IoT Sensor Fusion Coordinator for Context-Aware Risk Assessment
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Solution Overview
Problem
Current IoT systems lack the ability to seamlessly integrate personal and public devices to build a rich context and respond to user needs in real-time, especially in situations requiring holistic data analysis and emergency responses.
Innovation Solution
A personal IoT cloud system that utilizes a coordinator device to collect and process sensor data from both personal and public devices, employing a cascading sensor fusion mechanism to selectively access and integrate data from multiple tiers of sensors, enabling context-based responsive actions through a rule evaluation circuit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor data from multiple IoT devices is continuously collected and processed, then user safety and context awareness are improved, but power consumption and computational resources increase
Solution Approach 1:
The system segments sensor data processing into multiple tiers: first-tier sensors continuously monitored, second-tier sensors activated only when specific conditions are met. This segmentation allows the system to maintain safety monitoring while reducing continuous power consumption by activating additional sensors only when needed.
Solution Approach 2:
The system dynamically adjusts sensor activation and data processing intensity based on contextual conditions. The coordinator device evaluates user context and risk ratings in real-time, activating additional sensors and processing only when necessary, thereby optimizing the balance between safety monitoring and power consumption.
2Reliability
If sensor data from multiple IoT devices is continuously collected and processed, then user safety and context awareness are improved, but computational resources increase
Solution Approach 1:
The system segments computational processing into tiers matching the sensor hierarchy. First-tier sensor data is processed continuously with low computational overhead, while second-tier sensor data is processed only when contextual conditions trigger their activation, reducing overall computational resource requirements while maintaining safety.
Solution Approach 2:
The system performs partial processing by evaluating only the necessary subset of sensor data based on current user context and risk rating. Instead of continuously processing all available sensor data, the system activates and processes only the portion needed for current safety assessment, reducing computational burden.
3Reliability
If sensor data from multiple IoT devices is continuously collected and processed, then user safety and context awareness are improved, but network resources increase
Solution Approach 1:
The system segments network communication into tiers corresponding to sensor activation levels. First-tier sensors communicate continuously with minimal network overhead, while second-tier sensors transmit data only when activated by contextual conditions, reducing overall network resource consumption while maintaining safety monitoring capabilities.
Solution Approach 2:
The system employs periodic evaluation of user context and risk ratings to determine when additional sensor data collection and network transmission are necessary. Instead of continuous high-bandwidth communication, the system uses periodic assessments to trigger selective data collection and transmission, optimizing network resource usage.
Data Source
AI summary
Various systems and methods for Internet of Things (IoT) network sensor fusion are provided herein. A system for providing sensor collaboration includes: a sensor command circuit to access first-tier sensor data from a first-tier sensor associated with a user; a risk assessment circuit to use the first-tier sensor data to determine a risk rating, the risk rating representing a potential risk to the user; a user context circuit to determine a user context from the first-tier sensor data, wherein the user context circuit and the sensor command circuit are to selectively access second-tier sensor data from a second-tier sensor based on the user context; and a rule evaluation circuit to access a rule database to identify a rule corresponding to the risk rating and user context, and execute the rule when the rule is identified.