Dead reckoning solution for mass surveillance systems

OData support
Dr. Simon Vilmos
Department of Networked Systems and Services

We can see a rising popularity of festivals and events from year to year . Beside the fun they come with danger. That is why organizers are in need for an effective mass surveillance system that helps monitoring mass dynamics changes, to forecast and prevent mass disasters. To minimize the infrastructure costs, we can use the smartphones of participants to gather information about their location with the energy efficient dead recknoning method. By processing the data on the servers, we can gain information about the mass dynamics’ variables of the event, which enables us to forsee and prevent disasters.

Unlike GPS, dead reckoning is much more energy efficient for the smartphone users, does not drain the user’s battery quickly, which is a scarse resourse at a mass gathering. However it is accurate enough to provide us the mass dynamics most important state variables on time.

Developing and implementing the dead reckoning algorithm on a smartphone is a great challenge which I chose as the goal of this TDK work.

In my work mass surveillance systems are presented, furthermore the development of my dead reckoning algorithm, with the pros and cons compared with the GPS based track recording, together with the sensors which I use to gather data to calculate the trace.

I have implemented my algorithm on an iOS platform, presenting the functions and features of the application in my work and I also showing examples of the iOS specific developing process.

I conclude my work with a validation of my algorithm with real measurements tests. I have compared traces recorded with handheld and in-pocket smartphones with GPS based traces and the real trajectory.


Please sign in to download the files of this thesis.