AR System Integrating Multivariable Sensors for Environmental Risk Detection
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Solution Overview
Problem
Current augmented reality systems lack integration with environmental sensors to efficiently and reliably detect and mitigate environmental risks, limiting their application in meaningful and immersive experiences.
Innovation Solution
An augmented reality system integrated with multivariable sensors that visualize sensor data, providing actionable information and corrective procedures, utilizing gas-selective multidimensional detectors capable of detecting multiple gases and interferences, with data analytics and AI-driven inference engines for accurate risk assessment and response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If augmented reality systems are integrated with environmental sensors to detect and mitigate environmental risks, then detection capabilities and reliability are improved, but device complexity increases
Solution Approach 1:
The patent combines multiple sensor types (gas sensors, temperature sensors, humidity sensors) and augmented reality components into a single integrated system. The sensor module, processing module, and display module are merged into one device that can detect environmental risks and provide augmented reality feedback simultaneously, improving reliability while managing complexity through integration.
Solution Approach 2:
The augmented reality system is designed to perform multiple functions: detecting gas concentrations, monitoring temperature, measuring humidity, analyzing environmental data, and providing visual feedback through augmented reality. This multi-functional approach allows a single system to address various environmental risks without requiring separate specialized devices for each function.
2Measurement precision
If multivariable sensors are used to detect multiple gases and interferences, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The sensor module is divided into multiple independent sensor units, each specialized for detecting specific gases or environmental parameters. The processing module then segments the data from each sensor and analyzes them separately before integrating the results, which improves measurement precision for each parameter while managing overall system complexity through modular architecture.
Solution Approach 2:
The system utilizes sensors that can detect multiple parameters simultaneously (gas concentration, temperature, humidity) and changes in these parameters over time. By monitoring parameter changes and patterns rather than relying on a single measurement, the system achieves higher precision in identifying environmental risks and distinguishing between different gas types and interference sources.
3Productivity
If AI-driven inference engines are implemented for accurate risk assessment, then productivity is improved, but use of energy increases
Solution Approach 1:
The system pre-processes sensor data using filtering algorithms and pattern recognition techniques before feeding it to the AI inference engine. By performing preliminary data cleaning, normalization, and feature extraction, the system reduces the computational burden on the AI engine, enabling faster risk assessment while consuming less energy during the critical inference phase.
Solution Approach 2:
The AI-driven inference engine operates periodically rather than continuously, analyzing sensor data at optimized intervals based on environmental conditions and risk levels. During normal conditions, analysis occurs at lower frequency to conserve energy, while during elevated risk conditions or when anomalies are detected, the system increases analysis frequency to improve productivity and response time.
Data Source
AI summary
A method and system to receive information from at least one multivariable sensor, each multivariable sensor being deployed in an environment, having internet connectivity to communicate with at least one other device over the internet, and selectively determining at least one attribute of multiple events in its environment; receive an indication of a location of the multivariable sensor; receive an indication of a location of an augmented reality device; determine an alarm based on the received information from the at least one multivariable sensor; determine a location for the alarm and a location of a solution associated with the alarm; and present, in a field of view display on the augmented reality device, a visualization of the determined alarm and at least one of the determined location for the alarm and the determined location for the solution associated with the alarm.