Intrusion Detection System Using RSSI and Camera Tracking
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Solution Overview
Problem
Current network surveillance and intrusion detection systems fail to accurately identify the physical location of intruders and computer devices, especially in environments with obstacles and dynamic changes, leading to false positives and limitations in automated camera targeting.
Innovation Solution
A system that ties digital information to physical characteristics by using RSSI, time of signal travel, calibration mapping, supervised learning algorithms, camera surveillance, and servo systems to determine and track the location of both stationary and non-stationary devices, and automatically adjust camera angles for precise identification and monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional intrusion detection systems are used, then network security monitoring is provided, but the physical location of intruders and devices cannot be accurately identified
Solution Approach 1:
The patent combines multiple detection technologies (RSSI-based wireless signal location, time-of-flight measurement, and camera surveillance) into a unified intrusion detection system. This integration allows the system to simultaneously obtain digital information from network monitoring and physical characteristics from location and visual data, thereby accurately identifying both the digital and physical identities of intruders.
Solution Approach 2:
The patent introduces calibration mapping as an intermediary component that creates a correspondence between wireless signal measurements (RSSI, time of flight) and physical locations. This calibration map serves as a mediator that translates digital signal data into accurate physical location information, enabling precise identification of intruder positions without direct line-of-sight measurement.
2Extent of automation
If RSSI measurements are used for location determination, then wireless device positioning is achieved, but obstacles and dynamic environmental changes cause false identification
Solution Approach 1:
The patent performs calibration mapping in advance, before actual intrusion detection occurs. During the calibration phase, the system pre-establishes the relationship between wireless signal characteristics and physical locations in the environment, storing this information for later use. This preliminary action allows the system to account for environmental features and obstacles beforehand, improving reliability during automated detection without requiring real-time environmental assessment.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously compares measured signal strength and time of flight values against the pre-established calibration map. When discrepancies are detected due to environmental changes or obstacles, the system can identify these as potential false positives and adjust its location determination accordingly, thereby maintaining high reliability in dynamic environments.
3Measurement precision
If camera surveillance is used to monitor physical location, then visual identification is provided, but manual camera adjustment is required and automated targeting is limited
Solution Approach 1:
The patent replaces manual mechanical camera adjustment with automated electronic control based on computational data. The system uses the determined physical location coordinates from RSSI and time-of-flight measurements to automatically calculate and command the camera's positioning and orientation, eliminating the need for manual operation and enabling rapid, precise automated targeting of detected intruders.
4Reliability
If multiple security measures are implemented, then comprehensive monitoring is achieved, but system complexity increases
Solution Approach 1:
The patent designs the intrusion detection system to perform multiple functions through a unified architecture. The same hardware components (wireless receivers, cameras, processors) are used for both network intrusion detection and physical location identification, eliminating the need for separate specialized systems and reducing overall complexity while maintaining comprehensive security monitoring capabilities.
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
Accurately identifies the physical location of intruders and devices, reduces false positives, and enables automated camera targeting, enhancing security measures in dynamic environments.
Implementation Method 1
A system that ties digital information to physical characteristics by using RSSI, time of signal travel
Implementation Method 2
A system that ties digital information to physical characteristics by using RSSI, time of signal travel
Data Source
AI summary
An apparatus including an intrusion detection arrangement and a location identification arrangement which ties digital information (i.e. transaction events such as parameters of information, database queries, transaction ranges, etc.) submitted to a computer system with the physical characteristics of the event such as the picture of the person(s) originating the information.