latency built into your private 5G network, AI-powered video analytics can be performed in real-time at the edge (without data traffic transiting through a mobile network's core in the cloud). This significantly reduces latency with more frames being processed via ML models.

  • Dropped frames during AI video processing refers to a situation in which an AI-powered video processing system fails to process and display some frames of a video stream. Dropped frames can occur for various reasons and can impact the quality and smoothness of the video output. This is generally due to network latency where video is transmitted over a traditional mobile network for processing while network congestion or packet loss lead to dropped frames during transmission.
Depending on your backhaul's speed setup (e.g. Fiber, Ethernet), 80% latency reduction means that you can go from 100ms to 20ms in a typical setup and from 500ms to 100ms in a poor setup. In all cases, that's more time to process those extra defects (and improve yield) in your assembly line at a factory site; find a person of interest, weapon or a bomb at a school, residential/office building, sporting/music venue; track conditions like soil health, pests, and crop quality in your farm; or just improve user-experience for your XR apps at any large, crowded indoor site.

 
 
 


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