Development of mobile application for determining authenticity of media file
DOI:
https://doi.org/10.33216/1998-7927-2023-279-3-5-10Keywords:
authenticity, geodata, sensor, media file, mobile applicationAbstract
The article considers the task of developing a mobile application for collecting, analyzing, and visualizing geodata from multimedia files to solve the problem of identification and authenticity of media materials, since existing solutions do not use a group of tags called "extensions" of files of the standard GPX format, that is, additional data obtained from mobile device sensors, including waypoints, tracks, and routes. Unlike them, the developed mobile application allows you to compare the data from the sensors in the media files with the data of the specified area, thereby identifying and establishing the authenticity or falsification of the file. Recently, this has become more and more especially relevant, as thanks to media materials, it is possible to reliably prove whether any manipulations have been carried out with the file, which confirms or refutes the authenticity of events in various spheres of life, even in the legal and analytical spheres. Also, the mobile application allows you to create video files stored in the device's local storage together with GPX and CSV files containing data obtained during shooting from common sensors and services built into many modern mobile devices. The developed mobile application allows you to visualize geodata in Google Map, and display data from sensors (accelerometer, gyroscope, geomagnetic sensor) on the video player panel along with the calculated angle of inclination of the device and the distance to the object thanks to trigonometric formulas. During the implementation of the mobile application, such tools were used as the development environment - Android Studio Giraffe, the programming language for the Android system, the well-known developer JetBrains - Kotlin, the library for implementing the Dependency Injection programming pattern - Hilt, the library for visualizing the user's geolocation on the map - Google Maps, video player for the Android system - Exo Player. The mobile application has a simple and intuitive interface, is supported by the Android 5.0 operating system and above (that is, it is supported on 99% of all Android devices), is not demanding on resources, and has a flexible and modular Google Android App Architecture.
References
1. Leiva A. Kotlin for Android Developers: Learn Kotlin the easy way while developing an Android App / А. Leiva // CreateSpace Independent Publishing Platform. – 2016. – 240 р.
2. Derkach M. Parking Guide Service for Large Urban Areas / M. Derkach, V. Lysak, I. Skarga-Bandurova, I. Kotsiuba // 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). - Metz, France, 2019. – pp. 567 – 571.
3. Grinshpan А. Comparative Analysis of GPS Data / A.Grinshpan, S.Campbell // Undergraduate Journal of Mathematical Modeling: One + Two. - 2014. - Vol. 5, Iss. 2.
4. Skarga-Bandurova I. A Framework for Real-Time Public Transport Information Acquisition and Arrival Time Prediction Based on GPS Data / I. Skarga-Bandurova, M. Derkach, A. Velykzhanin // Dependable IoT for Human and Industry: Modeling, Architecting, Implementation (Eds. V. Kharchenko, Ah L. Kor, A. Rucinski). – River Publishers Series in Information Science and Technology, 2018. – P. 411-431.
5. Siuhi S. Opportunities and challenges of smart mobile applications in transportation / S. Siuhi, J. Mwakalonge // Journal of traffic and transportation engineering (english edition). – 2016. – No. 3 (6). – P. 582 - 592.
6. Basyir M. Determination of Nearest Emergency Service Office using Haversine Formula Based on Android Platform / M.Basyir, M.Nasir, Suryati, Widdha Mellyssa // EMITTER International Journal of Engineering Technology. - 2017. - Vol. 5, No. 2.
7. Manish J. Gajjar. Mobile Sensors and Context-Aware Computing / Gajjar J. Manish // Cambridge, MA: Morgan Kaufmann. – 2017. – 337 р.
