Big Data & Smart Cities: How can we prepare for them?

here are 1.3 million people moving into cities each week, and by 2040, 65% of the world’s population is expected to be living in cities, with 90% of this urban population growth set to occur in Africa and Asia.

From e-bikes to congestion charges, experts have spent decades trying to improve the quality of life in our cities.

We have heard the term “smart city” many times but what does it mean?

A smart city is simply one that uses technology to improve outcomes across every aspect of city operations and enhance the services it offers to its residents.

So what is big data’s role in the equation?

Let’s imagine a display on your dashboard window alerts you that weather conditions have made your usual route to work less favorable and, subsequently, reroutes your trip to the office based on real-time calculations of optimal conditions. Once inside the parking garage, another alert notifies you of the closest parking spot, determined by an estimation of your workplace based on your established commuting patterns.

Such a vision is not one of the future but of present reality. Indeed, cities have increasingly adopted technologies like Big Data, the Internet of Things (IoT), and distributed sensors to create what many are calling the city of the future.

We can see it through the deployment of connectivity resources (community fiber, municipal Wi-Fi) or single-purpose applications (smart street lighting, smart parking or waste management).

A few cities have begun to value a more forward-looking approach that cuts across multiple Smart City applications, focusing on data as the common element.

Data is the lifeblood of a smart city.

Common ground

To become a smart city, cities need at least one thing in common. They all need reliable (sensor) data to base their long-term decisions on. Because data is the new gold.

By inserting sensors across city infrastructures and creating new data sources — including citizens via their mobile devices — Smart City managers can apply Big Data analysis to monitor and anticipate urban phenomena in new ways.

Example of a sensor being used to improve the city management

Big data, has huge potential to increase and make use of smart city services. Big data is basically huge amounts of data that can be analyzed by businesses to make appropriate strategic moves and business decisions.

Big data analysis is implemented to study large volumes of data to uncover patterns and get insights to extract valuable information.

Information and communications technology (ICT) plays a major role in smart cities by making data that’s collected through information technology components available. This technology, also called the Internet of Things (IoT), works by communicating between connected devices while exchanging data that requires internet, wireless connections, and other communication mediums.

Mainly, smart cities make use of IoT devices to fetch data and efficiently process it for implementing it in a particular area. Smart city sensors and connected devices collect data from various smart city gateways installed in a city and then analyze it for better decision-making.

Other technologies can impact the smart city process. Indeed, cloud platforms and analytic applications offer an economical means of managing transportation data and solutions, creating insights that deliver more efficient and safer traffic routes on roads that already exist. Machine learning applications that pull data from connected devices can provide real-time updates to travelers through smart phone applications.

Data is the lifeblood of a smart city.

Three layers of Data

First is the technology base, which includes a critical mass of smartphones and sensors connected by high-speed communication networks.

The second layer consists of specific applications. Translating raw data into alerts, insight, and action requires the right tools, and this is where technology providers and app developers come in.

The third layer is usage by cities, companies, and the public. Many applications succeed only if they are widely adopted and manage to change behavior.

Issues for the city management

Cities and their solution providers cannot extract the full value of data if it is held in disparate systems and databases that limit access and use. There are already huge amounts of data in our cities, however much of it is in silos serving specific needs, rather than contributing to the common good. It includes government statistics, maps, details on public tenders.

Better parking, efficient lighting, improved traffic flow, smarter security, improved waste management, and disaster planning are all areas where technology can make a difference. However, there’s a lot of fragmentation … we need a way to connect all these different standards and bring them all in a common, unified platform.

Creating a smart city depends on how well organizations can share and analyze the vast amount of data being generated. Without the ability to share key information in real time, businesses operating both in the private and public sector can’t develop the applications that support automation, nor the software solutions that form the ‘smart’ capabilities of a city and its infrastructure.

Furthermore, each new sensor type often requires a new database, which is often subject to the city procurement process. These systems frequently do not talk to each other in ways that are useful or intuitive, making it virtually impossible to extract actionable insights from the information.

Finally, cities are very cost-conscious, the financing of smart city initiatives being one of the many stumbling blocks. One of the major obstacles for getting smart city initiatives off the ground is the upfront cost of populating the town with sufficient sensors to be meaningful, but thanks to sensor data.

In developing cities, the reality is that operations are uncoordinated and data capture is still a heavy manual process.

A better city thanks to Data

Let’s analyze how data is helping cities around the world:

  • The city of Nanjing, China, has installed sensors into 10,000 taxis, 7,000 buses and 1 million private cars. The resulting data is transferred daily to the Nanjing Information Center, where experts are able to centralize and analyze traffic data and send updates to commuters on their smart phones. With these data insights, government officials have created new traffic routes to improve congestion, without spending money on new roads.
  • Trenitalia, Italy’s major rail operator, installed sensors on the trains and now gets real-time status updates on the mechanical condition of each train and maintenance predictions that allows Trenitalia to plan a course of action ahead of an unfortunate event. These technological innovations provide travelers with a reliable system and service, while allowing cities to prevent major disruptions.
  • LA is replacing 4,500 miles of streetlights with new LEDs. Not only will this result in brighter streets, but the new lights will also be an interconnected system that will inform the city of each bulb’s status. If one malfunctions, it can be identified and fixed almost immediately. In the future, we could have lights that change colors or blink to warn citizens of various conditions.
  • Large groups of people mean tons of data is generated. Big data is being used to understand when, how, and why crowds form, and to predict their movements and actions.

There are millions of sensors in place already, monitoring various things. In the near future, these sensors will multiply until they can monitor everything from streetlights and trashcans to road conditions and energy consumption.

The Data challenge

The effective management of data is not limited to data capture and storage, but must also include data that is shared and combined so it can be accessed, analyzed and used across departments, between organizations, and even with the community at large.

In every major city in the United States, and beyond, there are millions of sensors producing a staggering amount of data every millisecond, second, minute, hour, and day. That data is captured, stored and more or less forgotten after.

Smart cities need to be built on networks that allow for the free communication of data.

Data sharing represents both a requirement and an opportunity for Smart City deployments. It is clear that data sharing across citywide departments and platforms is an essential element of any Smart Cities plan.

My prediction is that most cities will implement data sharing as part of an evolutionary journey from data integration to data exchanges, and then to data marketplaces

Building the digital infrastructure

Why we need more APIs?

APIs

Sharing data unlocks efficiency and open APIs are the best way to do it. An easy exchange of data via APIs and/or data marketplaces, along with the ability to easily add partners to the ecosystem, are critical components of any smart-city platform.

There is also a growing trend for city authorities to release APIs to encourage developers and community organizations to use open data.

What we need in a good smart-city platform:

The perfect data-sharing platform

A data-sharing should enable cloud-based data sharing . It will improve privacy, interoperability, security and secure data sharing, agile app development and testing. A platform on which many applications can run also offers these capabilities for specialized, domain-specific applications as well as provides access to the most up-to-date technology.

The platform should support both public and private sharing. If solutions are going to intermix data, then the governance, security and usage monitoring and management becomes more important to control access.

Finally, it should offer the ability to understand and manipulate data into information that people from many different roles can understand and leverage to create other solutions.

Big Data stands at the forefront of this endeavor to provide pervasive connectivity at a citywide scale. These technologies will play a primary role in this growing trend to create the city of the future.

DataSeries

A network of data thought leaders, sharing lessons learned, in preparation for the future 🚀

Alexandre Gonfalonieri

Written by

I write about AI | Freelance AI Consultant @Philips https://www.linkedin.com/in/agonfalonieri9/

DataSeries

A network of data thought leaders, sharing lessons learned, in preparation for the future 🚀