Carbon Footprint Data Aggregation via Standardized Conversion
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Solution Overview
Problem
Aggregating carbon footprint data from various sources is challenging due to discrepancies in data formats and structures, making it difficult to quantify and track user activities effectively, especially for community-level contributions.
Innovation Solution
A computer-implemented method that converts user actions into carbon emission equivalents, aggregates them for assigned communities, and displays the results on a master dashboard, using a system comprising client devices, a computing server, and a network to transmit and process data, including engines for action logging, verification, carbon calculation, and data aggregation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data aggregation is performed from various sources, then comprehensive carbon footprint tracking is achieved, but data format discrepancies and structural inconsistencies make aggregation difficult
Solution Approach 1:
The patent transforms heterogeneous carbon footprint data from various sources into a standardized format by changing the parameters of data representation. All data entries are converted to a common structure with standardized fields for carbon emissions, enabling aggregation despite originating from diverse sources with different formats and structures.
Solution Approach 2:
The patent introduces a data aggregation service as an intermediary component that receives data from multiple sources, standardizes it, and produces unified carbon footprint metrics. This intermediary layer handles the complexity of format conversion and structural harmonization, shielding the aggregation process from source-specific variations.
2Speed
If real-time data processing is implemented, then timely carbon emission tracking is achieved, but processing speed and computational resources are consumed
Solution Approach 1:
The patent performs preliminary data standardization and validation at the point of data entry, before aggregation and analysis. By pre-processing data to match the standardized format early in the pipeline, the system reduces the computational burden during real-time aggregation, enabling faster processing with lower energy consumption.
3Measurement precision
If detailed user action data is collected, then accurate carbon emission calculation is achieved, but data privacy and security concerns increase
Solution Approach 1:
The patent extracts only the essential data elements needed for carbon emission calculation from complete user action records. By taking out only the necessary parameters (such as distance, mode of transport, energy consumption) and excluding personally identifiable information, the system maintains measurement accuracy while reducing privacy and security risks.
Data Source
AI summary
The enclosed is a description of a computer-implemented method for aggregation of carbon emission data. A server receives data entries recording user actions from an application of a client device. The server assigns each data entry to one or more communities of the application. The user actions recorded are converted by the server to carbon emission equivalents. The carbon emission equivalents of a community to which a particular user belongs are aggregated for the particular user. The server establishes a data stream with the client device of the particular user and transmits the carbon emission equivalents of the community and a totality of carbon emission equivalents of the application to the client device. The carbon emission equivalents of the community and the totality of carbon emission equivalents, including communities the user is excluded from, are displayed on the client device on a master dashboard of the application.