#ResearchProjects | Call for Applications: PhD Students / MSc Research Students / Research Assistants for the project “Smart Low-Cost Air Quality Monitoring System for Urban Environments: A Case Study in Ha Noi”

Successful candidates will join the College of Engineering and Computer Science (CECS), VinUni as PhD students, MSc research students, or Research Assistants.  

Project Information  

This project proposes the development of a smart, low-cost air quality monitoring system to advance sustainable environmental management, with a focus on Ha Noi – a city facing severe challenges from air pollution. The system will design, develop, and deploy mobile sensor kits mounted on vehicles and drones, enabling real-time, high-resolution data collection across urban terrains.  

The research team aims to build an affordable, energy-efficient sensor network that integrates AI for performance optimization and anomaly detection, while addressing cybersecurity challenges such as data integrity, firmware protection, and intrusion detection. 

The project spans the full pipeline—from hardware and embedded software design to real-world field deployment—bridging research with practical implementation. It provides opportunities for those passionate about innovation, sustainable cities, public health, and secure IoT infrastructures.  

Led by Dr. Nguyen Dinh Duc Nha and VinUni faculty, the project aims to develop the first mobile air quality monitoring system in Vietnam. Team members will also contribute to technical reports, academic publications, and gain experience in both applied and scholarly research.  

Research Objectives  

The project targets the development of a smart, cost-effective air quality monitoring system optimized for urban environments such as Ha Noi. Key research goals include:  

1. Designing modular, low-cost sensor kits capable of measuring key air pollutants (e.g., PM2.5, NO₂, CO) in real time via mobile platforms and unmanned aerial vehicles (UAVs). 
2. Integrating renewable energy sources, particularly Triboelectric Nanogenerators (TENG), to power sensors autonomously. 
3. Developing efficient communication methods using LPWAN, ZigBee, NB-IoT, and store-and-forward models for low-connectivity areas. 
4. Building a hybrid monitoring network to complement existing fixed stations. 
5. Applying Artificial Intelligence (AI) for anomaly detection, data validation, health risk forecasting, sensor fault tolerance, and cybersecurity resilience. 
6. Creating an integrated data platform with visualization capabilities to support cross-disciplinary applications in public health, urban planning, transportation, and education. 

This system is expected to strengthen environmental governance capacity, promote interdisciplinary collaboration, and encourage community participation.  

Project Contact 

For details, please contact Dr. Nguyen Dinh Duc Nha via email [email protected]

Graduate Admissions Contact 

• VinUni Graduate Admissions
•  0978 549 846
• [email protected]

Learn more about Master’s, PhD programs, and scholarships at: VinUni Graduate Research Excellence Program

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