Dr Ahmed Moursi is a SyMeCo postdoctoral fellow with Lero@UoG undertaking his fellowship under the supervision of Dr Takfarinas Saber. Ahmed holds a PhD under joint supervision from Manchester Metropolitan University, UK, and Menoufia University, Egypt. He has an academic background in research and teaching. His research interests focus on air pollution monitoring systems, particularly leveraging UAVs for environmental data collection and analysis. Additionally, Ahmed has conducted research on protecting deep neural networks’ intellectual property using digital watermarking and enhancing search engines with social information. Previously, Ahmed worked as a lecturer at Menoufia University, Egypt, where he was involved in both undergraduate education and research. His goal is to contribute to cutting-edge advancements in his field and establish himself as a renowned researcher and educator.

Air pollution and climate change are major environmental challenges requiring innovative solutions. Ahmed’s SyMeCo research project, titled “UAV-Enhanced Air Pollutants Concentration Monitoring and Prediction”, aims to develop a flexible Air Quality Monitoring System (AQMS) using UAV-mounted sensors to collect and predict air pollutant concentrations efficiently. Designed for rapid deployment at events like city fairs, outdoor sports, and industrial sites, the system optimizes data collection by predicting air quality with minimal sensing locations. Building on research in UAV-based sensing, pollutant prediction, and optimized sensor placement, this solution enhances monitoring efficiency, reduces costs, and supports authorities in protecting public health, particularly during short-term pollution spikes.

Project impact – The project is expected to have a significant impact in various areas, including environmental protection, health benefits, efficiency and cost-effectiveness, versatility, scientific advancement, economic impact, policy influence, and public awareness. It aims to improve air quality monitoring and prediction, protect people with respiratory conditions, reduce costs through optimized sensing tasks, and quickly deploy in various events. The research will advance air pollution sensing and monitoring, reduce costs of mitigating air pollution, influence policymakers, and raise public awareness.

Project website: https://uav-apm.github.io/