While census data keeps governments updated on a population at any given time, it is no substitute for real-time information on a population’s mobility. For many nations, telecom data is some of the richest data available. Yet this data is often under utilised, if its value is recognised at all.
By looking at anonymised mobility patterns, telecom data can be used by city planners to optimise public transport and to approximate the best location for a new hospital or police station. It can also be used to promote awareness and prevent accidents, as authorities can gain a greater understanding of where they may occur, making the city safer for everyone in it. Ultimately, it can allow a city to deploy its resources efficiently.
How it works
With the advent of connected devices generating huge amounts of data, organisations are starting to realise the benefits of big data, and the need to analyse it to extract the full benefits of the connected world.
More specifically, the telecom industry holds a wealth of information. As mobile users, we create hundreds of data points each day. However, with many being unsure of the best way to utilise the data, it isn’t being used to its full potential.
Some telecom companies are starting to realise the benefits this data can bring to society. Rather than look at an individual’s data, by analysing and interpreting the data, telecom companies can look at patterns in the population’s anonymised and aggregated data as a whole. It is all about how city authorities and emergency services can work with the telecom companies to plan ahead.
City authorities can use data from telecom operators to plan future developments, and emergency services can use the trends extrapolated from the data to assess where a spike in criminal activity or health emergencies are likely to occur, allowing the more efficient deployment of emergency resources.
Practical uses
These large data sets can be used to spot changes in behaviour patterns, but it only proves valuable to society if it is interpreted and acted upon. If there is an event taking place at a stadium, local emergency services could use the data to ensure they have adequate provision around the stadium. They could even see in real-time which travel routes are being used most and move provisions based on this information. Or make getting home easier by redirecting some people to quieter routes.
Transportation is one area in cities where data can prove an invaluable resource. By knowing the origin and destination of population movements, infrastructure and public transport can be made more efficient. Not just when an event like a game at a stadium is taking place, but in everyday life.
Similarly, the data can be used to see patterns to help bring down drink driving deaths. By looking at the origins and destinations of groups of party-goers, the police can raise awareness in these areas about the dangers of drinking and driving. They can also position roadside testing in the right places in order to stop people before an accident occurs.
Telecom data can also be useful in times of natural disasters. Where are people heading? Do they know where the nearest evacuation points or health centres are? Up to date data on where populations are congregating and their mobility patterns can provide invaluable information on the locations where resources are needed. It means that emergency services can get the right information on what people need to do in the right places.
The important thing to remember is that this isn’t about monitoring the data of individuals; it’s about observing patterns and anomalies in the overall data and using it to plan and forecast. In short, it’s about using the data collected to improve lives.
Future developments
Telecom data is going to prove a vital piece of the big data puzzle. Cities are already starting to use connected devices and sensors fitted in cars and on roads to manage traffic flow, telecom data can add to this. Cities depend on their transport links to get people around in a safe, and timely manner. Telecom data can help planners discover where and why a problem exists, because it shows people across their complete journeys, no matter which transport mode they use. The original plans may say one thing, but human behaviour may have other ideas (such as the majority of people choosing to use exit A from a tube station, rather than use an exit that would take them two streets over).
For cities to get the full benefit from telecom data, they need to have the right tools to interpret it, and perhaps most importantly, they need to be willing to change or adapt plans to incorporate the insights discovered from the data. Data alone is useless; it’s how cities choose to implement it that matters when it comes to creating safe, and efficient, systems.
