IoT Camera Video Clip Prioritization via User Pattern Analysis
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Solution Overview
Problem
Users of IoT camera devices face inconvenience in identifying relevant video clips among numerous recordings, as existing systems lack the ability to prioritize or highlight clips of interest based on user patterns and irregular events.
Innovation Solution
An electronic device that stores user patterns from IoT devices, detects irregular events, and prioritizes video clips by matching these events with images captured by IoT cameras, allowing for preferential display and thumbnail updates reflecting user interests and event significance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If video clips are arranged in chronological order with thumbnails, then the complete record is preserved, but users cannot easily identify video clips of interest among numerous recordings
Solution Approach 1:
The system analyzes user interaction patterns with video clips (playback behavior, pause points, replay frequency) to generate feedback signals. This feedback is used to dynamically adjust the prioritization and presentation of video clips, allowing the system to learn and adapt to user preferences over time, thereby improving ease of identifying relevant clips without losing contextual information about user interest
Solution Approach 2:
The system changes the parameter of video clip presentation from simple chronological ordering to a composite ordering that incorporates multiple factors including user patterns, event types, and interaction history. This parameter transformation enables the system to prioritize and highlight video clips of interest while maintaining the complete chronological record in the background
2Reliability
If all video clips are displayed equally, then completeness is maintained, but important events are not highlighted
Solution Approach 1:
The system applies different quality levels of presentation to different video clips based on their importance. Important video clips containing detected events (motion, sound, object recognition) are highlighted with enhanced visual indicators, while less important clips maintain standard presentation. This local differentiation allows the system to maintain completeness while emphasizing important events
Solution Approach 2:
The system performs preliminary analysis of video clips to detect events and categorize them before presentation to the user. By pre-processing and tagging video clips with event information, the system can quickly identify and highlight important events during display without requiring users to manually review each clip, thus maintaining reliability while improving ease of operation
3Measurement precision
If users manually check each video clip to find content of interest, then accurate identification is achieved, but time consumption increases significantly
Solution Approach 1:
The system introduces an intermediary layer of automated analysis between the raw video clips and the user. This intermediary process uses machine learning models to predict user interest based on video content, metadata, and historical patterns, generating a prioritized presentation that maintains accuracy of identification while eliminating the need for users to manually check each clip, thus reducing time consumption significantly
Data Source
AI summary
An electronic device is provided. The electronic device includes a communication circuit configured to transmit and receive data to and from an external device, a memory, and a processor, wherein the processor may store a user pattern in the memory based on first sensing information detected during a first time period by at least one of an external camera device or an external Internet of things (IoT) device, detect occurrence of an irregular event based on second sensing information detected during a second time period by the external camera device or the external IoT device and the stored user pattern, match the irregular event that occurs with a plurality of images photographed by the external camera device, and determine priorities of the plurality of images based on a matching result.