IoT Vaccine Scheduling Platform for Smart City Overcrowding
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Solution Overview
Problem
In smart cities, efficiently scheduling vaccines across multiple vaccination points to prevent overcrowding during large-scale epidemics is challenging due to the complexity of managing vaccine distribution and time allocation.
Innovation Solution
A method and system utilizing IoT technology, which includes a vaccine management platform that determines a service scope for each vaccination point, collects information on vaccine services, predicts the number of potential vaccinees at each point, and allocates vaccines based on these predictions to optimize scheduling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual scheduling methods are used, then operation simplicity is maintained, but scheduling accuracy and efficiency deteriorate
Solution Approach 1:
The patent replaces manual scheduling mechanisms with an automated IoT-based system that uses sensors, communication modules, and processing units to automatically track vaccines, monitor temperatures, and coordinate scheduling across multiple vaccination points, thereby improving scheduling accuracy while managing system complexity through automation
Solution Approach 2:
The system enables self-service operation where the IoT platform automatically collects data from vaccination points, processes scheduling information, and allocates vaccines without requiring manual intervention, allowing the system to manage itself and improve scheduling efficiency while maintaining operational simplicity
2Productivity
If real-time monitoring is implemented, then vaccine allocation efficiency is improved, but information processing complexity increases
Solution Approach 1:
The patent implements real-time monitoring through IoT sensors that continuously track vaccine temperatures, locations, and vaccination point status, feeding this information back to the central processing system which dynamically adjusts allocation schedules, thereby improving allocation efficiency while managing data processing complexity through structured feedback loops
Solution Approach 2:
The IoT platform serves multiple functions simultaneously - collecting temperature data, tracking vaccine locations, monitoring vaccination point capacity, and coordinating scheduling across all vaccination points, which improves allocation efficiency while consolidating data processing into a single multi-functional system rather than separate complex subsystems
3Adaptability or versatility
If dynamic service scope adjustment is implemented, then vaccination coverage is improved, but system response time increases
Solution Approach 1:
The system performs preliminary actions by pre-establishing service scopes and allocation schedules based on historical data and predictions, then making real-time adjustments only when necessary, which improves vaccination coverage through adaptive service scopes while minimizing response time by avoiding constant reconfiguration
Solution Approach 2:
The patent implements dynamic service scope adjustment where the system can flexibly expand or modify vaccination point coverage based on real-time demand patterns and vaccination availability, improving adaptability while managing response time through incremental adjustments rather than complete system reconfiguration
Data Source
AI summary
The present disclosure provides a method and system for scheduling vaccines in a smart city based on the Internet of Things (IoT), which is executed by a vaccine management platform. The method includes obtaining a service scope corresponding to each vaccination point in a preset area, obtaining information related to vaccine service within the service scope, the information related to the vaccine service including vaccination information, information of target persons to be vaccinated, and a time type of each preset time point, determining a prediction result based on the information related to the vaccine service within the service scope, the prediction result including a number of possible to-be-vaccinated persons at the each vaccination point at the each preset time point, and determining an allocation scheme based on the prediction result.