Evaluating Sensor Data in the Context of Mobile Crowdsensing

Blasi, Maximilian (2022) Evaluating Sensor Data in the Context of Mobile Crowdsensing. Masters thesis, Ulm University.

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With the recent rise of the Internet of Things the prevalence of mobile sensors in our daily life experienced a huge surge. Mobile crowdsensing (MCS) is a new emerging paradigm that realizes the utility and ubiquity of smartphones and more precisely their incorporated smart sensors. By using the mobile phones and data of ordinary citizens, many problems have to be solved when designing an MCS-application. What data is needed in order to obtain the wanted results? Should the calculations be executed locally or on a server? How can the quality of data be improved? How can the data best be evaluated? These problems are addressed by the design of a streamlined approach of how to create an MCS-application while having all these problems in mind. In order to design this approach, an exhaustive literature research on existing MCS-applications was done and to validate this approach a new application was designed with its help. The procedure of designing and implementing this application went smoothly and thus shows the applicability of the approach.

Item Type: Thesis (Masters)
Subjects: DBIS Research > Master and Phd-Thesis
Divisions: Faculty of Engineering, Electronics and Computer Science > Institute of Databases and Informations Systems > DBIS Research and Teaching > DBIS Research > Master and Phd-Thesis
Depositing User: Robin Kraft
Date Deposited: 25 Jan 2023 15:04
Last Modified: 25 Jan 2023 15:22
URI: http://dbis.eprints.uni-ulm.de/id/eprint/2151

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