Flame Detector Cloud Diagnostics Using Fire Replay
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Solution Overview
Problem
Flame detectors in work environments often experience high processing communication latency times, leading to delayed diagnostics and increased false alarms, which hampers in-field performance and customer trust due to the lengthy communication pathways between the detectors, operators, and customers.
Innovation Solution
A communication system utilizing cloud-based remote diagnostics and the Fire Replay Technique, combined with wireless communication devices, enables efficient data transmission and analysis, allowing for real-time processing and reduction of latency by directly uploading data from flame detectors to a cloud database for immediate analysis by the development team.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional communication pathways are used between flame detectors, operators, and customers, then device complexity is reduced, but processing communication latency increases
Solution Approach 1:
The patent introduces a cloud-based communication intermediary that mediates between flame detectors, operators, and customers. This cloud platform receives data from detectors, processes diagnostics, and communicates with stakeholders, thereby reducing communication latency while managing system complexity through a centralized intermediary service.
Solution Approach 2:
The patent transitions from traditional linear communication pathways to a multi-dimensional cloud-based architecture. Data can be transmitted and processed through multiple channels and layers simultaneously (direct upload, remote access, automated notifications), reducing latency by utilizing parallel communication dimensions rather than sequential pathways.
2Loss of time
If remote diagnostics with cloud-based processing are implemented, then processing communication latency is reduced, but device complexity increases
Solution Approach 1:
The flame detector system performs self-diagnostic functions by automatically uploading its own operational data and fault information to the cloud platform. This self-service capability reduces the need for manual intervention and accelerates diagnostic processing, while the complexity is managed by having the detector autonomously handle data preparation and transmission.
Solution Approach 2:
The system continuously collects and pre-processes diagnostic data in the background before issues arise. When a problem occurs, the diagnostic information is already prepared and immediately transmitted to the cloud platform, eliminating delays associated with data collection and preliminary analysis, thus reducing overall processing time.
3Productivity
If real-time data transmission is implemented, then diagnostic speed is improved, but loss of energy increases
Solution Approach 1:
Instead of continuous real-time transmission, the system implements periodic data transmission at strategically determined intervals and trigger events. This approach maintains diagnostic speed by transmitting data when changes occur or at regular intervals, while significantly reducing energy consumption compared to uninterrupted continuous transmission.
Solution Approach 2:
The system dynamically adjusts transmission parameters such as data sampling rate, transmission frequency, and data volume based on operational conditions. During normal operation, transmission occurs at lower rates to conserve energy, while during critical events or anomalies, the system increases transmission frequency and detail, optimizing the balance between diagnostic speed and energy consumption.
Data Source
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AI summary
A communication system (100) comprising: a central server (134) configured to: access an event data from a cloud database (140), wherein the event data corresponds to ambient characteristics, associated with a detected event, detected by one or more flame detectors (102), wherein the ambient characteristics include at least one of amount of electromagnetic radiation, fire pic data, and audio data in a field of view of the one or more flame detectors (102); analyze the event data and identify an error with the one or more flame detectors (102) using a fire replay technique; and generate and communicate instructions to the one or more flame detectors (102) for automatically correct the error in the one or more flame detectors (102).