One of the busiest train stations in the world is New York’s Grand Central terminus. In peak hours around 1,000 people arrive at Grand Central every single minute and head out into the great metropolis. Impressive numbers, especially from a smart city perspective because those citizens represent an almost untapped source of data and smart city information.
Across the world, all types of sensors are now woven into the fabric of big city life – and they generate billions of data points from things such as parking meters, street lights, traffic control points, weather monitors, air pollution stations, and security systems. It is a market that is getting bigger – industry analysts estimate that the sensor market will grow from $424.4 billion in 2017 to reach a global size of some $1,201 billion in the next five years.
But the city’s human lifeforce represent another potential data source on the ground and given the right tools, they are keen to get in on the information act as well. By connecting through specially created smart city apps, social media and other channels, citizens can provide real-time on-the-ground information on traffic problems, safety concerns, vandalism, emergency health situations and a host of other issues – the trick is to separate the nuggets from the noise.
Pulling all that information together and combining it with data from IoT systems and smart city sensors can help create truly actionable and life-saving intelligence. In fact, combining and integrating data from multiple and varied sources could underpin a city-wide action plan that married improved efficiency with increased safety and faster reaction times for first responders.
However, we will only achieve this and make smart cities really smart if the entire ecosystem stops working in data silos. In order to do this, collaboration is required – between different municipal departments, the emergency services, with businesses and NGOs, and most importantly with the citizens themselves.
By integrating citizen-sourced data from smart city apps, and encouraging citizens to report incidents or flag concerns via the app, a city’s Facebook page or its Twitter handle, then the people living and working in a city can truly become part of its lifeblood; helping public authorities, bus companies, the emergency services, businesses and other organisations work more efficiently, and work together.
However, to make all this work, cities need to create new style ‘Command and Control Centers’ to deliver this unprecedented visibility of a city’s landscape and allow planners and first responders to do their jobs more effectively. Creating a ‘spinal cord’ of machine and human data for a smart city will help support law enforcement, public utilities, disaster management, and environmental controls. For example, areas of India and Pakistan recently suffered levels of air pollution so severe that it actually caused fatal traffic accidents. The ability for cities to detect and prevent these dangerous pollution levels from occurring in the first place by correlating real-time and historical data across traffic, meteorology, and air quality systems, will literally save lives.
These command and control centers should emulate how today’s communications service providers leverage, correlate and analyze the massive amounts of data that is traversing their digital networks. Bringing together smart city performance management, event management, and automation and orchestration functionalities with advanced visualization, would give authorities the ablity to detect possible incidents and also provide coordinated responses to emergencies, natural disasters and terrorist attacks much more quickly and effectively.
If we consider the string of natural disasters that have hit North America so hard – the fires in California, earthquakes in Mexico, and the hurricanes across many states – there was a clear need for city officials to have real-time information on what was happening right across their cities; and to be able to analyze and co-ordinate a response to this information in a way that optimizes available resources and minimizes risks to life and property.
However, all too often, valuable information is held within data silos instead of being shared and leveraged across teams, sytems and functionalities.
For example, by analyzing social media for crowd-sourced updates on where flood levels are rising and data from flood gauge sensors, city transportation officials could implement road closures and deploy life saving services to those in need. When this information is also fed to emergency responders they can be given alternative route information and plan their approach to a call out before they arrive at the closed road.
This kind of collaboration is only possible through a proven, carrier-grade service assurance platform that can scale to ingest billions of data records per day and uses open APIs to collect data from a range of sources. Data correlation, analytics and automation is then required to provide the advanced incident management needed.
From a management perspective, this also involves the ability to set and enforce policies across a variety of systems and to streamline workflows to ensure that city workers and first responders have access to the right information at the right time – giving them the ability to make faster, more reliable decisions. Being able to analyse this enormous amount of information quickly enough to provide this level of support requires advanced data visualization and dashboard-style reporting to help simplify the amount of information being presented.
Next generation 5G technology also has an important future role to play in this scenario. The network-slicing ability of 5G networks means that these smart city services can run across dedicated slices without impacting consumer capacity. This is important. That consumer capacity is needed both to enable citizens to access smart city apps in order to report incidents and provide on the ground information; but also to ensure that they can receive information from the smart city centre – perhaps data from traffic cameras to help drivers find alternative routes to avoid congestion.
Most of today’s smart cities are already generating billions of data points, but it’s how they correlate, analyze and share this data from multiple sources and across teams and organizations that will turn them into the Smarter Cities of tomorrow.
