The concept of smart cities has been around for a while. The basis of it is simple - through using technology and data you can create a better, more sustainable urban environment.
According to the World Health Organisation, 54% of the global population live in urban areas, with the biggest growth shown in developing countries. The rate of growth is profound given that in 1960 only 34% of the global population lived in urban areas. These increases are unlikely to abate any time soon as they are predicted to be 1.84% per year between 2015 and 2020, 1.63% per year between 2020 and 2025, and 1.44% per year between 2025 and 2030.
With this kind of growth in urban areas, the pressure on almost every aspect of urban infrastructure will be significantly increased; however, through the development of so-called ’smart cities', dealing with this pressure will be much easier. The success of this transformation will generally fall to innovative data initiatives - below we have outlined some of the key areas where it will have the biggest impact.
One of the big issues with having millions of people in smaller areas, is that disease can spread considerably quicker than in a more dispersed population. Although increased urban populations may have greater resilience to common illnesses built through more exposure to bacteria and germs, there is a far greater risk of spreading new strains of diseases coupled with faster infection rates.
It may be surprising to hear that during the Spanish Flu in 1918, 1 in 10 from urban populations died from the disease, whilst in some rural areas this ran to 9 in 10. This increased urban resistance was due to an earlier strain of the flu infecting more in the urban areas, making them more resistant to the later deadly strain. If doctors at the time had this kind of knowledge and the data to implement an effective prevention strategy, millions of lives could have been saved.
Now nearly 100 years later, scientists are trying to harness big data to implement predictive strategies, allowing them to track the spread of diseases and potential cures or protections against them. One of the organizations doing this is Mount Sinai Hospital in New York, who have been using data to help track and halt the spread of Influenza in cities. By tracking how the flu moves through populations and how the virus mutates, they have helped to prevent it in the future. According to Sumit Chanda, Ph.D., Co-Senior Author and Director (capitals in job title) of the Immunity and Pathogenesis Program at Sanford Burnham Prebys Medical Discovery Institute (SBP), 'Our research efforts are focused on finding unalterable host molecules—the ones within our bodies—that viruses hijack to spread and create full blown infections'. Through this, they are hoping to be able to prevent the annual spread of the flu throughout urban populations.
They are doing this through collecting data from thousands of patients, reported outbreaks (both current and historical) and also cross referencing this to mutations in the virus. Through this kind of work allows data scientists and doctors to predict how viruses will spread and the best ways to combat them. It will even be possible to use predictive analytics to estimate how they could spread in urban areas, then take action to limit this.
China has seen a huge increase in the number of cars it has on its roads, with the country having only 5.5 million cars in 1990 compared to 70 million in 2010. This represents an increase of over 1000% in only 20 years. As infrastructure to cope with this increase is slower than the rate of growth, it has meant that Chinese roads are now some of the most dangerous in the world, with 20.4 road deaths per 100,000 people, compared to 11.4 in the US and just 3.7 in the UK.
An unnamed city in Zhejiang, China worked with Intel to install 1,000 digital monitoring devices, 100 intelligent monitoring checkpoint systems, over 300 checkpoint electronic police, and more than 500 video monitoring systems, to deal with their 60% yearly increase in traffic. Through being able to monitor traffic and congestion more effectively, the city managed to improve traffic flow, increase prosecutions for trafficking offences and decrease road accidents.
As similar initiatives spread through the US and Canada, collecting and analyzing a huge amount of data across smart cities to deal with the huge traffic booms, we are likely to be seeing even more innovation big data initiatives used in population hubs across the globe.
Although it is not the most glamorous job, waste management is one of the most important elements to get right in any urban environment and data has a significant role to play in this.
The Waste Disposal Authority in Manchester, UK, have a system that utilizes data in order to recycle as much of the waste created as they can. This reduces the land needed for landfill and also reduces the chance of environmental damage from garbage. By weighing bridges as lorries come in and out of the processing plants from different areas, it is possible to find out how much waste is created in each location. This then allows them to create incentives for specific communities to recycle and reduce waste.
Through using these kinds of metrics, it is also possible to reduce the environmental impacts of urbanisation, as water, soil and air are tested for contaminates, allowing authorities to see changes over time and take steps to minimize future environmental problems before they have the chance to happen.
Without a doubt the biggest issue facing cities is going to be finding places for all these new people to live, especially in places where housing is already limited. Places like London have seen the property prices increase by around 250% due to the decreasing amount of space for housing and the increased demand for it. Due to this, one of the main areas of housing that is being hit hardest is social housing.
Here big data can have a profound effect, as the housing charity HACT has found, where it is currently collecting data from 400,000 houses to analyze for a variety of purposes. This could be anything from the improving repair of council owned properties through to how space is being utilized. The idea behind this is to use data to identify potential issues with design, construction or placement, which can then be rectified on those properties and avoided when constructing future buildings.
This kind of information is not just useful in social housing though, as elements like use of space and degradation of materials over time, can have a profound impact on how wider housing projects are approached, allowing developers and cities to create accommodation that maximizes available space, whilst still allowing for a pleasant living experience.