| CPC G06Q 10/06375 (2013.01) | 11 Claims |
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1. A method for progress monitoring and steering of impacts of a complex system to a world environment and ecosystem and social ecosystem induced by environmental-human and/or human-human linkages and for quantitative measuring of effects of applied risk-transfer structures to said environmental-human and/or human-human linkages induced by risk-transfer-sustainable development goal (SDG) linkages measuring quantifying distances of progresses toward at least one of a predefined SDG with and without applying said risk-transfer structures, the method performed by an automated measuring system and comprising:
capturing parameters indicating (i) a classification of the applied risk-transfer structures by operational or structural components and/or region or topographical cells, (ii) a volume of the applied risk-transfer structures by a risk-transfer structure count and at least one other volume measure, and (iii) a quantification of SDG-relevant properties of the applied risk-transfer structures,
quantifying the applied risk-transfer structures by classifying the risk-transfer structures and quantifying an associated risk-transfer volume and a volume of actions and/or operations conducted by the complex system,
measuring the environmental-human and/or human-human linkages and the risk-transfer-SDG linkages of the complex system to an SDG by quantifying associated impacts of SDG-relevant properties of the complex system, the measuring being realized by measuring temporally evolving real-world measuring parameters by a plurality of measuring sensors associated with physical real-world systems/objects to be monitored and associated with the world environment and ecosystem the systems/objects are interacting with and influencing their SDGs, including at least one of satellites, distributed measuring systems, smartphones, and wearable devices, allowing seamlessly collecting and communicating data enabling the measuring system,
capturing the properties of the complex system by creating a digital replica of the complex system based on performing machine learning on the evolving real-world measuring parameters measured by the plurality of measuring sensors and using a parametrization capturing a modified environmental-human and/or human-human linkage modified by one or more of the risk-transfer-SDG linkages associated with one or more of the applied risk-transfer structures to an SDG impact, the modified environmental-human and/or human-human linkages including three main parts: (i) a transmission mechanism cause capturing an impact of the complex system on a specific indicator, (ii) a transmission rate represented by a measuring value linking the transmission mechanism cause to a relevant activity/operation volume of the complex system, and (iii) a transmission measuring value providing a complex system's volume as the complex system's volume times a transmission rate for an indicator scaled by a risk-transfer structure allocation, parametrizing levers being generated by capturing mechanisms to SDG impact as different channels of transmission, for each risk-transfer structure a default value being determined from the classification, and the default values being adjusted in relation to the classification, the transmission rate generated to consist of fractions of the complex system's volume which are homogeneous and relevant for a specific indicator and type of fraction or of a measuring value quantifying the quality of the complex system as a type of custom,
quantifying the impact of the complex system on selected SDG indicators, a lever-specific volume being applied to an indicator intensity of the complex system and an underlying impact being attributed to an allocation of a risk-transfer structure, wherein a lever comprises a fraction value of a risk-transfer volume, the quantification comprising quantifying SDG-relevant properties of the risk-transfer structure,
comparing, for indicator conversion and scoring, the indicators to reference values to generate relative measures and converting them to a score metric,
aggregating indicators and scores across different portfolios and/or policies of the applied risk-transfer structures and aggregating scores across SDGs and across the different portfolios and/or policies of the applied risk-transfer structures, the scores being combined into an overall score for steering and overall optimization,
each score indicating the performance of an applied risk-transfer structure to a relative target according to a certain SDG indicator, and the risk-transfer structures being adapted based on the quantified measuring of the impact of the applied risk-transfer structures.
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