Pandemic Emergency System
Introduction
The Covid Epidemic Emergency System aims to report people who suspected covid patients and it indicates what needs to be done, gives the necessary information and sends the necessary emergency teams to the venue. This system designed to reduce the increasing cases of covid, prevent any possible cases and purposes to secure public health.
Current System
The user reports the observed events using the phone application. The user gives the necessary answers to the questions that asked by the application and conveys the situation to the program. The program tells the user what to do and reports the incident to the necessary government units.
Proposed System
Functional Requirements
- User: “reporting”
- GPS System: “location”
- Dispather: “dispatchUser”, “sendInfoToDispatcher”, “dispatch”, “dispatchUnit”
- AI:“sendSuggestionAndInfoToReporter”, “suggestion”, “createIncident”, “manageIncident”, “saveIncidentToDB”
Nonfunctional Requirements
- Response time should be less than a second
- The server must be available 24 hours of a day.
- A system should not be result in data loss.
- The system must support 100,000 parallel reporting
- If a major incident happens on the app and, the we must take measures to go back to being fully operational within three days.
- The app’s interface has to be user-friendly and easy to use.
System Models
Scenarios
Scenario Name: covidSuspiciousOnSchool.
Actors: Efe: reporter, AyseBot:AI, Tuğcan: covidSuspect
Flow of Events:
1. Efe comes to the classroom for a biology lecture. After couple of minutes he observes Tuğcan with specified covid symptoms.
2. Efe reports the incident to AI by using the mobile app.
3. AI sends a form to Efe about the suspect's condition and environment.
4. Efe answers the questions that asked by AI.
5. AI receives the form and notifies dispatcher.
6. Dispatcher gets the submited forms and creates an incident.
7. Dispatcher sends the necessary units to location.
8- AI acknowladges the user.
ENTRY CONDITION: 2. Efe reports the incident to AI by using the mobile app.
EXIT CONDITION: Efe informed and units allocated.
Scenario Name: covidSuspiciousOnBus.
Actors: Ata: passenger, Alican: busDriver, AyseBot:AI
1.Ata takes a bus to go home. He notices a passenger that has covid sympthoms. He lets Alican know about this situation. Alican confirms and reports it by using mobile app.
2.Alican selects the options that descibes the incident best.
3.AI decides to emergency level and gives him suggestions.
4.AI tells (dispatches) to the Alican to drive to the appointed medical center and lets know the appointed medical center about the situation.
ENTRY CONDITION: Alican reports the case by using mobile app.
EXIT CONDITION: AI informs and gives instructions.
Use Case Model
Object Model
Dynamic Models
Design goals
Functionality V Usability
Rapid Development V Functionality
Cost V Robustness
Backward Compatibility V Readability
Efficiency V Portability
Proposed Software Architecture
Subsystem decomposition
Hardware/software mapping
Persistent data management
Access control and security
Boundary conditions
Subsystem Services
Glossary
reporting:The user reports to the app based on where he/she is and the suspect's symptoms.
suggestion: The application tells the user what to do instantly depending on the situation.
dispatchUser: If the user is in the vehicle, the application finds the nearest health facility, tells the suspect will come to health facility, and then tells the user where to go by means of navigation.
dispatchUnit: If it deems appropriate according to the application, environment and situation, it sends mobile health teams to the venue.
SendInfoToDispatcher: Dispatcher takes information of user input
dispatch: Dispatcher decides who to dispatch
location: Takes location information from GPS System
sendSuggestionAndInfoToReporter: AI gives information about dispatch and suggestion to user.
CreateIncident: AI creates incident report
saveIncidentToDB: AI saves incident to the database
manageIncident: AI manages the incident