Automated Threat Detection Using AI Behavior Analysis
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Solution Overview
Problem
Existing security apparatuses are prone to error and fail to adequately distinguish between genuine threats and harmless bystanders, such as children, and are often biased, making them inadequate for comprehensive security solutions.
Innovation Solution
An automated threat detection and deterrence system utilizing a combination of sensors, including imaging, acoustic, radar, and lidar, along with a processor that employs machine-learning algorithms to analyze behavior descriptors and object recognition, to differentiate between threats and non-threats, and employs a graduated deterrence system that can escalate responses from warnings to incapacitating measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated security apparatuses are used to detect threats, then productivity and response speed are improved, but measurement precision deteriorates leading to errors in distinguishing threats from bystanders
Solution Approach 1:
The system segments threat detection into multiple independent analysis components: behavior analysis module, biometric verification module, contextual data module, and risk assessment module. Each module processes specific aspects independently and their results are integrated to form a comprehensive threat assessment, improving both speed and accuracy
Solution Approach 2:
The system introduces AI/ML algorithms as intermediary processors between sensor detection and threat classification. These algorithms analyze patterns, behaviors, and contextual factors to mediate between raw sensor data and final threat determination, enhancing measurement precision while maintaining automated response speed
2Measurement precision
If human security personnel are deployed, then measurement precision in threat assessment improves, but device complexity and cost increase
Solution Approach 1:
The system replaces human security personnel with an automated electronic system comprising sensors, processors, and actuators. The complex human cognitive processes of threat assessment are substituted with AI/ML algorithms that analyze multiple data streams and make automated decisions, reducing operational complexity while maintaining or improving assessment accuracy
Solution Approach 2:
The automated system is designed to perform multiple functions: detection, identification, classification, decision-making, and deterrence execution. This multi-functional integration consolidates what would require multiple specialized human roles into a single unified system, reducing overall system complexity
3Ease of operation
If existing security apparatuses are used, then ease of operation is maintained, but reliability deteriorates due to errors and biases
Solution Approach 1:
The system incorporates continuous feedback loops where sensor data, behavioral analysis results, and outcome data are constantly fed back to the AI/ML algorithms. This enables real-time adjustment and optimization of detection parameters, reducing errors and biases while maintaining automated operation and ease of use
Solution Approach 2:
The system dynamically adjusts detection parameters, sensitivity thresholds, and analysis weights based on contextual information and learned patterns. This adaptability allows the system to maintain high reliability across varying conditions while requiring minimal manual intervention or tuning
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system reduces errors and biases, enabling precise and proportional responses to threats while minimizing harm to bystanders, providing a cost-effective and reliable security solution that can detect and deter multiple individuals simultaneously with minimal physical impact.
Implementation Method 1
detection and sensing component consisting of one or more sensors, including, but not limited to, imaging
Implementation Method 2
acoustic... sensors, configured to detect and track a subject in a subject area
Implementation Method 3
radar... sensors, configured to detect and track a subject in a subject area
Implementation Method 4
lidar... sensors, configured to detect and track a subject in a subject area
Implementation Method 5
time-of-flight... sensors, configured to detect and track a subject in a subject area
Data Source
AI summary
An automated threat detection and deterrence apparatus includes an imaging device configured to detect a subject in a subject area, a deterrent component including a directed light deterrent, wherein the directed light deterrent includes a first deterrent mode and a second deterrent mode, the directed light deterrent is configured to perform a first deterrent action on the subject when in the first mode, the directed light deterrent is configured to perform a second deterrent action on the subject when in the second mode, and a processor communicatively connected to the imaging device and the deterrent component, wherein the processor is configured to identify the subject as a function of the detection of the subject, determine a behavior descriptor associated with the subject, select one of the first deterrent mode and the second deterrent mode and command the directed light deterrent to perform an action based on the selection.