GOALS

 

SDG 11

 

Make cities and human settlements inclusive, safe, resilient, and sustainable.

 

Important indicators for this goal are the number of people living in urban slums, the proportion of the urban population who has convenient access to public transport, and the extent of built-up area per person.

By analyzing data on traffic patterns and urban density, AI can contribute to lessening traffic congestion and enhancing urban planning. In this chart we see the mortality rate attributed to household and ambient air pollution, age-standardized (per 100,000 population).

This perspective offers a real-time view of the worldwide news on community-related topics, providing us with a media perspective on the progress at the different fronts of SDG 11.

A SDG Live Report is what it is all about! Here, you can have a real-time perspective of the state of the world in regard to AI and sustainability, tracking some of the main issues to address in the near future.

AI has been instrumental in advancing Sustainable Development Goal 11 (SDG 11), which aims to make cities and human settlements inclusive, safe, resilient, and sustainable. Between 2015 and 2023, there have been 253,595 scientific publications examining the role of AI in urban development and management. These studies highlight AI’s potential to improve urban planning, enhance public transportation systems, and optimize resource management. AI technologies can analyze vast amounts of data to predict and mitigate the effects of urban challenges such as traffic congestion, pollution, and energy consumption. Despite the relatively lower media exposure, with 6,364 news articles, public awareness of AI’s role in transforming urban environments is growing. The development of 561 AI policies targeting SDG 11 reflects a significant commitment from policymakers to integrate AI into urban development strategies, ensuring sustainable and resilient cities.

Looking ahead, the next 5 to 10 years are expected to witness significant advancements in AI applications for urban sustainability. AI-driven smart city initiatives will become more prevalent, enabling real-time monitoring and management of urban infrastructure. These smart cities will leverage AI to enhance public services, improve emergency response times, and reduce environmental impact. AI will also play a critical role in advancing sustainable mobility solutions, such as autonomous vehicles and intelligent public transport systems, reducing congestion and emissions. As AI technologies evolve, they will facilitate more effective disaster risk management and climate resilience strategies, ensuring that cities can adapt to changing environmental conditions. Collaboration between governments, urban planners, and technology companies will be essential to ensure that AI-driven innovations contribute to inclusive, safe, and sustainable urban development, aligning with the goals of SDG 11.

Here is your window to the state of the world in regards to sustainable communities through AI. This dashboard is configurable and can be integrated into other systems to bring actionable technology into the systems of research institutions, governments and enterprises that are willing to make a difference.

 

Avoiding data bias in AI systems is crucial to ensure fair, accurate, and equitable outcomes, preventing the reinforcement of existing inequalities and enabling more trustworthy and inclusive technologies. Here you will see a dashboard analysing the bias related to the data ingested in this observatory for SDG 11.

INDICATORS

Key indicators that report on the status of water sustainability will further understanding of this important topic. With this tool, you can utilize drop-down menus and animations to explore the various aspects of and progress towards SDG 1.

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This view offers the individual perspective at each of the indicators in order to disentangle the parameters in the global/local indicator view and have a better perspective of the evolution of the indicator through time across regions and countries.

Here you can observe the timeline of indicators that have a local dimension, comparing regions instead of countries to provide insight with more granularity reflecting local priorities being addressed.

This view offers the individual perspective at each of the indicators in order to disentangle the parameters in the global/local indicator view and have a better perspective of the evolution of the indicator through time across regions and countries.

MEDIA

The media room exhibits insight from world and local news, aiming to identify SDG-related events from millions of worldwide multilingual news, and to exhibit best practices towards solving SDG-related problems. This is offered in collaboration with EventRegistry.

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In this view you can explore the different topics and subtopics related to the signal of worldwide news related to the selected SDG.

This visualisation will expose the intensity of news published in the main topics of the selected SDG and the impact that AI has on it, exposing the newsworthiness of that impact worldwide and on a timeline.

Review the worldwide news, social media posts and forum discussions published on SDG-related topics, using interactive data visualisation that can help better refine the search parameters.

SCIENCE

This perspective is providing the IRCAI user with the access to text-mining tools to improve effectiveness in reviewing a topic over a large dataset of published science and patented technology.

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Here we can observe the research trends related to the selected SDG based on more than 128 million articles published worldwide since the 40’s. Add/remove aspects of the SDG that should be compared.

Here we observe the relation between the concepts (edges) relevant to the selected SDG and the relations between those concepts, stronger or weaker according to the amount of articles where these are topics in common.

Review the published research and submitted patents about SDG-related topics, building global knowledge, using interactive data visualisation that can help better refine the search parameters.

POLICY

The observation of policies applied worldwide on SDGs is fundamental to better understand the progress of the global action. Explore the topics related to the legal and regulatory landscape from open data using sophisticated data analytics and machine learning methods.

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Here we can observe the trends identified in the ingested policy and legislation related to the selected SDG based. Add/remove aspects of the SDG that should be compared.

Observe in time the relations between concepts automatically identified in the legislation and their relation according to frequency that they are being part of the same policy documents.

Review the published legislation and policies about SDG-related topics, making sense of the published policies using interactive data visualisation that can help better refine the search parameters.

EDUCATION

Education is key for progress and sustainability. Explore in this room the educational resources in several SDG-related knowledge domains that can help educational institutions, local governments and companies can leverage the Observatory to best fit the professionals of the future.

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Explore the available open education resources focusing SDG-related topics through interactive data visualisation and machine learning methods to get closer to what you are looking for.

In this view you can explore the different topics and subtopics related to the available educational resources related to the selected SDG.

Review published educational resources focusing SDG-related topics, making sense of the related topics using interactive data visualisation that can help better the professional training and public education on sustainability.

INNOVATION

The heart beat of entrepreneurship can be the driver for sustainability. Explore in this room the innovation initiatives, from start-ups to living labs, focusing in several SDG-related topics building an ecosystem of initiatives that will enrich the sustainability-focused industrial landscape.

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Explore the topics engaged in the different actors of the existing innovation ecosystem focusing AI and sustainability, and fed by IRCAI’s Top 100 using sophisticated data analytics and machine learning methods.

In this view you can explore the different topics and subtopics related to the existing initiatives focusing specific objectives related to the progress of the selected SDG.

Review the content of the initiatives in the ecosystem progressing SDG-related topics, making sense of the related topics using interactive data visualisation that can help better to build fruitful cooperation with SDG focus.