Seize this moment to invest in the present and future of transportation

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APIs open secure shared connections

APIs allow these sensors to work together, seamlessly and more securely connecting previously separate devices. For example, data from a company-made smart traffic camera can be shared with information collected by connected vehicles.

Connecting these seemingly disparate assets creates a mesh that can help cities improve everything from traffic to air quality and pedestrian safety.

Using open enterprise standards, modern APIs help municipalities consolidate existing investments in proprietary cameras and sensors while positioning themselves to accept new endpoints, regardless of manufacturer.

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Rule Engines Lead to Smarter Decision Making

Finally, the rule engines deployed in containerized applications that live near the sensors determine what information to process locally and what to send to the centralized cloud or to the agency data center.

The more data that can be processed at or near the edge, the faster the decision can be made. Expenses are also reduced, as edge processing helps agencies avoid the excessive entry and exit costs incurred while transmitting data to central data centers.

Perhaps more importantly, the less data has to travel, the more resilient the overall ecosystem becomes. For example, an autonomous car must locally process data using artificial intelligence algorithms to make the decision in real time to stop before hitting a jaywalker. It’s like building human muscle memory through repeated practice and training to catch a frisbee or hit a curve ball.

Conversely, machine learning models can be used to determine smarter ways to reduce overall vehicle maintenance costs, improve safety, and increase overall customer and employee satisfaction.

For example, city bus telemetry information can be sent to the cloud to feed applications that notify customers when the bus will arrive at their stops. Telemetry information collected over time, coupled with data from vehicle weight sensors, can be analyzed using centralized machine learning models to provide better insight into when a bus needs maintenance. preventive.

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Standard, open infrastructure and future possibilities

Ideally, each of these technologies should be supported by a common enterprise open source infrastructure. This allows better interoperability between the different types of sensors. It will also provide IT professionals with a standard, consistent framework on which to build and iterate over time.

Inherently modular components prevent agencies from having to make significant changes to their IT infrastructure every time they add a new tool to their toolboxes. They can add new features and applications incrementally and require less rework, which speeds development while keeping costs low.

These core technologies set the stage for endless future possibilities, large and small. Imagine having the ability to manage and monitor thousands of connected red lights from one central location across a city. Imagine giving a state department responsible for motor vehicles the ability to gradually modernize without needing to make substantial and costly changes to their IT environment.

State and local agencies must continue to reflect on these future opportunities and move away from outdated technology and thinking while continuing to care for the present. Agencies should not lose this chance to meet all of their infrastructure goals.

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