Full Stack•Full-Stack Engineer•2026•Rubric Score: 4.60/5.0

Campus Environment Data Visualization System

Full-stack Python telemetry platform with Plotly Dash analytics, EPA AQI indexing, and multi-zone surveillance.

Full-stack Python system engineered to ingest, store, process, analyze, and visualize ambient and indoor environmental telemetry across 8 university campus zones. Features a Flask WSGI core, embedded Plotly Dash interactive dashboards, SQLAlchemy ORM, and automated alert resolution.

8 Zones

Campus Zones

27 Passed

Pytest Tests

7 Parameters

Sensed Metrics

View verified GitHub repo Open verified live demo

The Problem & Intended Users

Modern universities host thousands of students in enclosed lecture halls, crowded study libraries, cafeterias, and high-traffic gates where poor ventilation (CO2 > 1000 ppm, fine particulates PM2.5) and acoustic pollution degrade cognitive performance and student health, yet manual spot-checks fail to detect acute spikes.

Architecture & Implementation Decisions

Engineered an end-to-end Python monitoring ecosystem with mathematical diurnal atmospheric simulation models, dynamic EPA piecewise linear interpolation for AQI calculation, ASHRAE thermal comfort indices, 5-axis normalized radar matrices, and role-based access control.

Technical Architecture Pipeline:

Dual-engine Python architecture combining Flask WSGI routing and REST API endpoints (`/api/zones`, `/api/sensors`, `/api/readings`, `/api/alerts`) with reactive Plotly Dash components (`/dashboard/`). Backed by SQLAlchemy 2.0 ORM, SQLite embedded database, Pandas aggregations, and Flask-Login authentication.

Source-Verified Capabilities

Role-Based Access Control (RBAC) with secure Admin sensor management and Public dashboard views

Campus Environmental Health Index (CEHI) weighted grading (A+ to F) evaluating AQI, acoustics, and comfort

Dynamic US EPA Air Quality Index (AQI) piecewise linear interpolation for PM2.5 and PM10

Multi-dimensional Plotly 5-axis spider radar matrix comparing 8 campus zones simultaneously

Synthetic sensor telemetry engine modeling solar diurnal curves and class occupancy spikes

Interactive REST API documentation and query explorer console (`/api/docs`)

Measurable Results & Delivery

A complete, publication-grade environmental analytics dashboard deployed live on GitHub Pages with 27 unit and integration tests executing seamlessly in pytest, seed scripts for 7+ days of synthetic telemetry, and instant CSV reporting.

27 unit and integration tests passing via pytest covering models, REST API endpoints, and Dash callbacks.

Verified Technologies & Tools

PythonFlaskPlotly DashSQLAlchemyPandasPytest

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