Living for 10 years in California and 12 in Washington DC with a commute into downtown, I’ve spent a lot of time in my car. While road and traffic signal infrastructures are designed to do their best to facilitate my drives on an average day, these infrastructures are historically pretty terrible at dynamically adjusting to changing conditions.
Whether it’s Southern California drivers screeching to a halt on the 101 because a drop of rain hit their windshield, or the Secret Service closure of everything west of 14th Street in downtown Washington because of the visiting President of Djibouti, drivers and city managers alike know how hard it can be to dynamically manage our infrastructures.
Imagine if transportation officials could dynamically adjust speed limits according to detected weather, accidents, or other road conditions. Could traffic signal timing and duration be dynamically managed to optimize traffic flow in a congested urban center? What if motorists could be dynamically routed to nearest available parking, saving citizen time and reducing road congestion? Efficiency challenges like these exist across the spectrum of municipal infrastructures, and the internet of things (IoT) provides a host of new opportunities to make our cities smarter through the intelligent use of data from the connected environment.
Applying analytics to IoT data provides opportunities for cities to use information from sensors, citizens and connected infrastructure in unprecedented ways. Whether it’s dynamic traffic signaling via improved intersection monitoring, vehicle to vehicle (V2V), and vehicle to infrastructure (V2I) communication, or real-time detection of municipal water system leaks and contaminants, streaming data from sensors and citizens can be analyzed in real-time to make our cities more safe, sustainable and efficient.
Beyond helping to unclog our roads, here are four examples of how SAS Analytics for IoT can make your city smarter:
- Improved energy efficiency. Using IoT analytics to understand energy use in a smart grid, energy use can be optimally measured, delivered and forecasted. This improves service reliability and reduces waste.
- Better sustainability and conservation. Analytics applied to water system sensors and customer usage data can automatically detect leaks and infrastructure failure, reducing costs and conserving water. In addition, embedded contamination sensors can report unsafe or contaminated water in real time, reducing exposure to citizens.
- Optimal service delivery. Trash and recycling receptacles, and any number of other service-connected city infrastructure can signal when they need attention, pick-up or repair, saving money and improving service.
- Anticipatory problem-solving. Applying SAS Analytics for IoT to streaming social media, and other citizen-generated data can help sense and understand the citizen environment. This permits government decision makers to anticipate and react more quickly to service disruptions or other problems.
The TDWI e-book, “Four Use Cases Show Real-World Impact of IoT” provides additional in-depth examples of IoT impacts in our cities. These and countless other examples demonstrate how rapid insights derived from analytics applied to streaming data can make our cities more efficient, more sustainable, more safe, and better able to provide services to citizens. Smarter cities through insights provided by SAS Analytics for IoT: Now that’s something to honk about.