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May 22 2018

Use wisdom of crowds to design smarter cities, businesses and networks

It’s hardly revolutionary to argue that cities and their infrastructure — including networks — should be designed around the needs of people. Yet, all too often, they’re not. Instead of working for people, the public spaces, support systems and business areas of the city are often designed with other objectives in mind or, simply, with too little real data. Where do people go and why, and when and how do they move?

Crowd data tells us where, how and when people move

The ‘wisdom of crowds’ is a new design principle for building sustainable, attractive and appealing cities. To understand the wisdom of crowds, we need crowd data that depicts the movement patterns of people. Crowd data tells us a lot about where people are, and when and how they navigate within cities. It can model the motion of people using aggregated telco data for drivers, commuters, pedestrians, shoppers, tourists and restaurant goers — all of them consumers of urban services.

The intelligence encapsulated in the anonymized movement data can yield answers to such questions as where to locate businesses, roads, bus stops and stadiums. As well, it can reveal who’s visiting stores and businesses, whether from home or office, at what time, and from which areas. It can help multiple verticals like retail, public transportation, urban planning and tourism to design better services and service delivery systems, and offer the services then when people want them.

Businesses thrive when they are where the people are

The crowd’s location and movement data enable businesses to learn from the wisdom of crowds and understand the needs and wants of people based in part on this navigational knowledge. Marketing, promotions and advertising can better target the right messages to the right people only when they understand the movement data.

AI-powered networks should follow the crowd

Effective, high functioning networks also cannot be properly built without understanding people’s location or movement patterns and projections. The principle is pretty simple: ‘AI-powered networks should follow the crowd’. Demographics can help the network to be available where the people are, even on short notice. Imagine, for instance with network/5G slicing, a network enterprise service slice spinning up instantly, on the spot and on an “as-needed basis”. Or, imagine greater bandwidth being brought on line to support a sudden, unplanned gathering in a public space.

Data remains anonymous

Today the mobile phone is the primary device for most people; virtually everyone has one. Thus, for communication service providers (CSPs), the number one source for information is its own network data. The data powered by machine-learning and predictions reveals where people are, when and how they move (from home to office and back home, office to shops and home to shops) and how (walking, cycling, by train or car). No insights about the whereabouts of the individual customer need be revealed; anonymised data is used to derive spatial insights from the crowd on the move.

Telco’s will be people flow experts

Telco data can truly enable organizations to serve people better across the globe – telcos have a big role to play as enablers of this transformation. They have a unique chance to monetize movement data to support smart cities and services, helping municipalities, businesses and other service deliverers with their location, advertising and marketing strategies, including finding the most optimal locations for billboards as an example. And the data never ends; people are constantly in-motion and no one else knows as much about the flows of people as the CSP.

Detect an anomaly and trigger an action

People movement data can also identify when crowds go wrong: for example, when there is an earthquake, a major medical emergency, or even a crowd of teenagers disturbing others at night having too much fun. The ability to detect an anomaly and trigger an action is embedded in the crowd movement data. Crowd analytics and modelling of normal behaviour, can trigger an automated or human action based on deviations from the norm. Some examples are a sudden traffic jam outside of rush hour, a health situation or emergency, concerts or big sporting events, even a strike or popular demonstration. All of these can be detected in the crowd data. Security should be there to protect citizens and make them feel safe. First responders should be completely attuned to crowd movements and be there immediately when things go wrong.

The ecosystems can be strengthened with more and more real-time data about crowds. Smart cities will have the means to intervene in real-time through intelligent transport planning, traffic management, intelligent parking and so on. We don’t need to look far to find examples, Nokia and StarHub have been working together and deployed the solution successfully in Singapore, to improve the transportation and the infrastructure planning of the city, enable contingency planning for authorities and public safety agencies.

These are just some of the ways that CSPs can derive value from crowd data and make it actionable. Its value is its built-in decision-making power. It helps enterprises, cities and even CSPs themselves to better serve their customers and optimize the customer experience, adding another dimension to the Customer Experience Index. Crowd data combined with actionable customer experience KPIs form a combination that can improve customer and citizen satisfaction, attract businesses and workers, and make cities better places for people to live.

Read more about Cognitive Analytics for Crowd Insight and download this infographic: Supercharging the Customer Experience with AI.

Share your thoughts on this topic by joining the Twitter discussion with @nokia and @nokianetworks using #AI #IoT #analytics #innovation  #machinelearning  #smartcity 

About Malla Poikela

Malla is Head of Marketing for Nokia Software’s Digital Intelligence unit. She oversees Nokia Software’s core strategic messaging around analytics and AI, and the customer-, business- and network-driven insights offering. Malla comes back to Nokia from Comptel, where she was senior director for industry marketing, and a strong proponent of the power of intelligent data. With 20 years of experience across the industry, Malla is a recognized presence at industry events and in social media, and is a passionate advocate for customer experience, digital transformation and software.

Tweet me at @MPoikela