Autonomous Camera Threat Detection With Safety Response Metrics
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Solution Overview
Problem
The rise in public threat events involving weapons being brandished and the need for rapid remediation using security cameras is unaddressed, along with the requirement for increased awareness of safety levels in crowded areas to reduce casualties.
Innovation Solution
An autonomous threat detection and safety response system using cameras to detect threat events and generate safety responses, including safety alerts and metrics, utilizing multimodal models for insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If security cameras are used to monitor areas, then detection capability is improved, but response time and effectiveness are insufficient without autonomous response generation
Solution Approach 1:
The system enables autonomous threat response generation where the computing device automatically analyzes threat event information from cameras and generates safety responses without human intervention. The system serves itself by autonomously completing the full workflow from detection to response generation, eliminating delays associated with manual analysis and decision-making.
Solution Approach 2:
The system pre-configures multiple safety response templates and decision-making algorithms in advance. When a threat event is detected, the system can immediately deploy pre-prepared response strategies, avoiding the time required for real-time analysis and decision-making from scratch.
2Reliability
If autonomous safety response generation is implemented, then response effectiveness is improved, but system complexity increases
Solution Approach 1:
The autonomous system is divided into distinct functional modules: threat detection module (camera), information processing module (computing device), response generation module, and communication module. Each module performs a specific function, making the complex system manageable through modular design and enabling independent optimization of each component.
Solution Approach 2:
The computing device serves as an intermediary between the camera system and the safety response execution. It processes threat event information, generates appropriate responses, and communicates with other systems, simplifying the overall architecture by centralizing the decision-making function in a dedicated intermediary component.
3Measurement precision
If safety context factors are monitored, then safety metric accuracy is improved, but data processing requirements increase
Solution Approach 1:
The system extracts only the most relevant safety context factors from the environment, such as crowd density, presence of emergency exits, and vulnerable populations, rather than processing all possible data. This selective extraction approach maintains safety metric accuracy while significantly reducing the volume of data that requires processing.
Data Source
AI summary
A method includes providing a camera proximate a safety zone, wherein the camera is configured to detect a threat event in the safety zone, providing a computing device configured to generate a safety response based on threat event information, detecting, by the camera, a first threat event, generating, by the camera, a first set of threat event information based on the first threat event, receiving, by the computing device, the first set of threat event information, generating, by the computing device, a first safety response based on the first set of threat event information, and initiating the first safety response.