Autonomous Emergency Detection via Distributed Sensor Validation
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Solution Overview
Problem
Existing emergency response systems rely on central authorities for emergency identification and communication, which can fail in areas without such infrastructure, leading to delayed or ineffective responses.
Innovation Solution
A method and system where smart devices autonomously detect sensor abnormalities, communicate directly with nearby devices via various networks, validate the data, and initiate emergency calls if a match is confirmed, ensuring rapid response without reliance on central systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a centralized emergency response system is used, then emergency information can be stored and controlled by a central authority, but the system fails in areas without central infrastructure and causes delayed responses
Solution Approach 1:
The centralized emergency response system is segmented into distributed autonomous devices. Each device independently monitors its local environment using sensors and can autonomously detect emergencies without relying on a central authority. This segmentation eliminates the single point of failure in centralized systems and enables operation in areas without central infrastructure.
Solution Approach 2:
Devices are equipped with autonomous capabilities to self-monitor, self-detect, and self-report emergencies. Each device independently validates sensor data against pre-stored reference parameters and can autonomously initiate emergency responses, eliminating the need for centralized control and enabling operation in remote areas.
2Loss of time
If devices autonomously detect and communicate emergencies without central systems, then response time is reduced and reliability in remote areas is improved, but false alarms may increase due to lack of centralized validation
Solution Approach 1:
Devices implement feedback mechanisms where sensor data is continuously monitored and compared against pre-stored reference parameters. The system provides feedback loops that validate readings against thresholds and patterns, allowing autonomous devices to distinguish between actual emergencies and false alarm conditions without centralized validation.
Solution Approach 2:
Reference parameters, threshold patterns, and validation criteria are pre-stored in devices before emergencies occur. This preliminary preparation enables devices to immediately validate sensor readings and make accurate emergency determinations without needing real-time centralized validation, reducing response time while maintaining accuracy.
3Measurement precision
If multiple devices validate emergency data through cross-validation, then false alarms are reduced and detection accuracy is improved, but communication overhead and system complexity increase
Solution Approach 1:
Multiple devices merge their sensor data and validation results through standardized communication protocols. Devices share their emergency detections and reference parameter comparisons, combining individual validations into a collective determination. This merging approach improves detection precision through cross-validation while using standardized protocols to minimize communication overhead.
4Speed
If devices broadcast abnormal sensor data to all nearby devices, then emergency information is rapidly disseminated, but network bandwidth is consumed and false alarms may propagate
Solution Approach 1:
Devices perform partial broadcasting by sending emergency information only to a subset of nearby devices rather than all devices in range. The system uses selective communication based on proximity, relevance, and current network conditions, disseminating information rapidly to the most relevant devices while conserving network bandwidth and energy by avoiding unnecessary transmissions to distant or unrelated devices.
Data Source
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AI summary
The invention relates to a method, a system and a device for autonomously identifying an emergency, wherein the method comprising the steps of monitoring, by an application of a first device, sensor data from at least one sensor of the first device; detecting or receiving, by the application of the first device, an abnormality in the sensor data of the at least one sensor; initiating, by the application of the first device, the abnormality state, storing, by the application of the first device, the abnormal sensor data from the at least one sensor; generating, by the application of the first device, a message comprising the abnormal sensor data; broadcasting, by the application of the first device, the generated message to all further devices over all types of available networks.