The introduction of the internet started a trend of the human race generating massive amounts of data. In 2020, IBM estimated that humans collectively produce 2.5 quintillion bytes of digital data every single day, and industry experts estimate we’ll reach a point where the number of bytes of data will outnumber the atoms on the planet.
A lot of this information is junk. But with the right tools, professionals can turn that mass of data into something actionable for a variety of applications. We’re already seeing doctors and medical researchers using collected data alongside machine learning and artificial intelligence (AI) programs to diagnose diseases with an often surprising degree of accuracy.
Cities are also cashing in on this wealth of data by using it to keep their citizens safe. How are cities around the world using public safety data to protect the people that live within their borders?
There is so much data out there that for anyone outside the data management industry, it can feel incredibly intimidating. Social media is one of the biggest sources of information when users opt-in, but cities can also collect data from a variety of sectors.
Smart devices spread across the city can collect information from a number of different sources and demographics. Traffic cameras can monitor vehicle movement and even call emergency services in the event of an accident, even before someone has the time to pull out their phone. Medical data can help officials track diseases that may be spreading within the city limits — something that has become a valuable tool throughout the COVID-19 pandemic.
Even cities that aren’t set up yet to adopt the Internet of Things can benefit from collecting this sort of information and plugging it into a machine learning or AI system that can sort through all the data points and turn it into something useful.
Over the last decade, social media in its various platforms has become one of the biggest sources of user-aggregated data in history. As of 2021, there are roughly 4.48 billion social media users around the world, which equals around 57% of the global population. For law enforcement professionals focusing on public safety data, this can be a valuable resource.
According to a United Nations report, social media-based trafficking cases have increased during the pandemic. Collecting data from social media can make it easier to combat human trafficking in U.S. cities and around the globe.
In most cases, predicting the future might sound like something out of a fantasy movie. But predicting future events is quickly moving out of magic and into science.
A properly programmed AI or machine learning engine can predict future events by looking at existing data and what’s happened in the past and identifying patterns that could indicate the same thing might happen again. The more data a system has, the more accurate the predictions become.
Whether it’s addressing a car accident or a city-wide disaster, emergency services often find themselves stretched thin while trying to keep up with demands. Public safety data can support these emergency professionals and, in turn, help keep the population safer.
Blockchain, for example, can be used to track both gun sales and crime patterns in any given area. Like the prediction models, this isn’t just pulling answers out of thin air. Instead, it tracks the applicable data, finds patterns, and makes connections. The key here is being able to sort through massive amounts of data and make sense of it, something that would be downright impossible for the average human being.
City population demographics are changing as more people switch to remote work and move out of the urban areas, but there are still massive populations that need protection. The data that we’re generating every single day if properly applied, can be an invaluable tool toward achieving that goal. Smart cities are the wave of the future, and if they hope to keep their populations safe, cities that haven’t started to adopt this new technology have their work cut out for them.