TrashTrack
About project
This project is a next-generation waste management and logistics optimization platform designed to help municipalities and enterprises improve operational efficiency, reduce costs, and support sustainability goals. The system integrates IoT devices, real-time GPS tracking, predictive analytics, and automated dispatching into a single platform. Beyond waste collection, it includes some of the fleet management capabilities.
Main goals of the project
- Optimize waste collection with real-time IoT tracking and smarter route planning.
- Ensure sustainability compliance by tracking CO₂ reduction and supporting circular economy initiatives.
- Provide scalable cloud-native architecture capable of handling thousands of concurrent vehicles and IoT sensors.
- Deliver an intuitive dashboard for both municipal authorities and business operators.
- Improve fleet efficiency by monitoring driver behavior, predictive maintenance, and automated dispatching.
Challenges and solutions
Challenge: Inconsistent data from sensors and GPS devices created unstable tracking feeds.
Solution: Developed a custom Poller framework on AWS EKS with concurrency control, retries/backoff, and deduplication to ensure reliable ingestion of IoT data.
Challenge: Managers lacked real-time control over vehicles and routes.
Solution: Built real-time dashboards with Google Maps integration, WebSocket updates, and complex filtering options for trip data, driver monitoring, and compliance reporting.
Challenge: Growing demand for CO₂ reduction reporting and regulatory compliance.
Solution: Integrated predictive analytics for fuel usage and emissions tracking, along with compliance-ready reporting dashboards.
Challenge: Sensitive municipal and business data required strict security boundaries.
Solution: Applied IAM least-privilege policies, KMS encryption, Cognito authentication, HTTPS everywhere, and secure SDLC practices.
Challenge: Infrastructure struggled with peak traffic when hundreds of vehicles were active.
Solution: Implemented autoscaling clusters on AWS (EKS/ECS), caching layers with Redis, and CI/CD pipelines with automated rollbacks.
Functionality
Features that make this project unique
Real-time integration of waste bins, vehicles, and sensors.
AI-powered route optimization and predictive maintenance for vehicles.
Data-driven insights to reduce waste, increase recycling, and track sustainability goals.
Built on AWS with autoscaling and event-driven pipelines.
End-to-end encryption, audit logging, and role-based access.
Tech stack
NextJS
Typescript
Axios
Media Recorder
TailwindCSS
Google Maps API
Zod
NestJS
.NET
Node JS
Socket.io
Passport JS
AWS
S3
ECS
SNS/SQS
Secrets Manager
CloudFront
PostgreSQL
Aurora
Lambda
KMS
MemoryDB
EKS
Route 53
Cognito
PostgreSQL
Redis
Websocket
Optional features that can be added to similar project types
Simulate urban infrastructure performance with real-time data.
Predict collection needs to reduce fuel costs.
Track and optimize electric vehicle charging and routes.
Allow residents to report waste issues or track collection schedules.
Automated sustainability reports for government regulators.
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