Connected Vehicle Sensor Fusion for Hyper-Local Weather Verification
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Solution Overview
Problem
Conventional methods for confirming triggering events in parametric insurance policies, such as weather data exceeding predetermined thresholds, are often inefficient and cumbersome, lacking effective mechanisms for hyper-local verification.
Innovation Solution
A network of connected autonomous or 'smart' vehicles equipped with various sensors, along with passenger mobile devices and wearables, is utilized to crowdsource confirmation of weather events and other natural occurrences by determining and verifying environmental data proximity to a location of interest, leveraging machine learning models for accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional weather data sources are used to confirm triggering events, then the system is simple to operate, but the measurement precision and reliability are insufficient for hyper-local verification
Solution Approach 1:
The patent combines multiple data sources (weather satellites, environmental sensors in vehicles, mobile devices, and wearables) into a unified verification system. This merging of diverse sensors and data streams enables hyper-local measurement precision while distributing the complexity across multiple independent components rather than requiring a single complex centralized system.
Solution Approach 2:
The system utilizes multi-functional sensors that serve both their primary purposes (e.g., cameras for navigation, microphones for ambient noise detection) and secondary purposes (confirming weather events and natural occurrences). This universality allows the system to achieve high measurement precision without adding dedicated complex verification infrastructure.
2Reliability
If a network of connected vehicles with sensors is deployed for crowdsource confirmation, then the reliability and measurement precision improve, but the device complexity and cost increase
Solution Approach 1:
The system leverages existing infrastructure (vehicles with onboard sensors, mobile devices, wearables) that already possess the necessary sensing capabilities for their primary functions. These devices self-serve the additional purpose of weather event confirmation without requiring complex dedicated verification infrastructure, thereby improving reliability while minimizing added system complexity.
Solution Approach 2:
Instead of deploying dedicated verification sensors at every location, the system uses copies of existing sensing capabilities found in vehicles, mobile devices, and wearables. This approach achieves high reliability through multiple distributed measurement points without the complexity of installing and maintaining specialized verification equipment.
3Measurement precision
If environmental sensors are permanently installed at locations of interest, then the measurement precision is high, but the cost and device complexity increase significantly
Solution Approach 1:
The system replaces expensive permanent sensor installations with temporary, mobile sensing resources from vehicles, mobile devices, and wearables. These existing devices already contain the necessary sensors (cameras, microphones, environmental sensors) and can provide hyper-local measurement accuracy without the high deployment and maintenance costs of permanent infrastructure.
Solution Approach 2:
The system utilizes sensors from devices that serve multiple purposes (navigation, entertainment, communication, ambient monitoring) to also perform weather event verification. This multi-functionality eliminates the need for dedicated permanent verification sensors, significantly reducing deployment costs while maintaining high measurement precision.
Data Source
AI summary
Techniques for using connected vehicles as secondary data sources to confirm weather data and other triggering events are provided, including (1) determining indication of a weather event associated with a location of interest; (2) receiving indications of location data captured by location sensors associated with vehicles (such as vehicle-mounted sensors and/or mobile devices, virtual headsets, or wearables of passengers); (3) comparing the location data captured by the location sensors to a location of interest in order to identify one or more vehicles within a proximity of the location of interest; (4) receiving environmental sensor data captured by environmental sensors associated with one or more of the identified vehicles; and (5) determining, based upon the environmental sensor data captured by the environmental sensors associated with the one or more of the identified vehicles, an indication of an accuracy of the indication of the weather event associated with the location of interest.