Social Application Development with Crowd Sensing and Big Data

OData support
Supervisor:
Dr. Forstner Bertalan
Department of Automation and Applied Informatics

The aim of this thesis was to design and create a social dating application which provides an opportunity to socialize with the modern and growing use of smartphones. This whole new dating method is a fast and convenient way to connect to users whose field of interests are the same. However, the system is safe enough, only the matched users (confirmed interest from both directions) are able to view each other’s personal data and locations and have the right to chat to each other.

The operation of the system requires a large amount of user data, since finding couples is more likely with multiple users. The data are produced exclusively on mobile clients, which can be personal information provided by users themselves or location information automatically collected by the mobile application. The latter implements the principle of crowd sensing.

On the server side, I have used the big data solution of Hadoop to store and analyse the data. This enabled efficient storage and processing. The core of the system is the matchmaking algorithm, which creates connections based on user data between users with similar interest, was implemented with Java Enterprise Edition environment. This same environment provides the interface for the iOS mobile application in my thesis as well.

During the design of the system I had the opportunity to get to know and practice the technologies I used. I gained experience in the areas of Java Enterprise Edition environment, Hadoop’s big data solution, and designing of the REST communication interface. In addition, I extended my knowledge of the iOS platform. My thesis gave a real opportunity to fully design, implement and test a distributed application.

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