Month 1 — Requirement Study & Environment Setup
Objectives
Understand Digital Twin architecture and workflows
Learn telecom digital twin concepts
Define application scope and technical architecture
Activities
Study Digital Twin APIs and scenario configuration
Review existing mobility, traffic, and UE simulation features
Setup development and test environment
Deliverables
Development environment ready
Requirement specification document
High-level application architecture diagram
Initial proof-of-connectivity to Digital Twin APIs
Month 2 — Core Framework Development
Objectives
Build core backend framework and data pipeline
Activities
Develop backend services/API modules
Implement Digital Twin scenario management functions
Build data ingestion and telemetry collection modules
Create database/storage structure for scenario metadata
Deliverables
Working backend framework
Digital Twin control interface prototype
Scenario configuration parser
Initial telemetry collection pipeline
Month 3 — AI & Automation Feature Development
Objectives
Introduce AI-assisted intelligence and automation
Activities
Develop AI-based scenario recommendation engine
Implement anomaly detection or KPI prediction models
Build automation workflows for scenario generation
Enable AI inference traffic orchestration
Deliverables
AI-assisted scenario generation prototype
Basic ML model integration
Automated test workflow execution
Technical demonstration to mentor team
Month 4 — Frontend Dashboard & Visualization
Objectives
Build user-facing dashboard and visualization capabilities
Activities
Develop web UI/dashboard
Visualize UE movement, traffic patterns, and KPIs
Add monitoring and analytics capabilities
Implement real-time scenario status tracking
Deliverables
Interactive dashboard prototype
Real-time KPI visualization
Digital Twin scenario monitoring page
User workflow demonstration
Month 5 — Advanced Integration & Optimization
Objectives
Integrate multi-domain workflows and optimize performance
Activities
Optimize backend performance and scalability
Validate large-scale crowd/mobility simulations
Conduct stress and performance testing
Deliverables
End-to-end integrated prototype
Performance benchmark report
Multi-domain orchestration workflow
Stability and scalability improvements
Month 6 — Final Validation & Demonstration
Objectives
Finalize application and demonstrate business/technical value
Activities
Conduct final validation testing
Prepare demonstration scenarios
Document architecture and implementation details
Present outcomes to CTO leadership/research partners
Deliverables
Final Digital Twin application prototype
Complete technical documentation
Final presentation/demo including
Architecture overview
AI workflow
Key innovations
Performance results
Future roadmap suggestions
Pre-Requisites / Skills / Experience Requirements
Preferred Skills & Qualifications
Required
Currently pursuing Bachelor’s, Master’s, or PhD in
Computer Science
Electrical Engineering
Telecommunications
AI / Machine Learning
Data Science
Programming experience in Python
Familiarity with REST APIs and Linux environments
Preferred
Knowledge of
Machine Learning / Deep Learning frameworks
LLMs or AI agents
Data analytics and visualization
