Crowdsourced Camera Feed Selection for Real-Time Event Coverage
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Solution Overview
Problem
Existing methods for obtaining and processing image data from multiple users fail to effectively capture and utilize live image data from various vantage points during events, especially in emergency situations, as existing surveillance systems lack comprehensive coverage and real-time accessibility.
Innovation Solution
A method and system for determining a location of interest, establishing a geofence, and obtaining crowdsourced live image data from multiple camera devices, prioritizing views based on criteria such as proximity and user history, and sending prompt messages to users to enhance the representation of the event.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If traditional surveillance systems are used to monitor events, then system complexity is reduced and ease of operation is improved, but coverage area and measurement precision are insufficient
Solution Approach 1:
The patent transforms personal camera devices into multi-functional surveillance nodes that serve both personal purposes and public safety monitoring. Users capture events with their own devices while contributing to broader situational awareness, eliminating the need for dedicated surveillance infrastructure in every location.
Solution Approach 2:
The system leverages users' own camera devices and voluntary participation to provide surveillance coverage. Instead of deploying centralized surveillance systems, the patent enables individuals to serve themselves by capturing and sharing event data, which automatically contributes to the collective monitoring network.
2Reliability
If centralized surveillance systems are deployed to ensure real-time monitoring, then reliability is improved, but loss of time for data collection and device complexity increase
Solution Approach 1:
Users continuously capture and store event data in real-time using their personal devices, preparing the data infrastructure in advance. When an event of interest occurs, the data is already available for immediate retrieval and analysis, eliminating the need for time-consuming data collection during critical moments.
Solution Approach 2:
The system implements real-time feedback loops where captured image and video data are immediately processed, analyzed, and shared across the network. This continuous feedback mechanism ensures that monitoring reliability is maintained without time delays, as data flows continuously from capture to analysis to action.
3Measurement precision
If multiple camera devices are coordinated to capture events from various vantage points, then measurement precision and coverage are improved, but device complexity and difficulty of operation increase
Solution Approach 1:
The patent introduces a centralized server as an intermediary that automatically coordinates multiple camera devices. The server manages device communication, synchronizes data collection, and processes images without requiring users to manually coordinate their devices, thus maintaining operational simplicity while achieving multi-angle coverage.
Solution Approach 2:
The system divides the complex task of multi-device coordination into separate functional segments: individual users capture data with their devices, the server collects and organizes data from multiple sources, and automated processes analyze and integrate the information. This segmentation allows each component to remain simple while the system as a whole achieves high precision.
4Loss of information
If crowdsourced image data is collected from multiple users, then coverage area and information completeness are improved, but data processing complexity and loss of time increase
Solution Approach 1:
The system collects excessive data from multiple user devices beyond what a single surveillance camera would capture, ensuring complete event representation. Automated filtering and selection processes then extract only the most relevant information from this abundant data stream, maintaining information completeness while managing processing complexity through selective action.
Solution Approach 2:
The patent replaces manual data processing and selection mechanisms with automated computer vision and machine learning algorithms. These computational systems automatically analyze, filter, and prioritize crowdsourced image data, eliminating the need for manual processing while handling the complexity of integrating multiple data sources.
Data Source
AI summary
Methods, computer program products, and systems are presented and can include for instance: determining a location of interest; and obtaining image data from one or more camera device about the location of interest.