ΑΙhub.org
 

Smart cities and AI


by
03 December 2021



share this:

cityscape with solar panels
More than 68% of the world’s population live in highly densely built cities. Those cities are not only causing high emissions and urban heat island impacts on the environment, they are also the most vulnerable areas for the impacts of climate change. Thus, immediate climate adaptation of cities is necessary.

AI-based methods not only allow us to automatize observations and make future predictions about the climate change related indicators of cities, they also help us to understand those indicators better by using explainable AI techniques. In this lecture, you will see a brief introduction to our studies in this field.

https://youtu.be/-iRTUMl9T_c



tags: ,


Beril Sirmacek is an associate professor at Saxion University of Applied Sciences
Beril Sirmacek is an associate professor at Saxion University of Applied Sciences

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

coffee corner

AIhub coffee corner: World models

  22 May 2026
The AIhub coffee corner captures the musings of AI experts over a short conversation.

Why the world’s banks are so worried about Anthropic’s latest AI model

  21 May 2026
The finance world’s concern rests on the impressive cyber capabilities of a product called Mythos.

Embracing empiricism – from the lottery hypothesis to creating real-world impact: an interview with Jonathan Frankle

  20 May 2026
Jonathan Frankle discusses empiricism, making an impact, and the legacy of his lottery ticket hypothesis.

A faster way to estimate AI power consumption

  19 May 2026
The “EnergAIzer” method generates reliable results in seconds, enabling data center operators to efficiently allocate resources and reduce wasted energy.

Introducing ARFBench: A time series question-answering benchmark based on real incidents

  18 May 2026
To resolve system failures, engineers must troubleshoot outages quickly.

Does ‘federated unlearning’ in AI improve data privacy, or create a new cybersecurity risk?

  15 May 2026
As the capacity of AI systems increases apace, so do concerns about the privacy of user data.

Reflections from #AIES2025

and   14 May 2026
We reflect on AIES 2025, outlining a discussion session on LLMs for clinical usage and human rights.

Deep learning-powered biochip to detect genetic markers

System can detect extremely small amounts of microRNAs, genetic markers linked to diseases such as heart disease.



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence