projets:plim:20142015:gr7
Différences
Ci-dessous, les différences entre deux révisions de la page.
| Les deux révisions précédentesRévision précédenteProchaine révision | Révision précédente | ||
| projets:plim:20142015:gr7 [2014/11/10 09:14] – bitschen | projets:plim:20142015:gr7 [2014/11/22 17:38] (Version actuelle) – bitschen | ||
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| === Name of the members of the Group === | === Name of the members of the Group === | ||
| - | | + | |
| - | * Quentin | + | |
| - | * IHM | + | * **Lastname**: |
| - | * bitschen@polytech.unice.fr | + | * **Class**: |
| - | * Da Mota | + | * **Mail**: |
| - | * Anthony | + | |
| - | * IHM | + | * **Firstname**: |
| - | * anthony.damota06@gmail.com | + | * **Lastname**: |
| - | * Martinez | + | * **Class**: |
| - | * Hugo | + | * **Mail**: |
| - | * IHM | + | |
| - | * hugo.83300@gmail.com | + | * **Firstname**: |
| + | * **Lastname**: | ||
| + | * **Class**: | ||
| + | * **Mail**: | ||
| === Equipments === | === Equipments === | ||
| - | * HTC 8S | + | * **Model**: |
| - | * Téléphone personnel | + | * **Personal phone**: NON |
| - | * IMEI : 353760058901069 | + | |
| === Content of the Project === | === Content of the Project === | ||
| - | // quelques lignes sur le projet | + | // Abstract |
| - | Notre projet a pour but d' | + | |
| - | Plusieurs type de mouvement pourront être détecté. | + | |
| - | // indiquer les données collectées sur le téléphone, | + | This project consists in programming a Widows Phone application with C# using sensors and learning algorithm. We choosed the accelerometer as our sensor. |
| - | // indiquer les informations que vous voulez obtenir après traitement (classification ...) des données collectées// | + | The main goal of our project is to detect 4 kind of movement : |
| + | * Static | ||
| + | * Walking | ||
| + | * Fast walking | ||
| + | * Running | ||
| - | // indiquer la manière dont vous présenterez les informations obtenues à l' | + | To do that we will use the combination between the measures we can get from the accelerometer and the use of the K-means clustering algorithm on those measures. |
| - | // indiquer si vous souhaitez utiliser les informations | + | The accelerometer allow us to get 3 measures : X, Y and Z. Those 3 values represent the acceleration in a three dimensions space. In the project we use the Accelerometer object which allows us to get all those informations, it's our API, and it comes from the namespace Microsoft.Devices.Sensors. |
| + | We want to get two clusters that allow us to determine an average of the amplitude and frequency of our movement. To do that we use the alglib library that contains an implementation of the Kmeans algorithm, that implementation is really easy to use and is entirely configurable (you can chose the number of dimension of your sample for example).You can find it at the following URL : [[http:// | ||
| - | === SOFTWARE PACKAGES | + | It s the répartition of the points in those two clusters that permits to determine which kind of movement |
| - | * README File | + | We choosed to show the variation of the accelerometer to the user through two interface elements : |
| - | // an README file to explain all you install from Visual Studio 2013 SP2 with the SDK WP8.0 or later, | + | * Three textblocks |
| + | * Three vectors | ||
| - | * Project zip file | + | The user chose when he wants to start the record and when when to stop it with the start and stop button. When the user presses the start button, we begin to record. We store the accelerometer' |
| - | // add the zip file of the Project // | + | |
| - | * All required softwares | + | When the execution is finished, we show all clustering informations to the user in a Popup : |
| - | //Put all the links and explanations to install and to configure required softwares, before your WP8.X C# project// | + | |
| + | | ||
| + | * the movement induced by the analysis of those informations | ||
| - | === HOW TO USE IT === | ||
| - | // here write step by step how to use your project // | + | We didn't have time to, but we could associate the movement recognition with some actions |
| - | // you can add copies of screen | + | |
| - | === RESULTS | ||
| - | // Write a summary | + | === SOFTWARE PACKAGES |
| - | === Optionnal but considered in the evaluation : An 2 pages ACM paper on your results ==== | + | * README File |
| - | // Optionnal but considered in the evaluation | + | Link to the README: [[https://docs.google.com/ |
| - | //if you finnd enough time, you can write a 2 pages paper about your project in a professional ACM format. This paper will be submitted to other researchers in the field and perhaps to present | + | * Project zip file |
| - | // | + | [[https://drive.google.com/file/d/0Bwx2Jhz4oCg5VHJHMTVHZjhydU0/view? |
| - | **A Paper ACM Format :** | + | * All required softwares |
| - | [[http:// | + | You just need to install the WP8.1 SDK and Visual Studio 2013 |
| + | === HOW TO USE IT === | ||
| - | === CONSIGNES ET RAPPELS === | + | Our projetct is really easy to use : |
| - | == Quelques consignes : == | + | - Go on your windows phone' |
| + | - Chose GestureRecognizer application | ||
| + | - Push the start button to start the recording | ||
| + | - Do whatever you want, like walking, running, or just stand there. | ||
| + | - Push the stop button and you get the clusters informations and detection' | ||
| + | |||
| + | === RESULTS | ||
| - | - // Warning | + | The main result of this project is that we are now able to detect some specific speed of movement like walking or running, but besides that, the realisation of this project made us learn : |
| - | - // Warning : every added file (ex. figures, picture, sources, binaries, video ...) must be added through | + | - How to develop |
| - | - //For more informations | + | - How to create an interface with .xaml files |
| + | - Developping in C# Silverlight | ||
| + | - How to exploit datas from phone sensors (Accelerometer | ||
| + | - How to use Kmeans algorithm to make clusters and use clusters | ||
projets/plim/20142015/gr7.1415610841.txt.gz · Dernière modification : 2014/11/10 09:14 de bitschen