Crowdsourced Weather Data Collection via Vehicle Sensors
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Solution Overview
Problem
Current weather prediction methods face limitations due to the high cost and inefficiency of deploying additional satellites and weather stations, and the variability of data collection, leading to inaccurate and costly forecasts.
Innovation Solution
A computer-implemented method utilizing vehicle-based sensors to gather and aggregate weather data from a network of vehicles, providing real-time and predictive weather reports based on GPS coordinates, vehicle heading, and speed, allowing for cost-effective and accurate weather forecasting by leveraging crowdsourced data from millions of automobiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If more satellites are launched to improve weather prediction accuracy, then measurement precision is improved, but cost increases significantly
Solution Approach 1:
The patent repurposes vehicles already in use for transportation to serve dual functions: transportation and weather data collection. The vehicles' existing sensors (barometers, thermometers, hygrometers, anemometers) are utilized for weather monitoring, eliminating the need for dedicated expensive infrastructure while achieving widespread data coverage.
Solution Approach 2:
The system leverages vehicles that are already operating in the environment, using their own onboard sensors to collect weather data. The vehicles serve themselves by contributing data to the weather prediction network without requiring separate dedicated data collection infrastructure, thereby reducing overall system cost.
2Measurement precision
If more weather stations are built to improve local weather prediction accuracy, then measurement precision is improved, but cost increases
Solution Approach 1:
The patent transforms transportation vehicles into mobile weather stations, allowing a single vehicle to serve multiple locations throughout its route. This eliminates the need to build fixed weather stations at numerous locations, as moving vehicles naturally distribute measurement points across the service area, reducing infrastructure costs while maintaining or improving local prediction accuracy.
Solution Approach 2:
The system transitions from static fixed weather stations to dynamic mobile measurement points. Vehicles continuously move through the service area, providing real-time weather data from multiple locations. This dynamic approach allows flexible adaptation to changing weather patterns and provides more frequent updates compared to fixed stations.
3Stability of the object's composition
If fixed weather stations are used, then data collection is stable, but data coverage and responsiveness to changing weather conditions are limited
Solution Approach 1:
The patent introduces mobility to weather data collection by using vehicles that continuously move through the service area. This dynamic system naturally adapts to changing weather conditions by providing real-time data from multiple locations, capturing weather transitions and localized phenomena that fixed stations would miss, while maintaining stable data collection through consistent vehicle operation.
Data Source
AI summary
A computer-implemented method of gathering data includes querying, via a vehicle computing system, a plurality of weather sensors included with a vehicle and in communication with a vehicle network. The method also includes determining whether or not appropriate conditions exist for storage of data from the sensor, for each of the sensors. Additionally, the method includes storing the data from the sensor if appropriate conditions exist. Finally, the method includes sending, from the vehicle computing system to a remote network, data from one or more queried sensors and current GPS coordinates of the vehicle.