Quantum Health State Model for Real-Time Weather Risk Alerts
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing technologies face challenges in efficiently incorporating diverse data sources, including IoT data, into weather prediction models, due to the significant computing resources required to update these models in real-time during weather events.
Innovation Solution
The use of quantum computing systems to perform combinatorial analysis, allowing for the simultaneous evaluation of various data sources, including IoT data and weather event data, to generate and update quantum health state models that assess the health states of individuals in relation to weather events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional computing systems are used to incorporate diverse data sources into weather prediction models, then measurement precision and reliability are improved, but productivity and processing speed deteriorate due to the vast computing resources required
Solution Approach 1:
The patent replaces traditional classical computing systems with quantum computing systems to perform combinatorial analysis of weather data and IoT data. The quantum computing system uses quantum bits (qubits) and quantum algorithms to process multiple data sources simultaneously through quantum parallelism, achieving both high prediction accuracy and fast processing speed that classical systems cannot achieve alone.
2Reliability
If real-time updates to prediction models are performed during weather events, then reliability is improved, but loss of time and productivity worsen due to the computational burden
Solution Approach 1:
The system performs preliminary actions by pre-processing and normalizing data from multiple sources before weather events occur, and by using quantum algorithms that can evaluate multiple prediction scenarios simultaneously. This allows the system to quickly update predictions in real-time during weather events without excessive computational delay, maintaining both reliability and speed.
3Measurement precision
If comprehensive combinatorial analysis of multiple data sources is performed, then measurement precision is improved, but device complexity and computing resource requirements worsen
Solution Approach 1:
The patent creates a universal quantum computing system that can handle multiple types of data (weather data, IoT sensor data, historical data) through a unified quantum algorithm framework. The quantum computing system serves multiple functions: data normalization, combinatorial analysis, pattern recognition, and prediction generation, reducing the need for separate specialized systems for each function.
Data Source
AI summary
A method may include receiving static input data comprising a plurality of heath states for individuals over a period of time with respect to respective locations, receiving event scenario data comprising expected paths for weather events, and generating a quantum health state model based on the static input data and the event scenario data. The quantum health state model may evaluate each health state with respect to the individuals at the respective locations and the weather events in superposition. The method may receive dynamic input data associated with the individuals and a plurality of sensors acquired after the first dataset. The method may determine that an individual of the plurality of individuals is associated with a health data value that is greater than a threshold based on the quantum health state model and the dynamic input data and automatically transmit notifications indicative of the expected location to devices.