Fiber Optic Smoke Detection with Cloud Localization
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Solution Overview
Problem
Conventional smoke detection systems using fiber optics can delay in detecting smoke or airborne pollutants and fail to accurately identify the source location, lacking the capability to differentiate between hazardous and non-hazardous conditions.
Innovation Solution
A computer-implemented method that receives data from multiple areas, including scattered light and time of flight information, to determine the status of each area and transmit notifications, utilizing a system with primary and collimating nodes to identify the source location of smoke or pollutants and differentiate between hazardous and non-hazardous conditions through polarization and collimating signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional smoke detection systems are used, then the system structure is simple, but the detection speed is slow and source location cannot be identified
Solution Approach 1:
The detection system is divided into multiple nodes distributed throughout the monitored space, with each node independently detecting smoke conditions. This segmentation enables parallel detection across multiple locations simultaneously, improving overall detection speed while maintaining manageable complexity through modular architecture.
Solution Approach 2:
The system transitions from single-point detection to multi-dimensional spatial detection by distributing nodes throughout the space and using time-of-flight measurements to add a temporal dimension. This enables both faster detection through parallel monitoring and precise source location identification through spatial-temporal analysis.
2Measurement precision
If conventional detection systems are used, then the device complexity is low, but the measurement precision of source location is insufficient
Solution Approach 1:
The system adds temporal dimension through time-of-flight measurements to the spatial distribution of detection nodes. By measuring the time it takes for smoke to reach different nodes and analyzing the spatial-temporal pattern of detection, the system achieves precise source location identification without requiring complex mechanical positioning systems.
Solution Approach 2:
The system uses scattered light as an intermediary carrier to transmit information about smoke presence and location. By analyzing the characteristics of scattered light detected at multiple nodes, the system can precisely determine source location without direct contact with the smoke, reducing system complexity while maintaining high measurement precision.
3Reliability
If high sensitivity fiber optic detection systems are used, then real-time detection is achieved, but the capability to differentiate hazardous from non-hazardous conditions is insufficient
Solution Approach 1:
The detection system segments the analysis by assigning different detection nodes to monitor specific areas and conditions. Each node can be configured to detect particular hazard types, allowing the system to reliably differentiate between various hazardous and non-hazardous conditions through distributed, specialized monitoring rather than requiring complex centralized analysis.
Solution Approach 2:
The system implements feedback mechanisms where detection results from multiple nodes are continuously analyzed and compared. By evaluating the spatial-temporal patterns of detections and using feedback loops to refine analysis, the system achieves reliable differentiation between hazardous and non-hazardous conditions while managing analytical complexity through iterative processing.
4Reliability
If conventional detection systems are used, then the device complexity is low, but false alarms occur frequently
Solution Approach 1:
By distributing detection across multiple nodes throughout the space, the system can segment false alarm sources and identify their specific locations. This spatial segmentation allows the system to distinguish between genuine hazards requiring alarm and localized non-hazardous conditions, improving alarm accuracy while maintaining manageable system complexity through modular node architecture.
Solution Approach 2:
The system uses the additional temporal dimension provided by time-of-flight measurements to differentiate between hazardous and non-hazardous conditions. By analyzing how detection signals evolve over time and propagate through space, the system can reliably distinguish true threats from false alarm sources, reducing false alarms without requiring overly complex analysis 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
Enables real-time detection and accurate identification of smoke or pollutant sources, reducing false alarms and improving response times by providing precise location information and distinguishing between hazardous and non-hazardous conditions.
Implementation Method 1
These known high sensitivity smoke detection systems with fiber optics typically use a primary detection node for whole area detection and a secondary node, commonly referred to as a localization or collimated node, for localization based on a spatial index relative the density of the smoke or the airborne pollutant.
Implementation Method 2
receiving from multiple areas data associated with the presence of one or more conditions at a plurality of nodes within each area, wherein the data received from each area comprises a signal including scattered light and time of flight information associated with a corresponding plurality of nodes
Implementation Method 3
the data received from each area comprises an accumulated data stream wherein the accumulated data stream comprises polarization horizontal and vertical laser signals from a primary node
Data Source
AI summary
A detection system for measuring one or more conditions within an area. At least one fiber optic cable transmits light wherein the at least one fiber optic cable defines a plurality of nodes arranged to measure the one or more conditions. A control system communicates with the at least one fiber optic cable such that scattered light and a time of flight record is transmitted from the at least one fiber optic cable to the control system. The control system includes a detection algorithm operable to identify a portion of the scattered light associated with each of the plurality of nodes. When determining an alert, the control system transmits data associated with a presence and magnitude of the one or more conditions at each of the plurality of nodes to a cloud computing environment and, in return, receives a notification based on the data transmitted.