Sensor Network False Alarm Validation
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Solution Overview
Problem
Intrusion detection systems are prone to false alarms due to their inability to differentiate between human and animal movements or determine the location of objects, leading to unnecessary alerts and resource wastage for alarm monitoring companies, building owners, and law enforcement.
Innovation Solution
The implementation of a sensor device with event sensors, processors, memory, and metadata analysis capabilities that communicate with other sensors in a peer-to-peer network to validate alarm conditions, combining raw data from various sensors to generate a composite event signal that accurately identifies true alarm conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If simple binary signals from sensors are used to indicate alarm conditions, then the system is easy to operate and install, but the system generates false alarms due to inability to differentiate between human and animal movements or determine object location
Solution Approach 1:
The patent combines data from multiple sensors (motion detectors, cameras, proximity sensors) to create a composite event signal. The control panel receives and analyzes data from several sensor types simultaneously, merging their outputs to make a unified alarm determination. This combination allows the system to cross-validate signals and reduce false alarms while maintaining ease of operation.
Solution Approach 2:
The patent adds temporal and contextual dimensions to alarm detection by analyzing sequences of events and metadata from multiple sensors. Instead of relying on a single binary signal, the system examines the timing, pattern, and context of sensor activations across different dimensions, enabling differentiation between legitimate intrusions and false alarm sources.
2Reliability
If multiple sensors are combined to validate alarm conditions and reduce false alarms, then the reliability of alarm detection is improved, but the device complexity increases
Solution Approach 1:
The patent segments the alarm validation function by assigning different validation tasks to different sensor types. Each sensor handles a specific aspect of detection (motion, visual confirmation, proximity), and the control panel segments the analysis by evaluating each sensor's data independently before integrating them. This segmentation manages complexity by creating modular, specialized detection components.
Solution Approach 2:
The control panel is designed as a universal device that can receive and process data from multiple types of sensors (motion detectors, cameras, proximity sensors). This multi-functional panel consolidates the complexity into a single device that handles various sensor protocols and validation logic, rather than requiring separate processing units for each sensor type.
3Measurement precision
If metadata analysis from multiple sensors is performed to distinguish true alarms from false alarms, then the measurement precision of alarm detection is improved, but the loss of time for data processing increases
Solution Approach 1:
The system performs preliminary filtering and validation of sensor data before full alarm processing. The control panel quickly checks metadata from multiple sensors to determine if an alarm condition warrants full investigation. This preliminary action reduces the time spent on false alarms by early-identifying and dismissing invalid signals before initiating time-consuming validation sequences.
Solution Approach 2:
The patent implements a multi-level processing approach where obvious false alarms are rapidly identified and skipped through simplified validation paths. When sensor data clearly indicates a false alarm condition (e.g., motion detected but no corresponding camera activation or proximity sensor confirmation), the system rushes through a quick dismissal process rather than performing complete multi-sensor validation, thus reducing time loss.
Data Source
AI summary
Embodiments of intrusion detection systems are described and which include an intrusion detection panel that receives binary and metadata sensor data from which the presence of an alarm condition is detected. In addition sensor devices analyze sensor data received from other sensor devices that are in a peer to peer relationship with the corresponding sensor device to validate whether the indicated alarm condition is a valid alarm or a false alarm.