Lines of Activity

We work in various social, humanitarian and environmental areas

We assist with projects in different areas and organizations, always using technology, data and artificial intelligence.

Lines of Activity

We work in various social, humanitarian and environmental areas

We assist with projects in different areas and organizations, always using technology, data and artificial intelligence.

Lines of activity

Preparation and response to natural disasters

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Migrations

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Environment, climate change and agriculture

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Public health

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Digital education

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Preparation and response to natural disasters

Data provides valuable information to improve preparation and responses to natural disasters. In particular, the data extracted from the mobile telephone network helps to locate vulnerable population centres and identify pre- and post-disaster mobility patterns. This is likely the line of action that most directly contributes to saving human lives and it is through technology that we cooperate with different organizations that have worked in areas affected by different disasters and have helped the victims.

Magic Box Project

Our collaboration with UNICEF on the Magic Box project analyses and integrates data from different sources to provide insights that help respond to natural disasters. Specifically, we analysed the impact of various disasters in Colombia such as the flooding that occurred in Mocoa (April 2017).

+ Project info

SafePost

SafePost is a service that allows you to communicate via social media or send emails without needing an Internet connection. Publications are made and information is sent with the use of encrypted SMS as a communication channel. Moreover, SafePost technology can be used to equip third-party applications with data communication capabilities via encrypted SMS.

+ Project info

Migration

Each year, millions of people are forced to leave their homes for various reasons such as war, persecution or the need to find better economic conditions. The migration phenomenon is an enormous humanitarian challenge for those who leave their place of residence as well as those in the receiving communities. As experts in data applied to the mobility of large groups of people, it would seem logical to apply our knowledge to one of the main causes for concern as a global humanitarian problem: internal and international migratory movements.

Mobility Patterns in Communities Vulnerable to Extreme Climate Conditions

Along with the United Nations Food and Agriculture Organization (FAO) and GSMA, we are conducting an internal migratory flow analysis in Colombia, focusing on the departments of La Guajira, Tolima and Huila. With the use of mobile data, open data and LUCA’s analytical capabilities, we can detect and quantify mobility patterns potentially linked to internal migration, the places of origin of which are more vulnerable to extreme climate conditions such as drought. Thus, the organizations involved are able to understand the reality of this migratory phenomenon associated with climate and low resilience, which has been difficult to detect up until now, and make well-founded decisions to improve these people’s lives.

+ Project info + Watch video

Environment, Climate Change and Agriculture

The development of society and the mass exodus from rural to urban areas has led to greater energy consumption and the generation of larger quantities of waste, among other problems. This has resulted in a change in the way we interact with the environment. Climate change is now a reality. And, as experts in data and AI, we have wanted to get involved by applying our knowledge to this issue.

Air Quality in Urban Areas

Large cities are facing a serious public health problem related to the high levels of air pollution their citizens are exposed to. Much of the contaminating gas emissions come from the transport sector. Taking advantage of our mobility analysis platform, Smart Steps, we’re able to connect mobility and pollution in cities like Madrid and Sao Paulo to provide insights that help predict NO2 levels. Our collaboration with GSMA combines time data, mobile data and NO2 level measurements in order to determine the quality of the air in detail in Sao Paulo.

+ Project info for Madrid Project document + Project info for Nuremberg + Project info for Sao Paulo

Public Health and Safety

Preventive decision making is essential when it comes to public health and safety matters. Therefore, the use of machine learning and predictive models can be of great help with these issues.

Epidemic Outbreaks in South America

We cooperate with the Pan American Health Organization (PAHO, a division of the WHO) as well as UN Global Pulse and UNICEF to generate predictive models relating to the spread of disease based on mobility data. These models complement epidemiological models that attempt to predict the spread of diseases such as Dengue fever and Zika in Colombia and measles in Brazil.

+ Project info + Project info

Public Safety

In conjunction with the University of Columbia, we use anonymized and aggregate mobile data as well as police databases to predict delinquency hotspots in downtown New York.

We also collaborate with the Ciudata Segura project developed by the Inter-American Development Bank which aims to generate insights associated with criminality in 6 major Colombian cities.

+ Project info for Public Safety in New York + Project info for Ciudata Segura

Digital Education SDGs

ProFuturo arose with a vocation to transform the education of 10 million children in 2020. Driven by the Telefónica Foundation and La Caixa, the program mission is to reduce the educational gap in the world by bringing quality digital education to girls and boys in underprivileged areas of Asia, Sub-Saharan Africa and Latin America. This education programme includes professional development for educators with training, digital resources and new teaching/learning methods. This is probably the line of activity that is most heavily found in our DNA. We cannot even conceive of technology not contributing something to education or an education system working without technology.

Big Data and AI for Digital Quality Education

Digital Education: ProFuturo

We collaborate with ProFuturo applying Learning Analytics techniques to the search for an "algorithm for quality education". With AI, this algorithm will help measure the results of the programme, make data-based decisions and customize education. This contributes to ProFuturo’s ultimate aim which is to enhance the quality of education and learning among children in underprivileged areas.

+ Project info

Would you like to collaborate with us?

Contact our team and we’ll work together to turn your social project into a reality

Partnerships for the goals

We’ve established agreements with some of the most relevant organizations and NGOs in the world.

Data Transparency Lab

We have a strong commitment to transparency and the ethical responsible use of data.

Partnerships for the goals

We’ve established agreements with some of the most relevant organizations and NGOs in the world.

Data Transparency Lab

We have a strong commitment to transparency and the ethical responsible use of data.