Sensor Network Event Detection with Dynamic Mode Switching
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Solution Overview
Problem
Existing surveillance systems consume excessive power and computational resources as sensors remain active at all times, lacking adaptability to changing conditions and requiring a central hub for operation.
Innovation Solution
A sensor network comprising first and second sensors that detect events, generate messages, and adjust operation modes between sensitivity/power modes, allowing for energy-efficient operation without a central hub, with the second sensor switching modes based on messages from the first sensor and providing confirmation or negation of detected events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensors remain active at all times to ensure high sensitivity and readiness, then detection reliability is improved, but energy consumption increases significantly
Solution Approach 1:
The patent implements dynamic operation modes for sensors, allowing them to switch between active detection states and low-power states based on environmental conditions and event likelihood. Sensors adjust their operational parameters in real-time rather than maintaining constant high-sensitivity operation, resolving the contradiction between continuous readiness and energy conservation.
Solution Approach 2:
The system changes operational parameters of sensors based on detected conditions, adjusting sensitivity thresholds, sampling rates, and activation states dynamically. This allows the system to maintain adequate detection reliability while reducing energy consumption during periods of low activity or when environmental conditions indicate lower risk.
2Measurement precision
If a central hub processes all sensor signals to ensure comprehensive monitoring, then detection accuracy is improved, but computational complexity and system cost increase
Solution Approach 1:
The patent divides the monitoring system into autonomous sensor nodes that each perform local signal processing and event assessment. Instead of one central hub processing all data, each sensor independently evaluates its own detections and communicates only relevant findings to neighbors, distributing computational complexity and reducing system cost while maintaining detection accuracy.
Solution Approach 2:
Sensor nodes are equipped with embedded processing capabilities that allow them to autonomously assess their own detection signals, filter false positives, and make local decisions about when to activate or communicate. This self-service approach reduces the burden on centralized processing and simplifies the overall system architecture.
3Measurement precision
If sensors operate in high-sensitivity mode continuously to ensure accurate event detection, then measurement precision is improved, but power consumption increases
Solution Approach 1:
The patent implements periodic sampling and event-driven activation where sensors switch between high-sensitivity detection modes and low-power states. Sensors activate at regular intervals or in response to triggering conditions, maintaining measurement precision when needed while consuming minimal power during idle periods between events.
Data Source
AI summary
A sensor network comprising a first sensor (104) and a second sensor (101, 108), characterized in that: the first sensor (104) and the second sensor (101, 108) are configured to detect an event and to generate a message (M1, M2, M3) corresponding to the detected event; and wherein the sensor network is configured to provide an assessment of the message (M1) from the first sensor (104) based on the message (M2, M3) from the second sensor (101, 108).