Thanks to the ubiquity of smartphones and laptops, people are used to getting what they need at the press of a button – whether they’re looking for information, seeking action or trying to solve a problem. Citizens want that same ease of access from their city’s government.

As more citizens expect routinely effective, efficient and responsive services, cities have embraced new ways to meet that need. By adopting improved and emerging technologies to create smart cities, many cities are changing how they operate by relying on “smart” technology to help them better govern and serve their citizens.

The essential role of technology: IoT in smart cities

In smart cities, governments use technologies like the internet of things (IoT), communications, social media, data storage, advanced analytics and artificial intelligence (AI) to improve life for residents. IoT solutions also help city officials address issues related to changing populations, increasing government regulations, workforce shortages, decreasing tax base growth, aging infrastructure and constrained budgets.

Yet IoT technology creates challenges, many related to data’s explosive growth. The number of IoT devices is expected to almost double to more than 29 billion IoT devices by 2030. Cities add to this big data trend, generating vast amounts of new data streaming from IoT devices like streetlight sensors and water meters.

As data continues to grow, it’s vital for cities to integrate, manage and make good use of these bits and bytes. Adopting as the framework for information systems provides intelligent insights from the enormous amounts of data generated by governments, stakeholders and citizens.

Related: Jakarta and SAS teamed up to create an award-winning approach to public services and disaster management. Get an inside look at what they did. 

IoT and telecommunications

Software has evolved rapidly. While it used to only exist inside computers, now software is embedded in everyday objects, like meters, sensors, cellphones, vehicles, infrastructure and machinery.

Wherever it resides, this software – part of IoT and smart cities technology – collects, communicates and analyzes information. By employing such technology, governments gain deeper insight into and control of their operations.

The data streaming from connected “things” – devices like sensors or meters connected through the internet – can be integrated with the systems used to run smart cities. This results in better management and smoother operations.

Here are just a few examples.


Automated meters collect water and fuel consumption data and analyze it at regular, frequent intervals. Cities use this to understand consumption patterns and trends, identify anomalous use that requires attention, and set policies and practices to influence future consumption.


Location data collected from cell phones and transit passes helps planners understand how residents move through the city. These insights, along with other smart city solutions for mobility, provide the information needed to plan resources, optimize transportation networks and forecast future needs.

And when cities embed technology in streetlights, it can reduce traffic congestion for drivers. Using sensors to monitor congestion and communicate with software, the system can adjust traffic signals – based on real-time data – to improve traffic management.

Related: See how SAS is getting it done with location intelligence for government

Parking spaces

Sensors in the parking bays of decks provide real-time information to help drivers find available spots. This not only improves the driver's experience but also minimizes the congestion created by drivers circling decks to search for empty spots. When analyzed, the information gathered from parking sensors enables governments to forecast parking needs, set demand pricing, and optimize resources.

Smart waste management

Cities are deploying many different IoT solutions to improve the environmental impact of waste and its removal. For example, sensors installed on dumpsters can issue alerts to collectors that a dumpster is full, reducing the number of unneeded visits from waste collectors. Sensors are also used to separate recyclables from waste to ensure cleaner recycling streams and to reduce waste going to landfills.

Public safety

Smart city solutions can protect the safety of communities and their officers. The analysis of video and static images from license plate readers, streetlight cameras and vehicle cameras aids in surveillance. Wearable technology helps officers protect their health in the line of duty.

Data from these non-traditional sources is integrated with data from other law enforcement information systems, helping to identify criminal patterns and trends and reveal hidden relationships. In turn, public safety organizations can thwart crime and complete investigations faster.

Air quality

With climate change at the forefront of government leaders’ minds, sensors that track air quality and analytic tools that calculate carbon scores are being adopted. Sensors on green energy devices like wind turbines and solar panels optimize their performance and make them more cost-effective.

The internet and social media

In addition to data collected from IoT devices, a huge amount of data generated by individuals on the internet can be valuable for cities.

Do you share your thoughts, likes and concerns on social media? Those posts generate data that can be collected and analyzed to understand trends, identify issues and make better decisions. As always in government, leaders must balance their use of publicly available information with their responsibility to protect privacy and provide security.

Cloud storage

Smart cities collect massive volumes of IoT data that must be securely stored, managed and accessed. Some store the data onsite, but many choose to store this data in the cloud. As governments strive to replace legacy systems and work with shrinking workforces, more are moving to cloud environments.

Because cloud-based storage is internet-accessible and can scale on demand, it gives smart cities more flexibility for storage and computational power, based on changing needs. When these services are provided by cloud-hosting companies, cloud storage also decreases the costs and labor of maintaining and running municipal servers and databases.

A city doesn’t have to buy more space or processing capability than it requires when it stores data on the cloud. And city governments don’t have to worry about insufficient storage space or slow operations due to inadequate processing capacity.

Related: AI and sustainability: Balancing innovation with environmental impact


City governments use analytics software – which incorporates a variety of statistical analysis methods and algorithms – to turn IoT data into valuable insights. This analysis can be as simple as general business information that looks at data to determine what has already happened. Or, with more advanced analytic techniques, cities can uncover elusive insights from their data and better predict what might happen next.

  • Artificial intelligence: AI combines intelligent algorithms and fast, iterative processing with data to learn automatically from patterns or features in the data. Then, this information is used to solve problems. AI makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks.
  •  IoT analytics: IoT analytics refers to analytics used with IoT data. Edge computing is data processing that happens at or near the “edge” of a network. Likewise, edge analytics is when analysis occurs at the “edge” of the data-collecting device. When the analysis happens as data is being communicated from a collection device to a database, it’s known as streaming analytics. IoT analytics can help cities reduce costs and improve transparency by enabling them to identify trends, patterns and anomalies rapidly with real time decisioning. By doing this at the edge or with streaming data, governments reduce the amount of data that needs to be communicated and stored

High-performing AI technology sorts through incredibly large volumes of data to identify correlations, trends and anomalies. By processing millions of records or events per second, it accomplishes work that’s too time-consuming or difficult for humans, as well as those that are mundane and repetitive. AI is particularly valuable for governments with workforce shortages as it can help governments do more work with fewer people.

Advanced analytics and AI give leaders and service providers the intelligence they need to make fast, data-driven decisions. This can help city government leaders understand what has happened and why. It also helps them determine future outcomes and trends. With this knowledge, a city can more accurately predict the impact of events or specific actions and then optimize outcomes.

Leading the way to the future

Smart cities help communities meet today’s needs while preparing for a future of sustainable infrastructure and effective public services. By facilitating better decision-making based on data – in areas like public safety, air quality and transportation – IoT technology provides solutions to improve the quality of life for residents of cities around the world.

Learn more about smart cities


About Author

Jason Mann

Vice President of Internet of Things (IoT)

Jason Mann is responsible for growing IoT revenue and providing global focus, strategic direction and alignment across the SAS IoT analytics portfolio. He oversees the research and development, product management and marketing, and execution of the sell-through strategy across the portfolio. “My job is to empower R&D teams to innovate and create the forward-looking solutions that enable customers to seize the opportunity inherent in IoT, solve specific business challenges and capitalize on the insights mined from the data,” said Mann. Prior to his current position, Mann served as Director of Product Management for Industry Solutions and the Internet of Things where he set the strategic IoT direction for SAS. He was also responsible for product management of the manufacturing and supply chain, retail, energy, and health and life sciences industry solutions. Prior to that, he served as Manufacturing Industry Strategist where he led the internal and external positioning of SAS’ distinctive competence and value to the manufacturing industry. Before joining SAS in 2003, Mann worked at Nortel Networks for 10 years where he led the multiyear design and implementation of global manufacturing operations and order management systems. Mann received a bachelor’s degree in industrial engineering from North Carolina State University.

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