Titre : | Monitoring System Development To Non-Invasively Forecast Future Body Temperature |
Auteurs : | Khadidja MAKHLOUF, Auteur ; Zohra Hamidi, Directeur de thèse |
Type de document : | Monographie imprimée |
Editeur : | Biskra [Algérie] : Faculté des Sciences Exactes et des Sciences de la Nature et de la Vie, Université Mohamed Khider, 2021 |
Format : | 1 vol. (64 p.) / ill. / 29 cm |
Langues: | Anglais |
Mots-clés: | Body temperature forecasting, Articial Intelligence, Machine Learning, Internet of Things, Forecasting methods, Microcontroller, Temperature sensor. |
Résumé : | Articial Intelligence has lately begun to be used into medicine to improve patient care by speeding up processes and increasing accuracy, paving the way for improved healthcare in general. On the other hand, temperature is an important health factor that has to be regularly monitored, and even early detected in some situations.Therefore, this project aims to invest the advances of AI to develop a monitoring system that early detects body temperature. The used technique relies on building a wearable device using a temperature sensor and a microcontroller with WiFi card integrated. Thus, the internet of things technology is mandatory to beneciate from cloud storage and display the forecasted results on a reactive web application using the forecasting technique to get early body temperature values. |
Sommaire : |
General Introduction 3
I State of the art 5 1 Articial intelligence 7 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.2 Articial intelligence and machine learning . . . . . . . . . . . . . . . . . . . 7 1.2.1 Articial Intelligence . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.2.2 Articial intelligence in medicine . . . . . . . . . . . . . . . . . . . . 7 1.2.3 Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.2.3.1 Approach for a machine learning algorithm development process. 8 1.2.3.2 Machine learning methods . . . . . . . . . . . . . . . . . . . 9 1.2.3.3 Machine learning algorithms for data analytics . . . . . . . 13 1.2.4 Articial intelligence and early body temperature detection . . . . . 13 1.2.5 Prediction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 1.2.5.1 Health predicting . . . . . . . . . . . . . . . . . . . . . . . 14 1.2.5.2 Predicting body temperature . . . . . . . . . . . . . . . . . 14 1.2.6 Forecasting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 1.2.6.1 Health Forecasting . . . . . . . . . . . . . . . . . . . . . . . 15 1.2.6.2 Health forecasting elucidation . . . . . . . . . . . . . . . . 15 1.2.6.3 Measure of error . . . . . . . . . . . . . . . . . . . . . . . . 16 1.2.6.4 Focus of a health forecast . . . . . . . . . . . . . . . . . . . 16 1.2.6.5 Horizon of health forecasting . . . . . . . . . . . . . . . . . 16 1.2.7 Prediction vs Forecasting . . . . . . . . . . . . . . . . . . . . . . . . . 17 1.2.8 Patterns of health data and applications in forecasting . . . . . . . . 19 1.2.9 Probabilistic health forecasting methods for peak events . . . . . . . 20 1.2.10 Challenges in developing and using health forecasts . . . . . . . . . . 20 1.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2 Body temperature and Internet of Things technology 23 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2.2 Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2.2.1 Methods of measuring body temperature . . . . . . . . . . . . . . . 23 2.2.2 Dierent types of medical thermometers . . . . . . . . . . . . . . . . 24 2.2.2.1 Electronic thermometer . . . . . . . . . . . . . . . . . . . . 24 2.2.2.2 Forehead (infrared) thermometer . . . . . . . . . . . . . . . 24 2.2.2.3 Mercury thermometer(liquid in glass) . . . . . . . . . . . . . 25 2.2.2.4 Pacier thermometer . . . . . . . . . . . . . . . . . . . . . . 25 2.2.2.5 Digital ear (tympanic) thermometer . . . . . . . . . . . . . 26 2.2.3 Another way of temperature monitoring . . . . . . . . . . . . . . . . 26 2.3 Temperature Sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 2.4 Internet of Things . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.4.1 Working principle of IoT system . . . . . . . . . . . . . . . . . . . . . 29 2.4.2 Benets of IoT technology . . . . . . . . . . . . . . . . . . . . . . . . 30 2.4.3 Microcontrollers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 2.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 II Design and implementation 34 3 Design 35 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 3.2 Body temperature monitoring device . . . . . . . . . . . . . . . . . . . . . . 35 3.2.1 Hardware part . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 3.2.1.1 Hardware system design . . . . . . . . . . . . . . . . . . . . 37 3.2.2 Software part . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 3.2.2.1 Dataset Collection and storage . . . . . . . . . . . . . . . . 38 3.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 4 Implementation 42 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 4.2 Hardware realisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 4.3 Software implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 4.3.1 Development tools and languages . . . . . . . . . . . . . . . . . . . . 44 4.3.1.1 Arduino Sketch . . . . . . . . . . . . . . . . . . . . . . . . . 46 4.3.1.2 Machine learning models implementation . . . . . . . . . . . 51 4.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 General conclusion and perspectives 60 |
Type de document : | Mémoire master |
Disponibilité (1)
Cote | Support | Localisation | Statut |
---|---|---|---|
MINF/679 | Mémoire master | bibliothèque sciences exactes | Consultable |