Firearm Safety Control System Using AI Target Classification
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Solution Overview
Problem
There is a need for a firearm safety control system that prevents unintentional discharge and shooting of nearby individuals by ensuring the firearm only fires at permitted areas, addressing the issue of accidental injuries and deaths caused by poor aim or unintentional firing.
Innovation Solution
A system comprising a camera, image recognition software, artificial intelligence, a chipset, micro-controller, processor, memory storage device, and a disabling mechanism that classifies targets into categories and determines lethality modes, preventing the firearm from firing if the user attempts to engage an area not permitted by the current mode.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a firearm safety control system with image recognition and AI software is implemented to prevent unintentional discharge, then safety and reliability are improved, but device complexity increases due to multiple components including camera, processors, and disabling mechanisms
Solution Approach 1:
The system divides the safety control function into separate modular components: image capture module (camera), image processing module (image recognition software), decision-making module (AI software), and execution module (disabling mechanism). Each module performs a specific function, allowing the complex safety system to be constructed from manageable, independent segments that can be developed, tested, and maintained separately.
Solution Approach 2:
The patent introduces an intermediary processing chain between the trigger pull and the firearm discharge. The camera captures target images, image recognition software processes these images to identify target characteristics, AI software makes lethality mode decisions based on the analysis, and only then is the disabling mechanism engaged or disengaged. This intermediary chain ensures safety decisions are made through multiple layers of analysis rather than direct mechanical connection.
2Measurement precision
If image recognition software and AI processing are used to classify targets and determine lethality modes, then shooting accuracy and target discrimination are improved, but processing time and response delay increase
Solution Approach 1:
The system performs preliminary image capture and analysis before the trigger is fully pulled. The camera continuously monitors the target area, and the image recognition software pre-processes images to identify potential targets and their characteristics. When the trigger is pulled, the AI software already has pre-analyzed data about the target, allowing for rapid lethality mode determination without requiring time-consuming analysis during the critical firing moment.
Solution Approach 2:
The system dynamically adjusts processing intensity based on situational context. For clearly identified targets with unambiguous characteristics, the AI software can make rapid decisions with minimal processing. For complex or ambiguous targets, the system increases analysis depth and may request additional image captures or angles. This dynamic processing approach optimizes the balance between accuracy and response time based on the specific situation.
Data Source
AI summary
The present invention relates to a firearm safety control system. The system is primarily comprised of at least one camera, at least one image recognition software, at least one artificial intelligence software, and at least one disabling mechanism. Using the camera, the image recognition software detects and classifies a target. The artificial intelligence software then determines what lethality mode the target can be engaged at. If a user attempts to engage an area of the target not permitted by the current lethality mode, the firearm will become disabled and will not fire.