Infrared Temperature Array Outbreak Detection

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Solution Overview

Problem

Current infectious disease outbreak detection systems lack population-level analysis capabilities, failing to provide early warning and discrimination between non-epidemic and epidemic outbreaks, relying on manual reporting and individual tracking rather than comprehensive data collection and analysis.

Innovation Solution

An automated fever-causing disease outbreak detection system utilizing a central control unit with wireless infrared detectors, environmental data collection, and machine learning algorithms to generate predicted population temperature distributions, compare with measured data, and issue alerts for outbreak conditions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual reporting by healthcare workers is used for syndromic surveillance, then individual patient tracking is achieved, but population-level detection capabilities are lost and detection is delayed

Engineering Contradiction:

Improveindividual patient tracking accuracyVSAvoidpopulation-level data coverage

Core Design Contradiction:

Measurement precisionVSQuantity of substance

Solution Approach 1:

The system segments surveillance into two complementary layers: individual-level manual reporting by healthcare workers and population-level automated temperature monitoring. This segmentation allows each method to excel at its appropriate scale while feeding data to a unified analysis platform that performs population-level outbreak detection.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system merges data from multiple sources including manual healthcare worker reports, automated infrared temperature sensors, and environmental data into a unified syndromic surveillance platform. This combination enables both individual case tracking and aggregate population analysis to occur simultaneously within the same system.

Inventive Principle:

Principle #5Merging (Combining)

2Quantity of substance

If automated infrared temperature monitoring is deployed, then population-level detection capability is improved, but false positives increase due to environmental factors

Engineering Contradiction:

Improvepopulation-level data coverageVSAvoidtemperature measurement accuracy

Core Design Contradiction:

Quantity of substanceVSMeasurement precision

Solution Approach 1:

The system implements feedback loops where temperature measurements are continuously compared against environmental conditions (ambient temperature, humidity, time of day) and historical baseline data. This feedback mechanism allows the system to dynamically adjust thresholds and filter out readings influenced by environmental factors, reducing false positives while maintaining population-level monitoring coverage.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system changes the parameters used for temperature assessment from simple absolute thresholds to multi-parameter analysis that includes environmental context, time of day, seasonal variations, and individual baseline temperatures. This parameter transformation allows accurate distinction between environmentally-induced temperature changes and fever indicative of disease.

Inventive Principle:

Principle #35Parameter changes

3Measurement precision

If comprehensive environmental data collection is implemented, then outbreak detection accuracy is improved, but system complexity increases

Engineering Contradiction:

Improveoutbreak detection accuracyVSAvoidsystem architecture complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system employs a multi-functional data processing platform that handles diverse data types (temperature readings, environmental sensors, manual reports, historical data) through unified algorithms. This universal processing architecture reduces overall system complexity by avoiding separate specialized systems for each data source while maintaining high detection accuracy through comprehensive analysis.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

Enables early warning and accurate detection of infectious disease outbreaks by analyzing population-level temperature data, reducing false positives and accounting for environmental factors, thereby facilitating timely health authority alerts and resource allocation.

Implementation Method 1

an array of infrared detectors wirelessly connected to the central control unit, wherein the array of infrared detectors measures temperatures of persons in a measured population

Methodology Applied

Scientific EffectInfrared radiation detection: Infrared Radiation

Data Source

PatentUS11393595B2Method for determining a disease outbreak condition at a transit facility

Publication Date: 2022.07.19 PRINCE MOHAMMAD BIN FAHD UNIV

AI summary

A fever-causing disease outbreak detection system for an early warning of the outbreak of an infectious disease. The system uses an array of infrared detectors to measure the temperatures of individuals in a population. The measured temperatures are used to create a measured population temperature distribution. A central control unit generates a predicted population temperature distribution using environmental data such as local atmospheric conditions and compares the predicted population temperature distribution to the measured population temperature distribution. If an outbreak is detected, an alert is issued.