Explore the platform architecture, environmental intelligence workflows, AI capabilities, and implementation patterns behind GreenGuard AI.
GreenGuard AI is an environmental intelligence platform that unifies real-time environmental monitoring, meteorological forecasting, AI-assisted analysis, citizen reporting, and municipal authority workflows into a single cohesive system.
Access real-time AQI and weather indicators, submit geo-tagged complaints with photo evidence, track resolution progress, and interact with the AI assistant.
Receive assigned complaints within departmental jurisdiction, review severity scores, record investigation notes, submit resolution evidence, and resolve cases.
Triage and verify incoming citizen reports, route cases to appropriate authorities, manage monitored city parameters, and oversee system governance.
Key operational entry points across the platform for exploring data, submitting issues, and managing environmental workflows.
Understand current environmental conditions, active alerts, and key environmental indicators across monitored cities.
View pollutant measurements (PM2.5, PM10, NO2, O3, SO2, CO), historical trends, and AI-assisted insights.
Report environmental issues like garbage burning, water contamination, or smoke with photo evidence.
Understand how administrators review, verify validity, prioritize, and assign complaints to departments.
Learn how authority personnel receive assigned complaints, conduct investigations, and submit resolution details.
Review 7-day weather and air quality forecasting, city EcoScore metrics, and run policy impact simulations.
Every module is designed to solve a specific facet of urban environmental monitoring, forecasting, decision-making, and public collaboration.
Real-time environmental monitoring, AQI indicators, and operational alert feeds.
Comprehensive pollutant metrics, air & water indices, and historical trend analysis.
7-day meteorological and AQI forecasting with confidence intervals and weather outlooks.
Context-aware AI copilot for natural-language environmental analysis and recommendations.
Civic portal for geolocation-tagged complaint reporting, evidence uploads, and tracking.
Interactive GIS map featuring monitoring stations, pollution hotspots, and geocoded reports.
City EcoScore calculation, carbon tracking benchmarks, and SDG environmental alignment.
Scenario modeling for clean-air zones, traffic regulations, and industrial emission shifts.
AI-summarized environmental briefings, compliance tracking, and structured PDF exports.
Governance dashboard for complaint verification, city parameters, and system oversight.
From sensor ingestion and meteorological feeds to actionable municipal insights and citizen resolution workflows.
Weather observations and atmospheric metrics are pulled via Open-Meteo feeds, combined with localized citizen-submitted environmental reports.
The platform computes pollutant sub-indices, EcoScores, and 7-day predictive trends, using Google Gemini for grounded contextual briefings.
Insights are surfaced on the Smart Map and Dashboards, while complaints are triaged by administrators and assigned to authorities for resolution.
The full-stack application architecture connecting the React frontend, Node.js API, MongoDB persistence layer, and external intelligence services.
┌─────────────────────────────────────────────────────────────────────────┐
│ React 19 + TypeScript Application │
│ TanStack Router · TanStack Query · Tailwind CSS · MapLibre GL │
└────────────────────────────────────┬────────────────────────────────────┘
│ HTTP / REST (JWT Auth & Cookies)
▼
┌─────────────────────────────────────────────────────────────────────────┐
│ Node.js / Express.js REST API Gateway │
│ Security (Helmet, CORS) · Rate Limiting · Role Authorization (RBAC) │
└──────────────┬───────────────────────────┬──────────────────────────┬───┘
│ │ │
▼ ▼ ▼
┌──────────────────────────────┐ ┌───────────────────┐ ┌──────────────────┐
│ MongoDB / Mongoose │ │ Open-Meteo API │ │ Google Gemini AI │
│ Users · Complaints · Cities │ │ Weather & AQI │ │ 2.5 Flash Model │
│ Alerts · Reports · Audits │ │ Forecast Feeds │ │ Prompt Grounding │
└──────────────────────────────┘ └───────────────────┘ └──────────────────┘How GreenGuard AI leverages Google Gemini as a grounded decision-support layer.
To ensure accuracy and prevent hallucinations, all AI queries query the underlying MongoDB database and meteorological services first. Current pollutant numbers, temperature, historical baselines, and complaint context are directly passed into the Gemini model prompts.
AI within GreenGuard AI functions as an assistive intelligence tool — summarizing complex time-series datasets, generating public health guidance, and explaining policy simulator impacts. Final municipal actions and governance approvals always remain with human operators.
The closed-loop resolution process ensuring every environmental issue is tracked, verified, and resolved with full accountability.
Citizens submit localized complaints with category, location coordinates, description, and optional photo evidence via Citizen Hub.
Administrators review new reports in the governance dashboard, verify validity, classify severity, and assign them to the appropriate municipal department.
Assigned authority personnel view the complaint in their dashboard, conduct field investigation, update case notes, and record resolution details.
Administrators review the submitted resolution evidence. Once approved, the case is marked resolved, and the citizen receives a status update.
The citizen reviews the resolution outcome and can either accept the resolution or request rework if the issue persists.
GreenGuard AI maintains explicit separation between observed physical readings, derived indices, forecasts, and AI analysis.
Direct meteorological measurements from Open-Meteo APIs (temperature, humidity, wind speed) and direct citizen report observations.
Standardized Air Quality Index (AQI), Water Quality Index (WQI), and city EcoScores calculated via deterministic backend scoring formulas.
7-day predictive weather and AQI models generated from meteorological services with confidence intervals.
Natural-language context, environmental summaries, and simulation policy explanations synthesized by Google Gemini models.
Technologies, libraries, and frameworks powering the current implementation.
Implemented REST endpoints available on the GreenGuard backend service.
Security controls implemented across the API, database, and client applications.
Granular access control enforcing strict permissions for Citizen, Authority, and Administrator roles across all routes and API controllers.
Stateless JSON Web Tokens with expiration handling, bcrypt salted password hashing, and optional 2FA verification challenge workflows.
Express rate limiters protect authentication endpoints, AI endpoints, and general API routes, combined with Helmet HTTP security headers.