Abstract
In developing countries such as Bangladesh, social and economic development is often hindered by lack of civilian safety due to increasing crime rate. In this paper, we have attempted to devise a solution to help citizens avoid potentially dangerous locations using data analytics. We designed and developed a system named “Sachetan”, which is a mobile application that enables its users to privately share their own experience of incident occurrences with precise spatial and temporal information. Two data sources are combined and statistical insight and graphical representation of patterns have been presented to the users. In our research, we tried to find the pattern and determine the movements of high-frequency incident areas by analyzing the data.
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Acknowledgements
This work was done at the Innovation Lab, Department of CSE, SUST. We would like to thank all staff, faculty, and anyone who helped us take our research forward.
Informed consent was obtained from all individual participants included in the study.
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Mohammad, S.N., Hossain, S., Rahman, M.M., Das, M., Amin, M.R. (2019). Sachetan: A Crowdsource-Based Personal Safety Application. In: Abraham, A., Dutta, P., Mandal, J., Bhattacharya, A., Dutta, S. (eds) Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing, vol 813. Springer, Singapore. https://doi.org/10.1007/978-981-13-1498-8_43
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DOI: https://doi.org/10.1007/978-981-13-1498-8_43
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