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An Android-based Crime Data Collection and Analytics: An Integrated Framework
| International Journal of Applied Information Systems |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 13 - Number 2 |
| Year of Publication: 2026 |
| Authors: Sophie Uwho, Ifeoma B. Asianuba |
10.5120/ijais2026452044
|
Sophie Uwho, Ifeoma B. Asianuba . An Android-based Crime Data Collection and Analytics: An Integrated Framework. International Journal of Applied Information Systems. 13, 2 ( Feb 2026), 11-17. DOI=10.5120/ijais2026452044
Abstract
In many developing countries, crime reporting is on the decline. It involves manual processes, and could be inaccessible, thereby reducing the responsiveness of law enforcement agencies and weakening public trust. Leveraging the widespread availability of mobile devices, the study presents an integrated Android-based intelligent crime reporting and analytic framework that incorporates geolocation, multimedia evidence captures, Naïve Bayes classification, and exponential smoothing forecasting for proactive public safety management. The application was developed using the Flutter framework to ensure a responsive and user-friendly interface, while backend functionalities were implemented using PHP and MySQL. The Naïve Bayes classifier achieved an accuracy of 88.6%, while exponential smoothing forecasting attained a Mean Absolute Percentage Error (MAPE) of 8.55%, indicating excellent predictive performance. Usability testing involving 130 participants demonstrated high acceptance, with 96% reporting ease of navigation and 92% highlighting the accuracy of GPS-based reporting. The system offers a scalable, user-friendly, and technologically solution for enhancing public security.
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