About the Project
Surgere’s Container Optimization System is a smart logistics solution designed to enhance container tracking, reduce inefficiencies, and optimize supply chain management. The system leverages advanced data analytics, IoT tracking, and automation to improve asset utilization, minimize losses, and streamline operations.
Tech Stack & Tools
- Frontend: ASP.net MVC, Blazor
- Backend: ASP.net, .net Web API
- Database: Microsoft SQL Server
- IoT & Sensor Integration: RFID, GPS, and BLE-enabled tracking
- Cloud & Hosting: Azure Server
- Security Measures: Role-based access control, data encryption, API security
- DevOps & Deployment: CI/CD pipelines
- Analytics & Reporting: Power BI
Development Process
1. Planning & Requirement Analysis:
Defined key logistics challenges and optimization goals.
Researched real-time tracking, data collection, and predictive analytics needs.
2. Frontend & UI Development:
Designed an intuitive dashboard for real-time container tracking.
Implemented responsive UI for desktop and mobile accessibility.
3. Backend & API Development:
Developed secure APIs to integrate IoT data from RFID, GPS, and BLE sensors.
Implemented business logic for container utilization analytics.
4. Database & Cloud Integration:
Designed a scalable database structure for tracking millions of data points.
Used cloud computing for high availability and real-time processing.
5. IoT & Data Processing:
Integrated IoT sensors for real-time tracking of containers.
Implemented machine learning models for predictive analytics and loss prevention.
6. Security & Compliance:
Implemented encrypted data storage and secure API authentication.
Ensured compliance with logistics and data security regulations.
7. Testing & Deployment:
Conducted rigorous testing, including load testing for high traffic scenarios.
Deployed using automated CI/CD pipelines for seamless updates.
Challenges & Solutions
- Ensuring Real-Time Data Accuracy:
Solution: Used edge computing for immediate data processing and cloud synchronization.
- Handling Large-Scale IoT Data Streams:
Solution: Implemented message queuing and distributed processing for scalability.
Key Takeaways & Future Scope
- Successfully developed a robust, scalable, and intelligent container tracking system.
- Future improvements may include AI-driven predictive maintenance, blockchain integration for enhanced security, and automated anomaly detection for supply chain efficiency.
Technologies
