{"id":3527,"date":"2023-01-31T10:01:45","date_gmt":"2023-01-31T09:01:45","guid":{"rendered":"https:\/\/miniprojets.net\/?p=3527"},"modified":"2023-04-04T23:22:47","modified_gmt":"2023-04-04T21:22:47","slug":"publication-des-bureaux-detudes-machine-learning-optimization","status":"publish","type":"post","link":"https:\/\/miniprojets.net\/index.php\/2023\/01\/31\/publication-des-bureaux-detudes-machine-learning-optimization\/","title":{"rendered":"Publication des bureaux d&#8217;\u00e9tudes Machine Learning &#038; Optimization"},"content":{"rendered":"\n<p>Bonjour \u00e0 tous, <\/p>\n\n\n\n<p>Aujourd&#8217;hui, je vous propose la publication des articles produits par les \u00e9l\u00e8ves de 3\u00e8me ann\u00e9e de la fili\u00e8re SGB de l&#8217;Ense3 pour leur projet tournant autour du Machine learning et de l&#8217;Optimisation. <\/p>\n\n\n\n<p>Je vous souhaite une bonne lecture, <\/p>\n\n\n\n<p>J\u00e9r\u00f4me Ferrari<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Project 1: Estimation of electrical consumption &amp; analysis<\/h2>\n\n\n\n<p><strong>Authors<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Albert Granollers<\/li>\n\n\n\n<li>Mikayel Margaryan<\/li>\n<\/ul>\n\n\n\n<p><strong><strong>Abstract<\/strong><\/strong><\/p>\n\n\n\n<p>Currently, one of the hot topics in the engineering is the power supply in highly loaded<br>periods like, especially after last geopolitical crisis. According to EU commission, Russia\u2019s<br>unjustified military aggression against Ukraine and its weaponisation of gas supplies<br>have provoked an unprecedented energy crisis for the EU. They have caused a sharp rise<br>in energy prices and brought hardship for Europeans. Thus, the EU commission is taking<br>strong action to address this.<br>In order to overcome unexpected challenges, one of the actions and policies published<br>in September 2022 is about new measures that were implemented to reduce electricity<br>demand and use energy surpluses for the benefit of citizens and industry. As a result,<br>the focus of this study will be on how to use collected data to create opportunities for<br>appropriate policies.<\/p>\n\n\n\n<p><strong>Report<\/strong><\/p>\n\n\n\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/GRANOLLERS_MARGARYAN_MLO.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of GRANOLLERS_MARGARYAN_MLO.\"><\/object><a id=\"wp-block-file--media-b080eab3-45d0-4d53-9585-cfc54fda1387\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/GRANOLLERS_MARGARYAN_MLO.pdf\">GRANOLLERS_MARGARYAN_MLO<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/GRANOLLERS_MARGARYAN_MLO.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-b080eab3-45d0-4d53-9585-cfc54fda1387\">Download<\/a><\/div>\n\n\n\n<p><strong>Code<\/strong><\/p>\n\n\n\n<div class=\"wp-block-file\"><a id=\"wp-block-file--media-92486ba9-90d2-4138-b531-28e21c371372\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/BE_MLO_GRANOLLERS_MARGARYAN.zip\">BE_MLO_GRANOLLERS_MARGARYAN<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/BE_MLO_GRANOLLERS_MARGARYAN.zip\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-92486ba9-90d2-4138-b531-28e21c371372\">Download<\/a><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Project 2: Estimation of thermal Comfort based on CO2 level<\/h2>\n\n\n\n<p><strong>Authors<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Kriti Baruah<\/li>\n\n\n\n<li>Priyadarshini Karthikeyan<\/li>\n<\/ul>\n\n\n\n<p><strong><strong>Abstract<\/strong><\/strong><\/p>\n\n\n\n<p>Air temperature and the Co2 level in a particular space play a vital role, it does not<br>only affect energy consumption, but also occupancy, thermal discomfort, ventilation<br>behaviour and building performance maintenance. The effect of air temperature and<br>CO2 level in the bedroom of the building is used to predict the thermal comfort of the<br>room. The paper aims to build a prediction model for thermal discomfort based on<br>the air temperature and the carbon dioxide level using a Linear Regression. The<br>CO2 level indoor environment ranges between 350 to 2500 ppm. It is important to<br>maintain the level in the range, to have lower thermal discomfort. The occupancy in<br>the room increases the air temperature, air circulation and CO2 level of the room. To<br>predict the CO2 level in the bedroom using the external and the indoor temperature<br>linear regression predictive model is used. The study measures the thermal<br>discomfort level and helps the user to take action towards optimizing the air<br>circulation and thermal comfort of the bedroom.<\/p>\n\n\n\n<p><strong>Report<\/strong><\/p>\n\n\n\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MACHINE-LEARNING_CO2.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of MACHINE-LEARNING_CO2.\"><\/object><a id=\"wp-block-file--media-d177a77c-8614-4c38-a0af-66a5fb38da55\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MACHINE-LEARNING_CO2.pdf\">MACHINE-LEARNING_CO2<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MACHINE-LEARNING_CO2.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-d177a77c-8614-4c38-a0af-66a5fb38da55\">Download<\/a><\/div>\n\n\n\n<p><strong>Code<\/strong><\/p>\n\n\n\n<div class=\"wp-block-file\"><a id=\"wp-block-file--media-6c16c6bb-79e8-4d98-a106-e78156690b28\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/Machine-Learning-Thermal-Comfort.zip\">Machine Learning Thermal Comfort<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/Machine-Learning-Thermal-Comfort.zip\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-6c16c6bb-79e8-4d98-a106-e78156690b28\">Download<\/a><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Project 3: Influence of Weather on Energy Consumption<\/h2>\n\n\n\n<p><strong>Authors<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Sara IZADI<\/li>\n\n\n\n<li>Tiwalade OYEBODE<\/li>\n\n\n\n<li>AL-Mu\u2019tez billah AL-SQOUR<\/li>\n<\/ul>\n\n\n\n<p><strong><strong>Abstract<\/strong><\/strong><\/p>\n\n\n\n<p>Demand prediction and demand response are becoming more and more crucial because<br>of the rising proportion of renewable energies in the electrical mix and the accompanying<br>unpredictability of electricity generation. The need for electricity frequently varies<br>with the weather; for example, when it is cloudier, there is a greater demand for inside<br>illumination. Solar panels are also currently producing less electricity than usual. Order<br>to ensure grid stability and timely activation of backup resources, this requires the forecasting<br>of the electrical demand. The necessary generation can then be coordinated by<br>grid operators to meet the demand. In this work, we evaluate a decision tree regression<br>performance in estimating the electricity consumption and gas usage of a smart home<br>using weather information. Wind, rain, and UV index are the factors employed. The<br>property is equipped with gas heating. This study\u2019s objectives are to identify the meteorological<br>factors best suited for use in making predictions of this nature and to identify<br>plausible reasons for the findings. However, obtaining the most precise results is not the<br>objective. Many more variables, such as historical energy use (from a week ago, today,<br>etc.), must be taken into account to produce a performance that is more accurate.<\/p>\n\n\n\n<p><strong>Report<\/strong><\/p>\n\n\n\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MLO_report-1.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of MLO_report-1.\"><\/object><a id=\"wp-block-file--media-0e0c7939-dab1-4f10-b2be-de22b3662504\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MLO_report-1.pdf\">MLO_report-1<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MLO_report-1.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-0e0c7939-dab1-4f10-b2be-de22b3662504\">Download<\/a><\/div>\n\n\n\n<p><strong>Code<\/strong><\/p>\n\n\n\n<div class=\"wp-block-file\"><a id=\"wp-block-file--media-96612dfa-d909-4da3-9e8e-58c846c84604\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/Machineminiproject.zip\">Machineminiproject<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/Machineminiproject.zip\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-96612dfa-d909-4da3-9e8e-58c846c84604\">Download<\/a><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Project 4: Estimation of Energy Consumption in a Smart-House via meteorological variables<\/h2>\n\n\n\n<p><strong>Authors<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Germ\u00e1n Alejandro Ni\u00f1o Pallares<\/li>\n\n\n\n<li>Jos\u00e9 Ricardo Cabral Vianna<\/li>\n<\/ul>\n\n\n\n<p><strong><strong>Abstract<\/strong><\/strong><\/p>\n\n\n\n<p>Among the perks of disposing of several sensors in a smart house lies the possibility<br>of analyzing how the different sources of data can be used to estimate different<br>parameters of interest. In the past this study would be carried out with different<br>outlooks but the most predominant would remain being an empirical approach<br>which would need a good amount of experience to make it work. Nowadays we<br>possess larger amounts of data and tools that may allow us to find correlations<br>between data that are not to follow a deterministic nature but are easily modifiable in<br>order to find the best results. In this scope, the present report verses on how to use<br>meteorological data in order to estimate energy consumption for a smart house.<\/p>\n\n\n\n<p><strong>Report<\/strong><\/p>\n\n\n\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/Machine-Learning-Project-Report-CABRALVIANNA_NINO.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of Machine-Learning-Project-Report-CABRALVIANNA_NINO.\"><\/object><a id=\"wp-block-file--media-2fad6813-3254-44e4-9935-d011a8d5748e\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/Machine-Learning-Project-Report-CABRALVIANNA_NINO.pdf\">Machine-Learning-Project-Report-CABRALVIANNA_NINO<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/Machine-Learning-Project-Report-CABRALVIANNA_NINO.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-2fad6813-3254-44e4-9935-d011a8d5748e\">Download<\/a><\/div>\n\n\n\n<p><strong>Code<\/strong><\/p>\n\n\n\n<div class=\"wp-block-file\"><a id=\"wp-block-file--media-51575385-288b-4e4d-9592-6c883fc9460a\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/How-the-weather-influence-energy-consumption.zip\">How the weather influence energy consumption<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/How-the-weather-influence-energy-consumption.zip\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-51575385-288b-4e4d-9592-6c883fc9460a\">Download<\/a><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Project 5: Impacts of weather variation on air quality<\/h2>\n\n\n\n<p><strong>Authors<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Ahmad Opeyemi ZUBAIR<\/li>\n\n\n\n<li>Ismam BIN HASNAT<\/li>\n<\/ul>\n\n\n\n<p><strong><strong>Abstract<\/strong><\/strong><\/p>\n\n\n\n<p>Air quality in residential places is a growing concern, as it can have significant effects on<br>the health and well-being of individuals living in these areas. Exposure to Poor air quality<br>can lead to a variety of health complications, including respiratory problems, headaches,<br>and fatigue. In addition, it can also contribute to the deterioration of indoor surfaces<br>and possessions. Therefore, it is essential that steps are taken to ensure good air quality<br>in residential spaces.<\/p>\n\n\n\n<p><strong>Report<\/strong><\/p>\n\n\n\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/ML_Project.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of ML_Project.\"><\/object><a id=\"wp-block-file--media-a6a11df1-f26c-4803-98dd-342fa099507a\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/ML_Project.pdf\">ML_Project<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/ML_Project.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-a6a11df1-f26c-4803-98dd-342fa099507a\">Download<\/a><\/div>\n\n\n\n<p><strong>Code<\/strong><\/p>\n\n\n\n<div class=\"wp-block-file\"><a id=\"wp-block-file--media-ac7de392-e39c-4150-b394-77faf168511c\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/ML_project.zip\">ML_project<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/ML_project.zip\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-ac7de392-e39c-4150-b394-77faf168511c\">Download<\/a><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Project 6: Impacts of weather variation on air quality<\/h2>\n\n\n\n<p><strong>Authors<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Jui-Lien Hsia<\/li>\n\n\n\n<li>Anujraaj Gopalsamy Sakthivel<\/li>\n<\/ul>\n\n\n\n<p><strong>Abstract<\/strong><\/p>\n\n\n\n<p>The forecasting of residential electricity demand has become<br>a critical aspect in the development of sustainable energy systems. Accurate<br>prediction of electricity consumption patterns is essential in order to maintain<br>a stable energy supply and prevent overloading the grid. The present study<br>aimed to explore the effectiveness of the Stride TCN model in forecasting electricity<br>demand using data obtained from a Raspberry Pi. The collected data<br>underwent a rigorous preprocessing stage, which involved transforming the raw<br>time series data into a format suitable for training the model. Through the<br>use of the Stride TCN model, the study was able to demonstrate the potential<br>of deep learning models in predicting residential electricity demand with<br>high accuracy. This research sheds light on the importance of incorporating<br>cutting-edge machine learning techniques in energy forecasting and highlights<br>the significance of precise demand forecasting in the development of a sustainable<br>energy future.<\/p>\n\n\n\n<p><strong>Report<\/strong><\/p>\n\n\n\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MLO-Project2-Report.pdf\" type=\"application\/pdf\" style=\"width:100%;height:610px\" aria-label=\"Embed of MLO-Project2-Report.\"><\/object><a id=\"wp-block-file--media-f601873e-b85f-4c57-9305-7af4cf7b7f49\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MLO-Project2-Report.pdf\">MLO-Project2-Report<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MLO-Project2-Report.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-f601873e-b85f-4c57-9305-7af4cf7b7f49\">Download<\/a><\/div>\n\n\n\n<p><strong>Code<\/strong><\/p>\n\n\n\n<p><a href=\"https:\/\/github.com\/anujgs\/MLO-Project-2\">https:\/\/github.com\/anujgs\/MLO-Project-2<\/a><\/p>\n\n\n\n<div class=\"wp-block-file\"><a id=\"wp-block-file--media-7b85d761-6b48-4f89-93d5-7d930cbbbf66\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MLO-Project-2-main.zip\">MLO-Project-2-main<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MLO-Project-2-main.zip\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-7b85d761-6b48-4f89-93d5-7d930cbbbf66\">Download<\/a><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Project 7: Occupancy estimation<\/h2>\n\n\n\n<p><strong>Authors<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Patricia Mart\u00ednez Ruiz<\/li>\n\n\n\n<li>Leticia Tejedo Cerrato<\/li>\n<\/ul>\n\n\n\n<p><strong>Abstract<\/strong><\/p>\n\n\n\n<p>In this project we want to build a model that allows us to determine the presence<br>or not of individuals in the living room of the house. To carry out the estimation, we<br>will need to get access to the different measures from the sensors. For that, the<br>first step is to choose which ones we need.<\/p>\n\n\n\n<p><strong>Report<\/strong><\/p>\n\n\n\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/Expe-SmartHouse_Occupancy_estimation.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of Expe-SmartHouse_Occupancy_estimation.\"><\/object><a id=\"wp-block-file--media-073aa699-2983-4aeb-b6d3-80551047da16\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/Expe-SmartHouse_Occupancy_estimation.pdf\">Expe-SmartHouse_Occupancy_estimation<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/Expe-SmartHouse_Occupancy_estimation.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-073aa699-2983-4aeb-b6d3-80551047da16\">Download<\/a><\/div>\n\n\n\n<p><strong>Code<\/strong><\/p>\n\n\n\n<div class=\"wp-block-file\"><a id=\"wp-block-file--media-77bef75a-5a60-45e8-b429-22f5a8fd7302\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/FINAL-PROJECT.zip\">FINAL PROJECT<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/FINAL-PROJECT.zip\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-77bef75a-5a60-45e8-b429-22f5a8fd7302\">Download<\/a><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Project 8: Smart Home-Measuring the correlation between Energy Consumption and Weather<\/h2>\n\n\n\n<p><strong>Authors<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Manu Rajesh<\/li>\n\n\n\n<li>Omar Khalil<\/li>\n\n\n\n<li>Hussein Khalife<\/li>\n<\/ul>\n\n\n\n<p><strong>Abstract<\/strong><\/p>\n\n\n\n<p>Forecasting power consumption is a critical aspect of energy management, as it helps<br>in ensuring a stable and reliable electricity supply. Weather conditions play a significant<br>role in determining power consumption, with factors such as temperature, humidity, and<br>luminosity affecting the demand for electricity. For example, cold weather entices people<br>to utilize more electricity for heating.In this study, we aim to explore the relationship<br>between weather data and power consumption by developing a predictive model based<br>on decision tree classifier. By analyzing the correlations between weather variables and<br>power usage, we aim to identify the key factors that drive power consumption and gain<br>insights into the behavior of the system. The model will be developed using a dataset of<br>weather data and power consumption readings, and will employ advanced statistical<br>techniques and to establish the relationship between the two variables. The goal of this<br>study is to provide a more accurate and robust method for predicting power<br>consumption, which can help utilities and energy providers to better manage energy<br>supply and demand.<\/p>\n\n\n\n<p><strong>Report<\/strong><\/p>\n\n\n\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/Smart-Home-Measuring-the-correlation-between-Energy-Consumption-and-Weather-1.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of Smart-Home-Measuring-the-correlation-between-Energy-Consumption-and-Weather-1.\"><\/object><a id=\"wp-block-file--media-1c659b21-4ee1-49d0-b0ff-b41dd47c9bab\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/Smart-Home-Measuring-the-correlation-between-Energy-Consumption-and-Weather-1.pdf\">Smart-Home-Measuring-the-correlation-between-Energy-Consumption-and-Weather-1<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/Smart-Home-Measuring-the-correlation-between-Energy-Consumption-and-Weather-1.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-1c659b21-4ee1-49d0-b0ff-b41dd47c9bab\">Download<\/a><\/div>\n\n\n\n<p><\/p>\n\n\n\n<p><strong>Code<\/strong><\/p>\n\n\n\n<div class=\"wp-block-file\"><a id=\"wp-block-file--media-543da6ba-4316-4adf-8f5e-da867fba0a5e\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MLO2.zip\">MLO2<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MLO2.zip\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-543da6ba-4316-4adf-8f5e-da867fba0a5e\">Download<\/a><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Project 9: Electrical Consumption Estimation in the Smart Home<\/h2>\n\n\n\n<p><strong>Authors<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Shariq NADEEM<\/li>\n\n\n\n<li>Solomon Berihu ARAYA<\/li>\n<\/ul>\n\n\n\n<p><strong>Abstract<\/strong><\/p>\n\n\n\n<p>Demand prediction and demand response are becoming more and more crucial because<br>of the rising proportion of renewable energies in the electrical mix and the<br>accompanying unpredictability of electricity generation. The need for electricity<br>frequently varies with the weather; for example, when it is cloudier, there is a greater<br>demand for inside illumination. Solar panels are also currently producing less electricity<br>than usual. In order to ensure grid stability and timely activation of backup resources,<br>this requires the forecasting of the electrical demand. The necessary generation can<br>then be coordinated by grid operators to meet the demand.<\/p>\n\n\n\n<p><strong>Report<\/strong><\/p>\n\n\n\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MLO_TP_NADEEM_ARAYA.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of MLO_TP_NADEEM_ARAYA.\"><\/object><a id=\"wp-block-file--media-b306a0ac-3254-4116-b7e1-e6b38e2a0d07\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MLO_TP_NADEEM_ARAYA.pdf\">MLO_TP_NADEEM_ARAYA<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MLO_TP_NADEEM_ARAYA.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-b306a0ac-3254-4116-b7e1-e6b38e2a0d07\">Download<\/a><\/div>\n\n\n\n<p><strong>Code<\/strong><\/p>\n\n\n\n<div class=\"wp-block-file\"><a id=\"wp-block-file--media-e2cba287-94eb-488c-ac7c-728d4b110847\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/TP_ML_NADEEM_ARAYA.zip\">TP_ML_NADEEM_ARAYA<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/TP_ML_NADEEM_ARAYA.zip\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-e2cba287-94eb-488c-ac7c-728d4b110847\">Download<\/a><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Project 10: Should I open the window? How to detect the optimal temperature and air flow for a room <\/h2>\n\n\n\n<p><strong>Authors<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Constanza MU\u00d1OZ FILIPPIG<\/li>\n\n\n\n<li>Francisco Javier CUESTA ELIAS<\/li>\n<\/ul>\n\n\n\n<p><strong>Abstract<\/strong><\/p>\n\n\n\n<p>Buildings are a vital stakeholder toward energy savings. Advanced research has been done on this<br>domain to adapt and change behaviors for an efficient use of the energy inside them. From using<br>better insulation materials to sensors acquiring data to make decisions on the optimal temperature or<br>amount of air flowing; these controls will allow to make cuts on the energy bill. Smart buildings are<br>currently developed not only on new construction projects, which are a must, but also on actual<br>existent buildings which are adapted to these new technologies to really generate an impact on<br>reducing energy consumption.<br>In this project, an analysis is made on the living room which includes multiple sensors. The data<br>obtained by them will undergo a treatment and a machine learning model will be executed to<br>understand the relation between these factors and answer to the following question: When is the right<br>moment to open the window considering to avoid bad indoor air quality. It\u2019s relevant to know what<br>can happen if air quality is not good and the effects it might have on the human body, taking into<br>account the recent development of diseases that can be transmitted through air such as COVID-19.<br>Temperature impact will also be taken into account for window opening.<\/p>\n\n\n\n<p><strong>Report<\/strong><\/p>\n\n\n\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MLO_BE2_Report_Munoz_Cuesta.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of MLO_BE2_Report_Munoz_Cuesta.\"><\/object><a id=\"wp-block-file--media-33f5a787-5348-4042-aa0e-15546406457c\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MLO_BE2_Report_Munoz_Cuesta.pdf\">MLO_BE2_Report_Munoz_Cuesta<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MLO_BE2_Report_Munoz_Cuesta.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-33f5a787-5348-4042-aa0e-15546406457c\">Download<\/a><\/div>\n\n\n\n<p><strong>Code<\/strong><\/p>\n\n\n\n<div class=\"wp-block-file\"><a id=\"wp-block-file--media-a3870c7b-5b53-49db-8639-382e38e838f1\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/be-2-smart-home-code_2023-01-30_1237.zip\">be-2-smart-home-code_2023-01-30_1237<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/be-2-smart-home-code_2023-01-30_1237.zip\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-a3870c7b-5b53-49db-8639-382e38e838f1\">Download<\/a><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Project 11: Should I open the window? How to detect the optimal temperature and air flow for a room <\/h2>\n\n\n\n<p><strong>Authors<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Juli\u00e1n Felipe Giraldo Cruz<\/li>\n\n\n\n<li>Hugo Ronaldo Paipa Chaparro<\/li>\n<\/ul>\n\n\n\n<p><strong>Abstract<\/strong><\/p>\n\n\n\n<p>Energy consumption in residential buildings depends for now in human behaviors, weather conditions, etc. During this report we want to predict the energy consumption in a residential building depending on the quantity of CO2, temperature and humidity using machine learning methods. Specifically in this study we used supervised learning with linear regression and Decision tree classifier.<\/p>\n\n\n\n<p><strong>Report<\/strong><\/p>\n\n\n\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/Report-Giraldo-Paipa-.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of Report-Giraldo-Paipa-.\"><\/object><a id=\"wp-block-file--media-e7c38b64-9867-4bf5-a277-572614857e6d\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/Report-Giraldo-Paipa-.pdf\">Report-Giraldo-Paipa-<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/Report-Giraldo-Paipa-.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-e7c38b64-9867-4bf5-a277-572614857e6d\">Download<\/a><\/div>\n\n\n\n<p><strong>Code<\/strong><\/p>\n\n\n\n<div class=\"wp-block-file\"><a id=\"wp-block-file--media-e76fae3a-1cfe-43d8-b03c-0195a4d2ca93\" href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MLO.zip\">MLO<\/a><a href=\"https:\/\/miniprojets.net\/wp-content\/uploads\/2023\/01\/MLO.zip\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-e76fae3a-1cfe-43d8-b03c-0195a4d2ca93\">Download<\/a><\/div>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Bonjour \u00e0 tous, Aujourd&#8217;hui, je vous propose la publication des articles produits par les \u00e9l\u00e8ves de 3\u00e8me ann\u00e9e de la&hellip;<\/p>\n","protected":false},"author":1,"featured_media":3556,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-3527","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-en-cours"],"_links":{"self":[{"href":"https:\/\/miniprojets.net\/index.php\/wp-json\/wp\/v2\/posts\/3527","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/miniprojets.net\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/miniprojets.net\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/miniprojets.net\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/miniprojets.net\/index.php\/wp-json\/wp\/v2\/comments?post=3527"}],"version-history":[{"count":0,"href":"https:\/\/miniprojets.net\/index.php\/wp-json\/wp\/v2\/posts\/3527\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/miniprojets.net\/index.php\/wp-json\/wp\/v2\/media\/3556"}],"wp:attachment":[{"href":"https:\/\/miniprojets.net\/index.php\/wp-json\/wp\/v2\/media?parent=3527"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/miniprojets.net\/index.php\/wp-json\/wp\/v2\/categories?post=3527"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/miniprojets.net\/index.php\/wp-json\/wp\/v2\/tags?post=3527"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}