How kavicente/nowalert works
AlertNow is a multi-agency emergency alert and response system: users submit incident alerts, the server routes them to agency dashboards in real time, agencies record responses, and dashboards provide incident analytics and prediction outputs. The excerpts show alert handling, Socket.IO dispatch, response persistence, and some chart/report queries; unsampled routes and model-loading details limit how precisely other workflow links can be drawn.
Main entry points: users_web.db Application database · analytics.js Analytics client · AlertNow.py Alert server · submission.py Agency responses
Components 20
Accounts and Access
- Agency login
AgencyIn.py - Account registration
AgencyUp.py - Public signup
SignUpPage.py - Password reset
PassReset.py
Alerts and Response
- Alert server
AlertNow.py - Agency responses
submission.py - Live alert client
static/js/dashboard.js
Analytics and Prediction
- Incident datasets
dataset - Prediction code
models.py - Road prediction code
road_models.py - Trained models
training - Role chart endpoints
BarangayCharts.py - Health charts
HealthCharts.py - Hospital charts
HospitalCharts.py - DILG reports
DILGDashboard.py - Analytics client
static/js/analytics.js
Application State
- Application database
database/users_web.db
Other components
- Alert submitters
- Agency users
- Web dashboards
Connections 26
- Agency users → Agency login: signs in
- Agency login → Application database: checks accounts
- Agency users → Account registration: registers
- Account registration → Application database: stores account
- Alert submitters → Public signup: creates account
- Public signup → Application database: stores account
- Alert submitters → Password reset: requests reset
- Password reset → Application database: updates credentials
- Alert submitters → Alert server: submits alert
- Alert server → Application database: writes incident
- Alert server → Live alert client: broadcasts alerts
- Live alert client → Web dashboards: updates dashboard
- Agency users → Agency responses: submits response
- Agency responses → Application database: saves response
- Agency responses → Live alert client: emits updates
- Incident datasets → Prediction code: provides training data
- Trained models → Prediction code: supplies models
- Trained models → Road prediction code: supplies forecasts
- Role chart endpoints → Application database: queries incidents
- Health charts → Application database: queries incidents
- Hospital charts → Application database: queries responses
- DILG reports → Application database: queries reports
- Web dashboards → Analytics client: views analytics
- Analytics client → Role chart endpoints: requests charts
- Analytics client → Health charts: requests charts
- Analytics client → Hospital charts: requests charts