AI Video Trigger Storage for Missed Event Capture

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Solution Overview

Problem

Cameras often fail to capture important events as they require a record button to be pressed, leading to missed moments due to delayed user intervention.

Innovation Solution

Implementing a system with a camera, processor, and AI model in a computing device that continuously records video and uses AI to identify triggers such as user language, vocal pitches, and body language to automatically store or delete video portions, ensuring important events are captured and saved.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If a record button is required to start recording, then user control over recording is improved, but important events may be missed due to delayed user intervention

Engineering Contradiction:

Improveuser control over recordingVSAvoidcapture of important events

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

The system performs preliminary action by continuously recording video before the user presses the record button. The camera captures video in advance and the processor identifies triggers (such as detected events or conditions) to determine when to save portions of the video, ensuring important moments are captured even if the user delays pressing the record button.

Inventive Principle:

Principle #10Preliminary action

2Reliability

If continuous recording is implemented, then important events are captured reliably, but memory storage requirements increase

Engineering Contradiction:

Improvecapture of important eventsVSAvoidmemory storage requirements

Core Design Contradiction:

ReliabilityVSQuantity of substance

Solution Approach 1:

The system segments the continuous video stream into distinct portions based on trigger identification. The processor analyzes the continuous video and identifies specific segments that contain important events or triggers, then selectively saves only those portions to memory. This segmentation approach reduces the total amount of data stored while maintaining reliable capture of important moments.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system extracts and saves only the relevant portions of the continuous video stream that contain identified triggers or important events. By taking out only the necessary segments rather than storing the entire continuous recording, the system reduces memory storage requirements while maintaining reliable capture of important events.

Inventive Principle:

Principle #2Taking out (Extraction)

3Extent of automation

If AI trigger identification is used, then automated video management is improved, but device complexity increases

Engineering Contradiction:

Improvevideo management automationVSAvoidsystem complexity

Core Design Contradiction:

Extent of automationVSDevice complexity

Solution Approach 1:

The system implements self-service by using the AI model to automatically identify triggers and determine which video portions to save without requiring manual user intervention. The processor works with the AI model to autonomously analyze continuous video, detect triggers, and manage storage decisions, thereby achieving automated video management that reduces the need for user action.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS20240357052A1Storing video in memory

Publication Date: 2024.10.24 MICRON TECHNOLOGY INC

AI summary

The present disclosure includes apparatuses, methods, and systems for storing video in memory. In an example, an apparatus can include a memory, a camera, and a processor coupled to the memory and the camera, wherein the processor is configured to record video via the camera, store a first portion of the video for a first particular time period in the memory, and store a second portion of the video for a second particular time period responsive to a trigger.