Vehicle Audio Sensing for Localized Precipitation Detection
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Solution Overview
Problem
Traditional weather stations may not provide accurate and granular weather data, especially in areas lacking nearby stations, and crowd-sourced sensors can lead to false positives for adverse weather conditions.
Innovation Solution
A method using audio signals from multiple sensors on a vehicle to determine the presence and severity of precipitation, processing frequency and amplitude data through an algorithm to generate outputs on precipitation conditions and confidence measures, which can adjust vehicle operational states and transmit data to service providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional weather stations are used to gather weather data, then weather information can be obtained for historical trend data and current weather reporting, but the data may only approximate the weather at a location and may not be readily available or accurate in areas lacking nearby stations
Solution Approach 1:
Vehicles equipped with audio sensors autonomously detect precipitation conditions themselves and report the data, rather than relying on centralized weather stations. The vehicle's audio sensor system independently identifies precipitation sounds and transmits location-tagged data to a service provider, enabling self-service weather monitoring at the point of need
Solution Approach 2:
Instead of relying on physical weather stations at every location, the system creates virtual copies of weather monitoring capability through vehicles distributed across the landscape. Each vehicle acts as a mobile weather station, copying the monitoring function to locations where traditional stations do not exist
2Measurement precision
If crowd-sourced sensors are used to provide granular weather estimations, then more localized weather data can be obtained, but the sensors may erroneously report conditions resulting in false-positives for adverse weather conditions
Solution Approach 1:
The system uses multiple audio sensors on the vehicle to detect precipitation, requiring multiple independent detections before confirming adverse weather conditions. This partial action approach reduces false positives by not relying on a single sensor reading but rather requiring corroboration from multiple sensors or repeated detections
Solution Approach 2:
The system transmits precipitation condition data with location information to a service provider, creating a feedback loop where data from multiple vehicles can be aggregated and validated. The service provider can cross-reference reports from multiple sources to verify actual precipitation conditions and reduce false positives through collective validation
Data Source
AI summary
Embodiments described herein provide a method for using one or more audio signals from one or more sensors to establish the presence and severity of precipitation at a particular location. Methods may include: receiving at least one first audio signal from a first audio sensor of a vehicle; extracting acoustical features including frequency and amplitude from the at least one first audio signal; receiving at least one second audio signal from a second audio sensor of the vehicle; extracting acoustical features including frequency and amplitude from the at least one second audio signal; processing the frequency and amplitude from the at least one first audio signal and the frequency and amplitude from the at least one second audio signal as inputs to an algorithm to generate an output from the algorithm; and determining, from the output of the algorithm, a precipitation condition and a confidence measure of the precipitation condition.