GovTech / Infrastructure Monitoring

Z-SIMP Operational Demo Platform

A modular monitoring platform for water and infrastructure oversight, combining dual-mode ingestion — real public sensor telemetry plus a synthetic disaster simulator — with anomaly detection, incident workflows, public reporting, and responsibility-aware operations.

FastAPIReactVitePostgreSQLInfluxDBScikit-learnDockerNginx
Data modesLive + Simulation
Monitored sensors12
Disaster scenarios4
Infra packagingDocker + Nginx
Z-SIMP operations command console with system health strip and national coverage rollups

Role focus

Full-stack architecture, monitoring workflows, operational dashboard design

Frontend buildAutomation coverage

Project narrative

This is one of the strongest systems projects in the archive because it treats monitoring as an operational product, not just a charting exercise. The stack spans simulation, detection, persistence, command workflows, public visibility, and infrastructure packaging.

Why it matters

Strong systems-thinking signal

Clear evidence of workflow design and domain modeling

Useful flagship project for backend and operational software roles

Preview Gallery

Visuals that make the project story land faster.

Interface views and system visuals that help the product story read quickly. Tap any screenshot to view it full size.

Architecture map

Frontend

React and Vite power an operational console with incident workflows, coverage views, approval panels, public status surfaces, and live monitoring components.

Backend

A FastAPI service layer handles a live public-telemetry feed (default) alongside a synthetic simulator, anomaly detection, command workflows, notifications, auth, event-bus behavior, and persistence orchestration.

Data and infra

PostgreSQL stores alerts and incidents, InfluxDB handles time-series data, and infra assets package the system for deployment-style presentation.

Engineering Decisions

This is where the software engineering depth shows up.

Beyond features, this section highlights the structural choices that shape scalability, reliability, and product clarity.

Used rolling IQR plus domain rules as the primary detection strategy, with ML augmentation layered in as support rather than replacing explainable logic.
Modeled the platform around operators, approvals, public visibility, and response tracking instead of stopping at sensor charts.
Split persistence between time-series and operational records to keep storage aligned with usage patterns.

Validation snapshot

Frontend build

The Vite frontend production build passed during the audit.

Automation coverage

No dedicated automated test suite was detected in the repository.