Thesis Proposal Computer Engineer in Mexico Mexico City – Free Word Template Download with AI

Submitted to: Department of Computer Engineering, Faculty of Engineering, Mexico City

This Thesis Proposal addresses critical urban mobility challenges in Mexico City through the lens of a Computer Engineer's expertise. It positions Mexico City as the ideal laboratory for developing scalable smart city solutions while meeting national technological advancement goals.

Mexico City, home to over 21 million residents and 50% of Mexico's economic output, faces severe urban mobility crises. With traffic congestion costing the city $8 billion annually and air pollution ranking among the world's worst, traditional transportation models are failing. As a prospective Computer Engineer in Mexico City, I recognize that sustainable solutions require intelligent systems integrating real-time data analytics, IoT infrastructure, and AI-driven decision support—exactly where specialized computer engineering expertise is indispensable for Mexico City's development trajectory.

Current transportation management in Mexico City relies on fragmented legacy systems that cannot process the city's complex mobility patterns. Public transit data remains siloed across 15+ municipal agencies, while private ride-sharing services operate without integration protocols. This disintegration leads to suboptimal route planning, inefficient emergency response times (averaging 47 minutes during peak hours), and missed opportunities for reducing CO₂ emissions by up to 25% through coordinated mobility systems. As a Computer Engineer trained in Mexico City's academic ecosystem, I propose addressing this gap through an integrated platform that unifies data sources using edge computing and federated learning—solutions uniquely applicable to Mexico City's scale and socioeconomic context.

Existing studies on smart mobility (e.g., Barcelona's Superblocks, Singapore's Intelligent Transport System) fail to account for Mexico City's unique challenges: extreme population density, informal transportation networks (like "peseros"), and variable digital infrastructure across neighborhoods. While academic research from UNAM's Center for Research in Mathematics has explored AI-driven traffic prediction, no project has successfully integrated these models with Mexico City's heterogeneous public transport data ecosystems. Crucially, the 2023 Mexican Ministry of Communications report highlights that 78% of smart city initiatives fail due to poor cross-agency data interoperability—proving this is not merely a technical problem but a systemic one requiring Computer Engineer leadership in governance design.

• Primary Objective: Design and validate an open-source Mobility Intelligence Platform (MIP) for Mexico City that integrates real-time data from public transit, traffic cameras, ride-sharing apps, and environmental sensors using blockchain-based data sharing protocols.
• Secondary Objectives:
  • Develop a federated learning framework to train traffic prediction models without violating citizen privacy regulations (LFPDPPP).
  • Create an API-first architecture enabling seamless integration with Mexico City's existing "Cuidad Móvil" app and future smart infrastructure projects.
  • Quantify environmental impact through CO₂ emission modeling tied to optimized transit routes.

This Thesis Proposal adopts a mixed-methods approach grounded in Mexico City's technological landscape:

1. Phase 1: Data Ecosystem Mapping (Months 1-3) - Collaborate with Mexico City's Secretaría de Movilidad to document data sources, formats, and legal constraints across 8 key agencies. This establishes the foundational understanding of Mexico City's operational reality.
2. Phase 2: System Design (Months 4-6) - Architect MIP using microservices (Docker/Kubernetes) with edge processing nodes deployed at strategic traffic hubs in Coyoacán and Iztapalapa—two representative districts with contrasting mobility patterns.
3. Phase 3: Algorithm Development (Months 7-9) - Implement a hybrid LSTM-Transformer model for traffic forecasting trained on anonymized GPS data from Mexico City's public bus fleet (5,000+ units), adhering strictly to Mexican data sovereignty laws.
4. Phase 4: Validation & Impact Assessment (Months 10-12) - Run city-scale simulations using SUMO traffic software and partner with the Mexico City government for a 3-month pilot on Calzada de Tlalpan, measuring reductions in average commute time and emissions.

This Thesis Proposal will deliver:

• A deployable MIP framework that reduces Mexico City's traffic congestion by 18-25% in pilot zones (validated against city data standards).
• First open-source dataset of integrated mobility metrics for Mexico City, available through UNAM's Digital Repository.
• A governance model for cross-agency data sharing that meets Mexico's stringent privacy requirements—directly addressing a gap identified in the 2023 National Technology Strategy.
• Publication of at least two peer-reviewed papers in IEEE journals focused on urban computing, with explicit case studies from Mexico City context.

As a Computer Engineer preparing to contribute to Mexico's technological future, this project embodies the UNAM Department of Computer Engineering's mission: creating solutions that solve local problems while advancing global best practices. The outcomes will position Mexico City as a benchmark for smart mobility in Latin America—proving that urban innovation rooted in local realities drives scalable impact.

Beyond academic contribution, this Thesis Proposal directly supports Mexico's "National Strategy for the Fourth Industrial Revolution" (2021) and UN Sustainable Development Goals 11 (Sustainable Cities). By leveraging Mexico City's status as a global megacity, the MIP framework offers replicable architecture for other Latin American cities facing similar challenges. Crucially, it empowers local Computer Engineers to lead—not merely implement—urban transformation. The platform will be designed with scalability in mind: once validated in Mexico City's complex environment, it can adapt to cities like Guadalajara or Monterrey within 6 months of deployment.

This Thesis Proposal establishes a clear roadmap for a Computer Engineer to address one of Mexico City's most pressing urban challenges through technically rigorous, ethically grounded innovation. By centering the solution in Mexico City's unique socio-technical ecosystem—rather than importing foreign models—the project ensures relevance and sustainability. The Mobility Intelligence Platform will serve as both an academic milestone for the UNAM Computer Engineering program and a tangible tool to improve daily life for millions of residents in Mexico City. As future leaders of Mexico's tech sector, we must build solutions where they are most needed, starting in our own city.

Keywords: Thesis Proposal | Computer Engineer | Mexico City | Smart Mobility | Urban Computing | Data Interoperability

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