IoT Sensor AI for Supply Chain Pathogen Prevention
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods fail to effectively prevent the cross-contamination of pathogens during the delivery of products through supply chains, which can lead to the spread of diseases like COVID-19, as they lack real-time monitoring and dynamic prevention mechanisms.
Innovation Solution
A system utilizing IoT sensors and AI, specifically a Region Based Convolutional Neural Network (RCNN), is configured along the supply chain to track and analyze handling interactions, determining if handling requirements are met, and stopping distribution if not, thereby preventing pathogen propagation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time monitoring and dynamic prevention mechanisms are implemented, then pathogen propagation is prevented, but system complexity increases
Solution Approach 1:
The system segments the supply chain into multiple monitoring zones with IoT sensors deployed at different locations (warehouses, transportation routes, delivery points). Each zone independently monitors for pathogens and transmits data to the central AI system, allowing distributed monitoring that reduces central system complexity while maintaining comprehensive coverage
Solution Approach 2:
The patent introduces an intermediary AI system that acts as a mediator between IoT sensors and supply chain operations. The AI handling confirmation engine processes sensor data, identifies pathogen risks, and automatically implements prevention measures, reducing the complexity burden on individual components while achieving system-wide pathogen prevention
2Measurement precision
If AI analysis and IoT sensor tracking are deployed throughout the supply chain, then handling compliance is improved, but implementation cost and infrastructure requirements increase
Solution Approach 1:
The patent employs universal IoT sensors that can detect multiple types of interactions (touch, proximity, temperature changes) and pathogen presence across different supply chain contexts. The AI handling confirmation engine serves multiple functions: tracking package location, analyzing sensor data, determining handling compliance, and triggering prevention measures, reducing the need for specialized equipment at each stage
Solution Approach 2:
The system implements self-service capabilities where the AI automatically analyzes sensor data and determines handling compliance without manual intervention. The AI handling confirmation engine self-adjusts monitoring parameters based on package sensitivity levels and automatically implements prevention measures, reducing the need for complex manual monitoring infrastructure
Data Source
AI summary
Propagation of pathogens is reduced by configuring internet of things (IoT) sensors along a supply chain of package; and analyzing the packages in the supply chain using the IoT sensors to determine handling requirements of products. The packages can be tracked with a package handling confirmation engine including a Region Based Convolutional Neural Network (RCNN) to determine with the IoT sensors measuring interactions with the packages that parties in the supply chain are handling the packages in accordance with the handling requirements. Product distribution can be stopped through the supply chain in response to the interactions with the packages failing to meet the handling requirements.