Centralized AIoT Logistics Network for Real-Time Supply Chain Visibility
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Solution Overview
Problem
Current supply chain management systems lack a unified platform to integrate multiple supply chains, leading to inefficiencies, limited interoperability, and a lack of real-time data analytics, hindering the full potential of AIoT in optimizing logistics processes.
Innovation Solution
A comprehensive logistics network system leveraging AIoT to integrate multiple supply chain ecosystems, utilizing a centralized operator with high-performance computing, AIoT modules, and smart sensors to provide real-time visibility, dynamic pricing, and seamless communication across global supply chains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple supply chain ecosystems operate independently with disparate systems, then each system can maintain operational independence and simplicity, but integration and interoperability are limited leading to inefficiencies and increased costs
Solution Approach 1:
The patent introduces a centralized operator as an intermediary layer between multiple supply chain ecosystems. This operator acts as a mediator that receives data from various independent systems (suppliers, manufacturers, distributors, retailers, customers) and processes it through unified AIoT platforms, enabling integration without requiring each ecosystem to directly connect with every other system.
Solution Approach 2:
The centralized operator implements a universal platform that handles multiple functions: data collection from diverse sources, real-time monitoring, analytics, decision-making, and coordination across different supply chain stages. This multi-functional approach allows a single system to manage complexity that would otherwise require multiple specialized systems.
2Productivity
If traditional communication mediums like voice calls, email, and text messaging are used, then communication simplicity is maintained, but real-time data processing and analytics capabilities are limited
Solution Approach 1:
The patent replaces traditional mechanical communication methods (voice calls, email, text messaging) with an automated AIoT-based communication system. This system uses intelligent algorithms to process, analyze, and respond to supply chain data in real-time, substituting manual communication mechanisms with automated digital processing that operates continuously without human intervention.
Solution Approach 2:
The AIoT communication system operates continuously and autonomously, providing uninterrupted real-time data processing and response. Unlike traditional communication methods that require human action, the automated system maintains constant monitoring and processing of supply chain data, enabling immediate responses to changing conditions.
3Loss of information
If existing logistics systems operate in silos with limited interoperability, then system simplicity is maintained, but real-time visibility and coordinated decision-making across the supply chain are compromised
Solution Approach 1:
The patent merges previously siloed supply chain information into a unified view through the centralized operator. By combining data from all supply chain stakeholders (suppliers, manufacturers, distributors, retailers, customers) into a single integrated platform, the system eliminates information silos and provides comprehensive real-time visibility across the entire network.
Solution Approach 2:
The system adds a new dimensional layer of integration by implementing a centralized operator that operates above and beyond individual supply chain entities. This additional dimension enables cross-functional analysis and coordinated decision-making that was not possible within traditional siloed structures, providing holistic visibility across the entire supply chain ecosystem.
Data Source
AI summary
The disclosed system and method integrate multiple supply chain ecosystems into a cohesive network using a centralized operator. The system interconnects physical and mobile infrastructures, networks, and smart sensors. An Artificial Intelligence of Things (AIOT) module provides real-time visibility into dynamic pricing, booking availability, payment processing, smart contract execution, and traceability of physical and online goods. A high-performance computing module, comprising Central Processing Units (CPUs) and Graphics Processing Units (GPUs), executes complex algorithms and deep learning models for rapid data processing and analytics. The system empowers logistics operators with actionable insights and precise control over supply chain operations.