Project description
New tools to analyse data for smart city planning
Global population projections show that more than two thirds of the population – 6.5 billion people – will be living in urban areas by 2050. To prevent uncontrolled urbanisation, one of the United Nations Development Programme's goals is to promote the sustainable growth of urban areas. Smart urban planning and scalable methods require efficient instruments that can analyse large amounts of data over time. The EU-funded AI4SmartCities project will work to generate professional solutions for very high resolution geospatial and social–economic indicators for smart city planning and management. To that end, it will extend the already developed artificial intelligence algorithms and big Earth observation data management properties to very high resolution data for smart city solutions and prepare the software for commercialisation.
Objective
It is estimated that by 2050, 68% of the world population will live in urban areas, according to the United Nations. With the accelerated rhythm of population growth, the expected number of urban citizens in 2050 is close to 6.5 billion (compared to 4.2 billion nowadays). Uncontrolled urbanization raises a significant problem, the topic of the United Nations Development Programme Goal 11: ensuring sustainable and safe growth of urban areas. This project therefore addresses a global problem. To enable smart urban planning and scalable methods for example to predict the risk of structural degradation or damage to city buildings, it is essential to create efficient tools that can analyse large amounts of data, over time (4D), to create comprehensive global urban maps. The continuous expansion of data sets poses a significant problem for data analytics for global smart urban planning: we currently lack solutions that can generate useful insights from the data.
In this PoC project, I aim to extend the AI algorithms and the big Earth observation data management features developed in the ERC Starting grant to very high resolution data for Smart City applications and offer our software as a commercial, integrated service. Within the PoC, a comprehensive business case that will assist us in designing an exploitation strategy will be developed. Achieving these objectives will advance our AI solution for Smart City from a technology readiness level (TRL) of 4 to 6.
Our value proposition in AI4SmartCities is a set of professional solutions for very high resolution geo-spatial and social-economic indicators for Smart City planning and management by retrieving them from big EO data using AI. For example, high resolution building footprint map, urban building change map, and traffic flow map. Supporting the abovementioned solutions is an easy-to-use, interactive big EO data analysis platform.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences artificial intelligence
- natural sciences computer and information sciences data science
- engineering and technology civil engineering urban engineering smart cities
- natural sciences computer and information sciences software
You need to log in or register to use this function
We are sorry... an unexpected error occurred during execution.
You need to be authenticated. Your session might have expired.
Thank you for your feedback. You will soon receive an email to confirm the submission. If you have selected to be notified about the reporting status, you will also be contacted when the reporting status will change.
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
-
H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
See all projects funded under this programme
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
ERC-POC - Proof of Concept Grant
See all projects funded under this funding scheme
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2020-PoC
See all projects funded under this callHost institution
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
80333 Muenchen
Germany
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.