Mobile Sensor Data Fusion for Environmental Mapping
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Solution Overview
Problem
Existing methods for determining environmental properties using mobile sensors face challenges in providing precise and accurate estimates due to the random movement and location of data sources, leading to high measurement variance, and the inefficiency of transmitting large volumes of data from multiple sources to a central computing device.
Innovation Solution
A two-stage fusion method is employed, where each data source generates a measured value vector and calculates a preliminary estimated value (prefusion) based on spatial and temporal weighting, and a central computing device summarizes these estimates using virtual measuring stations to determine a final estimated value (main fusion), reducing variance and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all measured values from mobile data sources are transmitted to a central computing device for processing, then the completeness and accuracy of environmental property estimation is improved, but the transmission bandwidth requirement and processing effort increase significantly
Solution Approach 1:
The patent divides the data processing into two segments: (1) Each mobile data source independently performs local processing to generate an estimated source value from its measured values, and (2) The central computing device processes only these compact estimated source values rather than all raw measured values. This segmentation reduces transmission bandwidth while maintaining estimation accuracy.
Solution Approach 2:
The patent applies preliminary action by having each mobile data source pre-process its measured values locally to generate estimated source values before transmission. This pre-processing includes forming measured value vectors and calculating weighted estimates, so that the central device receives ready-to-use data rather than raw measurements requiring extensive processing.
2Loss of energy
If measured values from mobile data sources are used directly without preprocessing, then the data transmission volume is reduced, but the measurement variance and uncertainty in estimated values increase
Solution Approach 1:
Each mobile data source performs preliminary processing by forming measured value vectors from its stored measured values and calculating estimated source values using weighted combinations. This preliminary action reduces the data volume to be transmitted while ensuring that the transmitted estimates have reduced variance through proper weighting of the original measurements.
Solution Approach 2:
The patent transforms the raw measured values into a different parameter representation - estimated source values with associated weights. This parameter transformation consolidates multiple measurements into single estimate values, reducing transmission volume while preserving information through the weighting mechanism that accounts for measurement quality and timing.
3Area of stationary object
If multiple mobile data sources are used for area-wide surveying, then the coverage and completeness of environmental mapping is improved, but the data volume and processing complexity increase
Solution Approach 1:
The patent segments the processing complexity by distributing preliminary processing to each mobile data source independently. Each source handles its own measured values locally to generate estimated source values, so the central device only needs to perform final aggregation and fusion of these estimates, rather than processing all raw measurements from all sources.
Solution Approach 2:
The patent extracts the essential information from large volumes of raw measured values by having each mobile source calculate compact estimated source values. This extraction process removes redundant data while preserving the key environmental information needed for area-wide mapping, reducing overall processing complexity.
Data Source
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AI summary
The invention relates to a method for determining estimated values of an environmental property by means of sensors (9) arranged in mobile data sources (2), wherein the data sources (2) store several measured values (10) of the environmental property at respective measurement positions (42) at respective measurement times in a prebuffer (21) and form a measured value vector (29) from this and determine a source estimated value (11) on the basis of the measured value vector (29) by means of a prefusion (17) and each data source (2) sends its source estimated value (11) to a source-external computing device (3) and the computing device (3) assigns the source estimated values (11) to a respective catchment area (15) of at least one measuring station (13) and determines a final station estimated value (12) of the environmental property at the station position (14) for a predetermined estimation time for each measuring station (13) by means of a main fusion (18).The pre-fusion (17) and the main fusion (18) weight their respective input values depending on a spatial distance of the respective measurement location to a reference position and/or depending on a temporal distance of the measurement time to a reference time.