Automated Live Video Feed Selection via Transponder Sensor Data
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Solution Overview
Problem
The need for an automated system to produce a live video stream from multiple live video feeds of events without requiring a production staff, as many events cannot afford the expense of dedicated camera and editing crews.
Innovation Solution
An automated system that connects multiple video devices and transponders to a cloud-based server, using sensor data to select and switch between live video feeds based on measured properties such as location, speed, and heart rate, allowing for real-time streaming and user preference-driven video selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple video devices and transponders are connected to a cloud-based server for automated live stream production, then the quality and contextual value of the live streaming video is improved, but the device complexity and network infrastructure requirements increase
Solution Approach 1:
A cloud-based server acts as an intermediary between multiple video devices/transponders and end users. The server receives, processes, and distributes video feeds and sensor data, automating the production process while managing system complexity centrally rather than distributing it across multiple devices
Solution Approach 2:
The cloud-based server performs multiple functions: receiving video feeds from multiple cameras, processing sensor data from transponders, selecting optimal video feeds based on contextual data, and distributing streams to multiple users simultaneously. This multi-functionality consolidates complexity into a single platform
2Adaptability or versatility
If automated selection algorithms use sensor data from transponders to select video feeds in real-time, then the adaptability and user experience are improved, but the processing requirements and computational complexity increase
Solution Approach 1:
The system processes only the essential sensor data and video feed parameters needed for automated selection, rather than analyzing all possible data from transponders and cameras. This partial processing approach achieves real-time adaptability while conserving computational resources
Solution Approach 2:
Video feeds and sensor data are pre-processed and organized on the cloud server before real-time selection is needed. This preliminary organization reduces the computational burden during live event processing, enabling faster and more energy-efficient real-time decision-making
3Productivity
If multiple streaming video feeds are incorporated into a live mesh for automated editing, then the productivity and coverage of event documentation is improved, but the complexity of video processing and editing increases
Solution Approach 1:
The system performs automated video selection and switching based on sensor data and pre-defined criteria, eliminating the need for human editors to manually monitor and switch between multiple feeds. The system serves itself by making intelligent decisions about which video feed to prioritize based on real-time event data
Data Source
AI summary
Provided is an automated system and process for producing a live video stream from a plurality live video feeds of an event from different views utilizing a transponder that measures a variable property of a person or animal participating in the event or a device that moves in the event, or the computer determines the measurement of the variable property utilizing pixels from the live video feeds. The computer 150 automatically selects a live video stream to broadcast from the plurality of live video stream to a user interface 120 based on the measurement.