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From Traffic Control to Sanitation, 2018 Moved Smart Cities Forward

In perhaps no other area does the IoT, big data, artificial intelligence, and machine learning come together as powerfully or offer more potential than smart cities. There is virtually no task associated with running a city that these technologies can’t make more efficient, operate better, cut costs or improve in other ways.

Officials whose job it is to keep cities running smoothly – planners, technologists and a host of others – must understand how these smart city tools are evolving and being integrated into citizens’ daily lives. Without up-to-date information, officials will quickly fall behind in not only technology, but the knowledge they need to efficiently manage their smart cities.

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Over the last year, there have been many advancements in smart city technology that officials need to know about. That said, technologies don’t evolve according to a calendar. One year blends into the next. Clearly, however, 2018 was an important year for smart cities, with great examples of exciting smart city IoT use cases.

Here are three examples of smart technology use in 2018 that will help city officials understand how smart cities are moving forward and improving the quality of life of their citizens.

IoT Sensors and Machine Learning Helped Cities Beat Traffic

Nobody likes to sit in traffic. People are especially annoyed to wait through two or three cycles to get through a stop light. Therefore, an important traffic management task is to better understand current conditions and adjust lights to improve traffic flow.

A tremendous source of information that can help is IoT sensors embedded in roads. IoT road sensors track traffic volume, the condition of the road, and other important factors. IoT data may be combined with information on time of day and major events, such as whether or not school is in session, and whether a construction project is reducing road capacity.

These and other variables enable AI to calculate the best way to time lights. As time goes by and sensors generate more data, machine learning incorporates the new information into planning going forward.¹

Video Analytics and Smart Tech Improves Utilities and Public Services

GovernmentCIO Media points to four potential uses of AI, including addressing water, power and waste systems.² These systems use similar adaptive signal control as in traffic lights, but to better control public services.

Other smart cities are using the technology for trash and cleanliness. Matt Hamblen at SmartCitiesWorld recently reviewed the ways municipal leaders are using AI and machine learning to keep Las Vegas clean.³ The system assesses video from security cameras to detect trash, graffiti and eyesores, something that’s possible with video analytics software. Cleanup crews are dispatched when an issue is spotted, helping city workers address problems more quickly and keep parks cleaner. The system even helps cut costs because crews are not automatically sent to clean parks, they’re dispatched only when needed. At the time the story was posted, the program was in use in two parks and a third was on the table.

Analytics and IoT Reduce Truck Congestion and Emissions

Some smart city use cases are unique. Dutch cities famously make extensive use of canals. In Delft, Nokia and Dell EMC are working on a public/private smart city initiative to reduce truck congestion and lower emissions in the city center by using semi-autonomous, hydrogen-powered barges for last-mile transportation over underutilized old canals.

Partners in the project include Blue Turtle Associates, Aratos Systems, Circle Lines, City Hub, SPIE, the University of Delft and the Provence of South Holland regional government.

A key to the project is the use of a Common Information Space for small city logistics. This is a scalable digital platform that controls the logistics chain in and around the city and serves as the core of the navigation guidance system. Dell EMC and Nokia are contributing computing, storage, data management, connectivity, analytics, IoT and blockchain capabilities.4

Smart Cities: Exciting New Options Solving Common Problems

All these examples have something important in common: they focus on solving the major issues cities around the world are facing today. That’s the greatest value of the IoT technology and machine learning. It can provide new ways to address problems and make mundane tasks more efficient.

2018 saw many examples of this side of the potential of smart cities. We’ll continue to see similar advancements and increasing adoption of smart city use cases in 2019, with more cities adopting advanced solutions to improve efficiency and quality of life.

 


¹ https://aibusiness.com/intelligent-traffic-smart-cities/
² https://www.governmentciomedia.com/4-examples-how-ai-can-make-cities-smarter
³ https://www.smartcitiesworld.net/special-reports/special-reports/las-vegas-cleans-up-with-machine-learning-
4 https://www.prnewswire.com/news-releases/dell-emc-and-nokia-team-up-on-digital-city-project-to-deliver-goods-using-semi-autonomous-barges-in-the-city-of-delft-300748650.html

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Case Study: IoT is redefining the customer experience. Nokia case study.

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