Mobile Security Monitoring via Real-Time Video Baseline Comparison
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Solution Overview
Problem
Conventional security systems require manual activation and deactivation, leading to potential inadvertent triggering or failure in providing adequate security, especially when users forget to set them, and lack continuous monitoring of frequented areas for intrusions or safety issues.
Innovation Solution
A mobile device-based system utilizing real-time video analysis, including augmented reality, to capture and compare images of frequented areas, establishing a baseline layout and alerting users to changes, such as intruders or security compromises, through indicators and automated notifications to authorities or financial institutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional security systems are manually activated and deactivated, then the system can provide security protection, but the system may be inadvertently triggered or not activated at all due to user forgetfulness
Solution Approach 1:
The system automatically detects when the user has left the premises using location services and mobile device sensors, and autonomously activates security monitoring without requiring manual user input. The system serves itself by monitoring its own operational state and triggering security protocols based on detected conditions.
Solution Approach 2:
The system performs preliminary detection of user absence using GPS location data and movement patterns before a security threat can occur. By proactively identifying when the user has left the area, the system pre-activates security monitoring in advance, ensuring protection is already in place before any potential intrusion.
2Reliability
If security systems require manual setting every time the user leaves or enters, then the system can provide targeted security, but the user must constantly remember to set the system, leading to potential failures
Solution Approach 1:
The system maintains continuous security monitoring by automatically tracking user location and presence status. Rather than requiring periodic manual activation, the security function operates continuously in the background, seamlessly adapting to user presence and absence without interruption or manual intervention.
Solution Approach 2:
The system continuously receives feedback from mobile device sensors, location services, and environmental sensors to determine user presence and security conditions. This real-time feedback loop enables the system to automatically adjust its operational state, maintaining reliable security coverage without requiring user input or time for manual configuration.
3Measurement precision
If real-time video analysis is used to continuously monitor frequented areas, then security detection capability is improved, but energy consumption and processing requirements increase
Solution Approach 1:
The system performs video analysis periodically based on detected conditions rather than continuously. When the user's mobile device detects presence in a frequented area, the system activates video capture and analysis. When the user leaves, the system enters a lower-power state, performing analysis only at periodic intervals or when triggered by specific events, thereby reducing energy consumption while maintaining detection accuracy.
Solution Approach 2:
The system applies partial video analysis by focusing computational resources only on specific areas of interest or suspicious changes in the video stream. Rather than analyzing every frame in full detail, the system uses motion detection and change analysis to identify only the portions of video that require detailed examination, reducing overall processing requirements and energy consumption while maintaining intrusion detection accuracy.
Data Source
AI summary
System, method, and computer program product are provided for using real-time video analysis to provide the user of mobile devices with security, no matter the user's location. Through the use of real-time vision object recognition objects, logos, artwork, products, locations, and other features that can be recognized in the real-time video stream and frequented locations of the user can be established. In this way, a baseline layout of the frequented location is determined, such that the objects and individuals typically in the frequented area are recognized. The system may continue to take real-time video images of the frequented location, such that if a variation in the baseline layout occurs, the change may be alerted. In this way, a security compromise, such as a break-in to a user's home may be detected by the system and thus the system may notify the user or the appropriate authorities.