CALAMITIPS: An Android Mobile Applications using Kalman Filter Algorithm

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Abstract

The study is an Android mobile application which promotes and implements risk reduction awareness and preparedness to the community. It connects Virtual Reality in terms of giving interactive user experience, in a way of educating users about the importance of participating in risk reduction seminars, and drills or activities. CalamiTips provides two main features for the user. First is the VR mode, where the user experience being in a situation before, during, and after the disaster / calamity. Second is the screen mode, where the user can still visualize the scenario, even without the use of VR box or VR equipment. The application also provides reader’s mode where all the gathered information is in text form, including guidelines on disaster / calamity and emergency hotlines. The study used Kalman Filters as an algorithm in developing the mobile application. Predictive tracking is used in VR to forecast position of an object and its trajectory. This makes Kalman Filters a common choice in this kind of application. The proponents will use the V-Model since it strictly follows important phases on the development of the system, and it also does verification and validation in the phase of testing. To be able to install the mobile application, the target device should be running the Android Operation System. The minimum Android Version supported is Android 4.4 'Kit Kat' (API level 19) or higher.

Keywords

Android Application, Calamity Mobile Application, Kalman Filter Algorithm, Virtual Reality

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APA 7th Edition:
Mojica, A., Cantila, B., Gomez, L., & Presco, J. (2019). CALAMITIPS: An Android Mobile Applications using Kalman Filter Algorithm. Innovatus, 2(1), 16-19.
Harvard:
Mojica, A., Cantila, B., Gomez, L. and Presco, J., 2019. CALAMITIPS: An Android Mobile Applications using Kalman Filter Algorithm. Innovatus, 2(1), pp.16-19.
IEEE:
[[1] A. Mojica, B. Cantila, L. Gomez and J. Presco, "CALAMITIPS: An Android Mobile Applications using Kalman Filter Algorithm", Innovatus, vol. 2, no. 1, pp. 16-19, 2019.

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