Projections indicate that more than half the world’s population will be living in cities by 2030, the towns and cities of the developing world will make up 80 percent of urban humanity. Fast-forwarding 20 years to 2050, seven out of every 10 of us will be a city dweller.
Mobile, social and sensor data
As the use of social and mobile technologies increase and physical objects are embedded with sensors, cognitive systems will be able to find patterns in the vast quantities of data produced. They can then reason through patterns that emerge and learn from their interactions with us to refine their suggestions. A new generation of machine learning algorithms and language processing systems will emerge to address those needs.
By 2017, the number of smart phones in the world is expected to top three billion – this will allow people to have a digital key to the city right at their fingertips. Information will be delivered to their phone and about what is happening in the city, what experiences are relevant to them and how to get there. Mobile apps will become the new norm for reporting and tracking pot holes, broken street lights and inaccessible sidewalks. For example, IBM Researchers in Brazil are working on a crowdsourcing tool, Rota Acessivel, that allows users to report accessibility problems to help people with disabilities better navigate challenges in urban streets.
City leaders, too, will be able to have a direct communication channel to every citizen, allowing city leaders to develop tailored plans for communities and regions, addressing each citizen’s needs in a unique way. Crowdsourcing and social sentiment analytics give city leaders a massive amount of feedback on constituent issues they can take action on. In Uganda, UNICEF is collaborating with IBM on a social engagement tool that lets Ugandan youth communicate with their government and community leaders on issues affecting their lives. Using IBM text analytics and machine learning, leaders are able to identify trending concerns or urgent matters and immediately take action where needed.
Take another example: Rather than running empty buses on fixed timetables, routes will be altered by citizen needs. Or, when it is raining more buses will be put into use to keep pace with an increase in riders (and the riders will be notified over mobile apps). Sensors, which are expected to reach more then 50 billion by 2020, will also alert sanitation workers as to which waste bins are full on city streets. And even inanimate city buildings will no longer sit empty with air conditioning blasting and lights ablaze, as they will smartly, efficiently, and autonomously adjust the environment.
By allowing cities and their leaders to unlock the knowledge in the data being produced around them, cities can become more flexible, increasingly flatter, less encumbered by bureaucracy and more open to sharing data and insight, allowing citizens to have direct input to community and city plans and receive feedback from city leaders.