AI Control Tower Platform for Logistics Digital Twin Decisions
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Solution Overview
Problem
Existing systems struggle to effectively manage and optimize value chain networks due to overwhelming data complexity and volume, leading to missed opportunities for insight and timely decision-making.
Innovation Solution
A cloud-based management platform with a micro-services architecture, incorporating interfaces, network connectivity facilities, adaptive intelligence, data storage, and monitoring facilities, to enable enterprises to manage value chain network entities from origin to customer use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If organizations implement comprehensive data collection systems with IoT sensors, wearable technologies, and information technology systems, then the amount of data available for management decisions increases dramatically, but the complexity and volume of data overwhelm users, causing them to miss opportunities for insight and timely decision-making
Solution Approach 1:
The patent introduces an artificial intelligence intermediary that acts as a mediator between the overwhelming data sources and human decision-makers. The AI system processes, analyzes, and translates complex data from multiple sources (IoT sensors, wearables, information technology systems) into actionable insights, eliminating the need for users to directly navigate data complexity while preserving access to comprehensive data quantities
Solution Approach 2:
The patent replaces manual data analysis and interpretation processes with automated artificial intelligence systems. Instead of humans directly processing complex data volumes, the AI mechanically processes data through algorithms and machine learning models, transforming raw data into insights automatically and efficiently without human cognitive overload
2Quantity of substance
If organizations implement comprehensive data collection systems with IoT sensors, wearable technologies, and information technology systems, then the amount of data available for management decisions increases dramatically, but users experience delays in making timely decisions due to being overwhelmed by data volume
Solution Approach 1:
The patent replaces manual data analysis processes with automated AI systems that mechanically process data at high speeds. The artificial intelligence automatically analyzes comprehensive data volumes and generates insights without human intervention delays, enabling rapid decision-making while maintaining access to complete data sets
Solution Approach 2:
The patent implements continuous automated data processing and analysis through AI systems that operate without interruption. The artificial intelligence continuously transforms raw data into actionable insights in real-time, ensuring that decision-making support is always available and eliminating gaps or delays in the data-to-insight conversion process
Data Source
AI summary
A value chain system that provides recommendations for designing a logistics system generally includes a machine learning system that trains machine-learned models that output logistics design recommendations based on training data sets that each respectively defines one or more features of a respective logistic system and an outcome relating to the respective logistics system; an artificial intelligence system that receives a request for a logistics system design recommendation and determines the logistics system design recommendation based on one or more of the machine-learned models and the request; and a digital twin system that generates an environment digital twin of a logistics environment that incorporates the logistics system design recommendation, and one or more physical asset digital twins of physical assets. The digital twin system executes a simulation based on the logistics environment digital twin, the one or more physical asset digital twins.