ΑΙhub.org
 

Towards greener and sustainable cities – an event from the Alan Turing Institute


by
19 August 2022



share this:
Bike lane

Earlier this summer, the Alan Turing Institute hosted a hybrid event on developing greener and more environmentally friendly cities using urban data analytics. All of the talks are now available to watch on YouTube.

The research presented by the speakers showcased a variety of methodologies. Below, we highlight the two talks where machine learning methods were used.

Using deep learning to identify (urban) form and function in open data satellite imagery
Martin Fleischmann, University of Liverpool


Understanding building energy efficiency with administrative and emerging urban big data by deep learning in Glasgow
Maoran Sun, Massachusetts Institute of Technology




AIhub is dedicated to free high-quality information about AI.
AIhub is dedicated to free high-quality information about AI.




            AIhub is supported by:



Related posts :



New AI technique sounding out audio deepfakes

  21 Nov 2025
Researchers discover a smarter way to detect audio deepfakes that is more accurate and adaptable to keep pace with evolving threats.

Learning robust controllers that work across many partially observable environments

  20 Nov 2025
Exploring designing controllers that perform reliably even when the environment may not be precisely known.

ACM SIGAI Autonomous Agents Award 2026 open for nominations

  19 Nov 2025
Nominations are solicited for the 2026 ACM SIGAI Autonomous Agents Research Award.

Interview with Mario Mirabile: trust in multi-agent systems

  18 Nov 2025
We meet ECAI Doctoral Consortium participant, Mario, to find out more about his research.

Review of “Exploring metaphors of AI: visualisations, narratives and perception”

and   17 Nov 2025
A curated research session at the Hype Studies Conference, “(Don’t) Believe the Hype?!” 10-12 September 2025, Barcelona.

Designing value-aligned autonomous vehicles: from moral dilemmas to conflict-sensitive design

  13 Nov 2025
Autonomous systems increasingly face value-laden choices. This blog post introduces the idea of designing “conflict-sensitive” autonomous traffic agents that explicitly recognise, reason about, and act upon competing ethical, legal, and social values.

Learning from failure to tackle extremely hard problems

  12 Nov 2025
This blog post is based on the work "BaNEL: Exploration posteriors for generative modeling using only negative rewards".



 

AIhub is supported by:






 












©2025.05 - Association for the Understanding of Artificial Intelligence