Knowing the wellbeing of an urban population is a complex problem, but data from smart cities could hold answers, writes Tzirath Perez Oteiza, Dr Liadh Kelly and Dr Peter Mooney, Department of Computer Science 

Encountering inconveniences such as traffic, a gloomy polluted skyline, or annoying bus schedules may be part of your daily routine. Experiences like these are known to affect your mental wellbeing, consciously or subconsciously.

Smart cities, such as Dublin and Barcelona, use information and communication technologies (ICT) to collect data related to these experiences such as weather, air pollution, traffic congestion times, etc. to help with city management. There is also the opportunity for researchers to harness the potential of this data using new artificial intelligence techniques to estimate urban citizens' wellbeing and ultimately inform and transform government policy into wellbeing supports.

To avoid stressful mornings, you may choose to avoid city traffic by taking public transportation. However, the effectiveness of public transportation remains the same: cancelled trains, late buses, and a lack of infrastructure. This may be as stressful as driving in the Dublin M50 traffic at 8am since research shows that every 10 more minutes of commuting time is associated with higher depressive symptoms. This same research also determines that not having bus stops within a 10-minute walk can also negatively affect your mental wellbeing. Another study found that 26% of women compared to 17% of men reported distress when commuting for more than one hour.

This situation extends beyond Dublin. According to the United Nations, in 2019 it was calculated that only half of the urban population across the globe has access to well-established public transportation. In the same report, the UN highlights the importance of policymaking based on urban citizens’ wellbeing. Similarly, the World Happiness Report states that poor public transportation infrastructure leads to congestion and worsens air pollution, which in turn can affect a citizen's happiness level.

Improving wellness in the city

Ultimately, there is a significant discrepancy between currently proposed government initiatives and solutions that benefit people's mental wellbeing. We know this because studies have been published giving evidence for the need for e.g., public transportation to be on time to support wellness; access to greenspaces to support wellness; the relationship between air quality levels and mental wellness; etc. These factors should form part of good city planning.

Dublin is one of the few European cities that does not have a metro system, which citizens consider a "basic necessity" for their everyday commute. Since the only transportation options available to people are overground transportation, initiatives such as IBM Smart Dublin have set out a plan to use data captured about the city to improve the bus transportation networks and reduce congestion. While organizations such as Smart Dublin have an initiative to bring a community of academics and industry researchers together to continue the development of techniques to further improve the community experience for people living in the city.

Using data captured about a city

Knowing the mental wellbeing of an urban population can be a difficult and complex problem. Ideally, a clinical trial would be carried out where every urban citizen is interviewed by a medical professional. Carrying out a clinical trial in a selected area would be resource intensive, socially and ethically complex, and would be difficult to repeat in other Irish cities. Thus, there are opportunities for automatically exploring data that a city and its inhabitants generate. It can offer us insight into the mental wellbeing of citizens. Here, the advantage is that it can be carried out in an unobtrusive way, repeated very quickly and over extended periods of time.

This approach would automatically collect data from sources such as bus times, congestion times, greenspaces, etc. Using each one of these factors, the algorithm will output a wellbeing estimation. These algorithms will include a combination of new methods such as machine learning and artificial intelligence to embrace the different information sources. These computation approaches will not give us the same results as a clinical trial, but it will give us indicators or a general picture of the mental wellbeing of citizens in the city- and these indicators could be enough to influence policy and even prompt public health responses.

Faster solutions …

Embracing this innovative approach could mean faster response times when implementing city wellbeing solutions. The process of clinical trials is long, it could be months to years until a solution is agreed upon and implemented. Perhaps by the time an initiative is set, the root problems have changed thus the original solution is not viable anymore. Artificial Intelligence approaches could offer immediate estimates of the current wellness levels offered by a city, make predictions for the future, and offer suggestions on how to improve wellness in the city.

As more smart cities emerge and those cities become more populated, it is essential for scientists and policymakers to prioritize the wellbeing of people, and this includes focusing on improving mobility in cities as well as having accessible amenities.

This publication has emanated from research conducted with the financial support of Science Foundation Ireland under Grant number 18/CRT/6049. The opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Science Foundation Ireland.

This article previously appeared on RTÉ Brainstorm.