S.A. Gros – Student, 

Department «Information Systems and Networks», Kaluga Branch of the Bauman MSTU

Е-mail: Sergey.Gros@gmail.com

T.A. Onufrieva – Ph.D. (Eng.), Associate Professor, 

Department « Information systems and networks», Kaluga Branch of the Bauman MSTU

E-mail: onufrievata@mail.ru

The article discusses the application of the clustering algorithm for the developed system for monitoring transport in the urban environment. The monitoring system of urban transport is one of the pressing problems of various industries in which there is transport. Online transport monitoring can improve business efficiency. The stage of visualization of movement in such systems is the main for the user and makes it easy enough to track the necessary vehicles. The author emphasizes that increasing the readability of the map, as well as reducing the cost of device resources for displaying objects, is one of the main tasks facing developers. The paper presents the application of an algorithm that provides a comfortable reading of the map and solves the following problems - reducing the memory occupied by the coordinates and resource consumption of the device, which reduces the frequency of the program freezes. To achieve this goal, the author performed an analysis of existing clustering methods. In the system described by the author, the basic information for determining the location of objects is data obtained from sensors located on the monitored vehicle. The received data is sent to the server and entered into the database. Data from the server is transferred to the device in JSON format and transferred to the card. The user receives information about the status of monitored objects on a mobile application. The mobile application implements two main stages of work - the collection and processing of information about objects from sensors located on monitored objects and visualization of traffic based on this information. The stage of collecting information from the server involves the use of standard technologies for the exchange of information between the mobile device and the server. The application is designed to work on Android smartphones, since this platform is highly popular among users.

For the method described in the article, the source data are the coordinates of the monitored objects. On the mobile device, the received coordinates of the objects are processed (clustering), followed by display to the user. During the article, an application for monitoring transport is considered, in which data is displayed to the client in the form of cluster icons included in the user's visibility area.

The author describes how to combine data into groups, the k-means algorithm was used with the number of clusters required. During the execution of this algorithm, iterations are performed on the grouping of objects. The implementation of the algorithm is presented in detail in the work. The result is issued to the user in the form of objects on the map. The article emphasizes that the feature of the work is the implementation of this algorithm on the client side.

At the end of the article, the author gives conclusions about the results of the considered algorithm in the developed system and shows how much the efficiency of the system has been increased.

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