Anemometer Network for Intrusion Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Security systems in high-value facilities face increased vulnerability during power outages, as video surveillance is often powered down to conserve energy, compromising the detection of unauthorized access.
Innovation Solution
A computer-implemented method using a network of anemometers to detect anomalies in airflow patterns, allowing for the identification of objects within a space without the need for continuous power, by creating a baseline airflow profile and comparing it to real-time data to determine the presence of intruders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If video surveillance systems are powered down to reduce power consumption during power outages, then energy usage is reduced, but security detection capability deteriorates
Solution Approach 1:
The patent replaces the electronic video surveillance system with an acoustic-based intrusion detection system that uses microphones and signal processing to detect intruders. This substitution allows the system to operate with minimal power consumption while maintaining security detection capability during power outages.
Solution Approach 2:
The system uses passive acoustic monitoring without requiring active illumination or power-intensive components. Intruders themselves generate the detection signals through their movements and actions, eliminating the need for active probing or illumination systems that would consume additional power.
2Measurement precision
If video surveillance systems are used to maintain security monitoring, then detection accuracy is improved, but power consumption increases
Solution Approach 1:
The patent substitutes the power-intensive video camera system with acoustic sensors and signal processing algorithms. The system achieves intrusion detection by analyzing sound waves and acoustic patterns, requiring minimal power while maintaining detection accuracy through sophisticated signal analysis rather than visual capture.
Solution Approach 2:
The system uses low-power acoustic sensors instead of expensive, power-hungry video surveillance equipment. The detection methodology relies on processing acoustic signals that are inherently present in the environment, eliminating the need for continuous operation of high-power imaging systems.
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
This solution enables continuous monitoring of high-value facilities without significant power consumption, reducing vulnerability by accurately detecting and tracking objects, even in low-power conditions, thereby enhancing security without the need for constant video surveillance.
Implementation Method 1
receiving, by a computer communicatively connected to a plurality of anemometers positioned throughout the space, first sensor data from the plurality of anemometers
Data Source
AI summary
A computer-implemented method, a system, and a computer program product for detecting objects are disclosed. The method can include receiving, by a computer communicatively connected to a plurality of anemometers positioned throughout the space, first sensor data from the plurality of anemometers, creating a baseline profile of airflow in the space based on the first sensor data, and receiving second sensor data from the plurality of anemometers at a different time than the first sensor data. The method can include comparing the second sensor data with the first sensor data to determine first different data, rendering, in response to determining that the second sensor data is different from the first sensor data, a representation of the object using the first different data and first location data related to the first different data, and calculating a vector associated with the object using the first different data and the first location data.