Created by Ajit Jaokar at citysciences, the aim of the lab is to explore cross domain, complex, AI related problems for future cities
Artificial Intelligence (AI) and Deep Learning technologies are impacting many aspects of our lives. In future, this impact is expected to accelerate to many more areas including Smart cities.
The problem we address
Many of the future problems facing city planners such as driverless cars, use of drones etc impact multiple facets in cities. To address them through AI technologies, we need to think beyond the current silo-based approach. We need to look to the interconnections between city areas.
In practice, that means:
- City planners need to think long term
- Technology implementations need to take a long term, pragmatic view focused on new services. This needs thinking beyond the current concerns of deployments of AI technologies
- New services may impact multiple verticals
- These ideas will also need a more fundamental policy change / thinking
Most importantly, we wish to engage with new ideas in an ‘agile’ way. Ideas and solutions may emerge from professionals in the wider AI community who are not traditionally familiar with future cities.
The lab aims to create synergies between the city sciences and data sciences communities working on improving cities through artificial intelligence. Our goal is to mix traditional knowledge of city performance with the latest Artificial Intelligence (AI) and
Deep learning algorithms to deal with the urban complexity through consolidation of knowledge.
UPM is creating this as an open initiative for anybody interested to participate. It is based on two professional or researcher communities working together:
- City specialist who will propose challenges
- Data Scientist (based on AI) who will solve this issues
The Lab will work with data sources from multiple cities (including many Spanish cities we work with already). We will aspire to create open, replicable research which can be shared with other cities worldwide.
We aim to take an Open, agile approach with a model more closely aligned to Kaggle
than to academic publishing.
Sep/Nov 2016 in Madrid and London.
Various AI and Deep learning technologies.
Cross disciplinary worldwide participation – labs located in Madrid (UPM).
Ajit Jaokar is a professor at Citysciences teaching IoT, Big Data and Predictive analytics for future cities.
Javier Dorao is Manager at Citysciences and urban researcher at UPM.
We are seeking collaborators and ideas (both city problems and data scientists)
We welcome comments and feedback
Please contact ajit.jaokar
at futuretext.com and javier.dorao
at citysciences to know more