Automated SDG Performance Measurement Across Environmental-Human Linkages

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Solution Overview

Problem

Existing systems fail to provide reliable, automated, and comprehensive measurements of sustainable development goals (SDGs) due to the complexity and multi-dimensionality of environmental-human and human-human linkages, particularly in the context of evolving real-world systems, and lack the ability to quantify the impact of risk-transfer structures effectively.

Innovation Solution

A performance measuring system that utilizes IoT and machine learning technologies to automatically measure, monitor, and report on SDGs by integrating multiple data sources, prioritizing indicators, and accounting for correlations, while normalizing measured factors and incorporating risk-transfer structures.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If manual tracking by human experts using spreadsheets and documents is used, then flexibility in capturing SDG findings is achieved, but reliability and consistency deteriorate due to errors and misunderstandings

Engineering Contradiction:

ImproveflexibilityVSAvoidconsistency

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The patent replaces manual mechanical tracking methods (spreadsheets, documents, human expert judgment) with an automated digital system that uses sensors, data processing algorithms, and standardized measurement protocols to track SDG indicators, thereby eliminating human errors while maintaining adaptability through configurable parameters

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system transforms qualitative SDG findings into quantifiable parameters and metrics that can be automatically measured and tracked, changing the state of data from unstructured text to structured numerical values that enable consistent comparison and analysis

Inventive Principle:

Principle #35Parameter changes

2Reliability

If automated measurement systems are implemented, then reliability and consistency improve, but device complexity increases due to multiple data sources and processing requirements

Engineering Contradiction:

Improvemeasurement reliabilityVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent divides the complex measurement system into modular components: data acquisition modules from multiple sources, data processing modules with standardized algorithms, and output modules for different SDG indicators. Each module operates independently with well-defined interfaces, reducing overall system complexity while maintaining measurement reliability

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system employs universal data processing algorithms and standardized measurement protocols that can handle multiple data sources and various SDG indicators through a single unified framework, reducing the need for separate complex systems for each measurement task

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Loss of information

If comprehensive SDG tracking across multiple indicators is performed, then measurement completeness improves, but loss of time increases due to processing large volumes of data

Engineering Contradiction:

Improvemeasurement completenessVSAvoidprocessing time

Core Design Contradiction:

Loss of informationVSLoss of time

Solution Approach 1:

The system performs preliminary data validation, filtering, and standardization at the point of data acquisition from multiple sources. Data is pre-processed and structured before being fed into the main analysis pipeline, reducing the computational burden and processing time for comprehensive SDG indicator calculation

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent creates simplified digital replicas or models of complex SDG measurement processes that can be computed efficiently. These digital twins or proxy models allow rapid estimation of SDG indicators without requiring full processing of all underlying data, maintaining completeness while reducing time loss

Inventive Principle:

Principle #26Copying

4Ease of operation

If prior art systems attempt to assign carbon values to items, then ease of operation improves, but measurement precision deteriorates due to guess values and misleading data

Engineering Contradiction:

Improveease of useVSAvoidcarbon value accuracy

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent replaces manual guessing and estimation methods with automated data-driven algorithms that calculate carbon values based on actual operational data from sensors and connected systems, maintaining ease of operation while dramatically improving measurement precision through objective measurement rather than subjective judgment

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12462210B2Performance measuring system measuring sustainable development relevant properties of an object, and method thereof

Publication Date: 2025.11.04 SWISS REINSURANCE CO LTD

AI summary

Proposed is an automated measuring system for progress monitoring and steering of impacts of a complex system to world environment and ecosystem induced by environmental-human linkages and for quantitative measuring of effects of applied risk-transfer structures to said environmental-human linkages induced by risk-transfer-SDG linkages measuring quantifying distances of progresses toward at least one of a predefined sustainable development goal with and without applying said risk-transfer structures.