Really liked the GNSS traffic modeling angle Fady, it made me think about how much untapped value there is in mobility data. Curious how close you think this kind of modeling is to being usable by actual city planners.
My Research Journey in Green Software and Urban Mobility — Fady Desoky Saeed Abdelaziz
Fady-Desoky-Saeed-Abdelaziz
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— Originally published at dev.to
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Fady-Desoky-Saeed-Abdelaziz
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@[Marco Marelli]
Thank you, I really appreciate that
I think GNSS-based traffic modeling is already quite usable in practice, especially for traffic monitoring, congestion analysis, and hotspot detection. Many cities are using similar data sources today, but often in a fragmented or reactive way.
What’s still evolving is turning these models into reliable decision-support tools for planners. I believe we’re very close technically — the bigger challenge now is data integration, policy, and adoption, not the modeling itself.
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Cairo, Egypt • linkedin.com/in/fadydesokysaeedabdelaziz
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I am a data analyst with a software engineering background, working across data engineering, system ... Show moreI am a data analyst with a software engineering background, working across data engineering, system optimization, and sustainability analytics.
My work focuses on understanding how systems behave in real-world environments, particularly in terms of performance, scalability, and resource consumption. I am interested in using data-driven approaches and machine learning techniques to analyze system behavior, identify inefficiencies, and support the development of more efficient and sustainable systems.
I have worked on projects related to software energy consumption, urban mobility analytics, and NLP-based systems. These experiences allowed me to explore how data can be used not only to describe systems, but to improve how they operate and scale.
In addition to research-oriented work, I have practical experience with enterprise data systems, including data quality improvement, reporting, and process optimization. This has shaped my approach to problem-solving, combining analytical thinking with an understanding of real-world constraints.
I am particularly interested in building systems that are efficient by design — systems that balance performance, scalability, and resource usage while delivering real-world impact. Show less
My work focuses on understanding how systems behave in real-world environments, particularly in terms of performance, scalability, and resource consumption. I am interested in using data-driven approaches and machine learning techniques to analyze system behavior, identify inefficiencies, and support the development of more efficient and sustainable systems.
I have worked on projects related to software energy consumption, urban mobility analytics, and NLP-based systems. These experiences allowed me to explore how data can be used not only to describe systems, but to improve how they operate and scale.
In addition to research-oriented work, I have practical experience with enterprise data systems, including data quality improvement, reporting, and process optimization. This has shaped my approach to problem-solving, combining analytical thinking with an understanding of real-world constraints.
I am particularly interested in building systems that are efficient by design — systems that balance performance, scalability, and resource usage while delivering real-world impact. Show less
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