Rescuer: Emergency Mobile App with Voice Recognition, Volume Key Pattern, Location SMS Reciprocation, & Push-Aid Systems

Overview

Objectives/Goals To construct an efficient mobile application that can send panic messages with the user's location in the case of an emergency. It should implement the following four features: 1. Voice Recognition: Rescuer should send out emergency messages with a geocoded location link by recognizing the user's spoken keyphrase. 2. Volume Key Pattern: Rescuer should send out emergency messages with a geocoded location link when a user presses the device's volume buttons in a custom pattern. 3. Location SMS Reciprocation: When another qualified contact sends a specific text message to the Rescuer equipped device, Rescuer should detect the keyword trigger and return the device location. 4. Push-Aid: Rescuer should implement a flexible layout fragment that can be accessed via the phone's home screen as a widget to send emergency messages. Methods/Materials To develop Rescuer, I first coded the background Java processes. Here I utilized the CMUsphinx voice recognition library for unique 24/7 recognition and multithreaded my application for optimal CPU usage. After building the brains of the app, I moved on to perfecting the user interface using XML and following Google's Material Design Guidelines. A finished product was created only after testing the application on over 100 emulated devices. Results Rescuer not only gathers the most accurate location, but is also memory (0% crash rate), CPU (<30% usage), and battery (<5% per charge) efficient. Response time is instantaneous. Finally, Rescuer does not require access to Wi-Fi or Mobile Data, making it universally available. Conclusions/Discussion I have developed a fully functional emergency mobile application that can reach out to custom emergency contacts in a crisis. No mobile app has ever utilized 24/7 voice recognition, background volume button detection, or continuous SMS recognition as tools for signalling for help in an emergency.

Awards (1)

• Honorable Mention

Competition history

• CSEF 2017 Computational Systems & Analysis · Entry S0801

Resources

• CSEF project summary ↗

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