Différences

Ci-dessous, les différences entre deux révisions de la page.

--- projets:plim:20142015:gr17 [2014/11/23 15:57] – [MAIN INFORMATIONS about the Project] ouhichi
+++ projets:plim:20142015:gr17 [2014/11/23 22:55] (Version actuelle) – [MAIN INFORMATIONS about the Project] ouhichi
@@ Ligne 46: / Ligne 46: @@
 ==  I- Project Description : ==
-Born from the idea of creating an application which makes a classification of persons per profile whether on foot, by bicycle or by car.
+Born from the idea of creating an application which makes a classification of persons per profile whether on foot, by bike or by car.
 Speed application provides users with their current location,speed and other informations and allows them a grouping of their visited places.
@@ Ligne 65: / Ligne 65: @@
 •	Longitude
 •	Altitude
-•	Time of fix
 •	Status
-•	NumSats
+•	Speed
 •	Bearing
-•	Speed
 We can say also that GPS Sensor have some options like displaying it automatciclly when it's closed  by selecting "Show GPS Sensor" when GPS pane is closed check box or to close it and showing the GPS pane.
@@ Ligne 129: / Ligne 126: @@
 This local DB uses LINQ to SQL to allow an object-oriented approach in order to work with data and comprises an object model and a runtime.
-== III- Application functionalities : ==
+== III- Project Step by Step : ==
+**1. Data Collection**
+The GPS Sensor used in our project allows the users to determine their position, their speed and the hour of day in earth, at sea and in the air 24/ 24 hour, in all weathers and to any place in the world.
+In the launch of the application, there will be a restoration and a recovery of all these data then posting them on the first interface «transportation mode”.
+**2. Data Storage**
+Once Data are collected it will be stored in a local data base.
+The local DB will be useful on one hand to apply various processing like classification and on the other hand to
+Keep a journalisation of the activities of the users and the possibility of displaying them at the needs.
+**3. Profiles classification**
+After collecting Data we apply a classification by speed on users in order to obtain finally 3 profiles whether on foot, by bike or by car.
+And this classification will be marked on our page with small images which signify each case.
+**4. Clustering**
+In our application once profiles are classified we ally K-means algorithm to have a clear distribution in form of group of the places the most visited and seen frequently by the users.
+These cluster will be shown on the maps and marked with circles.
+== IV- Application functionalities : ==
@@ Ligne 174: / Ligne 202: @@
 The final result of our project is to have a clear classification of users according to their profiles as well as a classification by cluster of their busiest and most visited place.
+Our application emphasizes the importance of the non-supervised classification and presents a direct resolution of the recognition of the modality of the transport problem of our everyday life.
 ===  2 pages ACM paper on our results ====
@@ Ligne 182: / Ligne 211: @@
-[[https://github.com/HAYKEL88/Speed-Clustering/blob/master/Vitess++/Assets/ACM_Word_Paper.pdf?raw=true|Word ACM Format PDF Version ]]
+[[https://github.com/HAYKEL88/Speed-Clustering/blob/master/Vitess++/Assets/ACM_Word_Paper1.pdf?raw=true|Word ACM Format PDF Version ]]
-[[https://github.com/HAYKEL88/Speed-Clustering/blob/master/Vitess++/Assets/ACM_Word_Paper.doc?raw=true|Word ACM Format DOC Version ]]
+[[https://github.com/HAYKEL88/Speed-Clustering/blob/master/Vitess++/Assets/ACM_Word_Paper1.doc?raw=true|Word ACM Format DOC Version ]]