by Six Pack (B21-CAP0031)
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Did you know that a huge amount of emergency cases remain unhandled? Some of the victims may lose their lives because of the long response time of the emergency service. While emergency services must always be a priority, we are here to help Indonesia to have a better emergency service. 🇮🇩
Our app implements machine learning technology to correctly generate reports from user voice and automatically send it to the responser app. Our superior technology can accelerate responders to respond appropriately according to the user’s needs and could save many lives.
| No. | Dir | Details |
|---|---|---|
| 1 | EmergencyApp |
User application: for emergency reporting, see news, and see tips while in emergency situation. |
| 2 | ResponderApp |
Reponder application: the app used for responders to read the automated reports and update status on the emergency case. |
| 3 | assets |
Contains all images for this repository. |
| 4 | build_df |
Processing data from scraping result, generate train and test data for Machine Learning |
| 5 | classification |
Classify user report to its label. |
| 6 | data |
Consists all data: raw, preprocessed, filtered, data for classification and NER. |
| 7 | flask |
Contains the code to create an API to do ML inferences by the Android App. |
| 8 | ner |
Extract entities from user's voice transcription. |
| 9 | scraping |
Gathered data or scraping through this website. |
To get a local copy up and running follow these simple example steps.
DISCLAIMER: This app will only work when the admin of the cloud server has opened the SSH connection to the android in order to run ML inferences. But you can set up your own virtual machine in your own cloud console.
This is an example of how to list things you need to use the software and how to install them.
- Android emulator or device
- Internet connection
- Location services (GPS)
- Setup cloud server: for more info about setting up the cloud server, click this link
Once you have followed the instructions in how to setup the cloud server you must:
- Go to your app level
build.gradle - Modify this part: (
YOUR_NER_BASE_URL,YOUR_CLASSIFICATION_BASE_URL)
android {
.....
defaultConfig {
.....
buildConfigField('String','NER_BASE_URL','"YOUR_NER_BASE_URL"')
buildConfigField('String','CLASSIFICATION_BASE_URL','"YOUR_CLASSIFICATION_BASE_RUL"')
.....
}
.....
}
There are two ways in which you can install this app.
Firstly you can fork this repository and run either one of these projects:
EmergencyAppResponderAppOn your android studio to be installed in your emulator/device
Or you can download our APK at this link
Use this space to show useful examples of how a project can be used. Additional screenshots, code examples and demos work well in this space. You may also link to more resources.
For more examples, please refer to the Documentation
Distributed under the MIT License. See LICENSE for more information.
insert picture here
| name | github | |
|---|---|---|
| Annisa Nuri Nabila |  |
 |
| Brian Mohammed Catraguna | |
|
| Fadia Hanifa Suwandoko | |
|
| Michael Wijaya | |
|
| Rahmat Syawaludin | |
|
| Septin Lutfiyatul Munawaroh | |
|
1. Hossain, M. M., Sharmin, M., & Ahmed, S. (2018). Bangladesh Emergency Services. Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies. https://doi.org/10.1145/3209811.3209870
2. Edillo, Shallom & Garrote, Pamela & Domingo, Lucky & Malapit, Arianne & Fabito, Bernie. (2017). A mobile based emergency reporting application for the Philippine National Police Emergency Hotline 911: A case for the development of i911. 1-4. 10.23919/ICMU.2017.8330110
3. Klein, B., Laiseca, X., Casado-Mansilla, D., López-de-Ipiña, D., & Nespral, A. P. (2012). Detection and Extracting of Emergency Knowledge from Twitter Streams. Ubiquitous Computing and Ambient Intelligence, 462–469. https://doi.org/10.1007/978-3-642-35377-2_64
