The concept of smart cities was premised on integrating information, communications and Internet of Things (IoT) technologies like sensors and cameras in a secure fashion to manage a city’s assets. One goal was more effective and cost-efficient management of city infrastructures and property, but equally important was responsiveness to emerging infrastructure events to help cities and their occupants.

Several years ago, cities began integrating their traffic management systems with city geographical information systems (GIS) so city planners and also city traffic managers could observe traffic flows, determine maintenance needs, and plan for future infrastructure. Initially these efforts captured static or near real-time information from sensors placed on traffic lights, at intersections, or on other stationary infrastructure assets that the city managed.

SEE: Smart cities: The smart person’s guide (TechRepublic)

Now, big data and analytics technology can further contribute by adding data collected from sensor feeds of commercial vehicles. A fleet truck accelerometer, for instance, can measure speed increases, braking, and tire vibration. Other truck-equipped sensors can measure weather conditions such as temperature. As trucks travel, this data can be transmitted in real time to commercial fleet managers–and it can also be piped into municipal data repositories to enhance knowledge about urban road infrastructure as truck fleets pass through the area.

“We call this field telematics,” said Mike Branch, vice president of business development for GeoTab, which provides fleet tracking software. “By collecting real time IoT data from trucking fleets, cities can acquire data about weather, road conditions, intersections, traffic lights, dwell times, and traffic jams.”

Branch referenced work being done in the city of Toronto, which is collecting incoming data from the accelerometers of fleet vehicles as the vehicles pass through. “The accelerometers show where trucks are slowing down, and the city has been using this data to locate road hazards like potholes,” said Branch. “The accelerometer data also assists in locating areas where railroad crossing signs are missing.”

Across the border at the Ohio Department of Transportation, Streetlight Data, which measures traffic behavior, is working with city planners to leverage the data that can be collected from IoT-equipped trucking fleets to deliver information about traffic flows and about the timings of traffic lights.

“The overall goal is to improve efficiency in municipal planning practices,” said Laura Schewel, Streetlight Data CEO. “In cities like Columbus, we are able to tell how new infrastructure additions are affecting traffic. This enables the city to make adjustments as needed.”

SEE: How Columbus, Ohio parlayed $50 million into $500 million for a smart city transportation network (TechRepublic)

Both GeoTab and Streetlight Data acknowledge that more besides technology is needed for cities to get this technology to work.”It can be challenging to get employees to change their work practices,” said Jean Pilon-Bignell, manager of strategic marketing and development at GeoTab. “But once they see the value, they begin to adopt the skillsets.”

Business cases are starting to demonstrate value.

“We have a large IoT-equipped truck fleet presence in Mexico City, so when the earthquake struck in September, we already knew that something disastrous was happening before the quake was even reported, and the ability to quickly respond was there,” said Branch.

As more cities incorporate new data feeds into their GIS and traffic management systems from sources like commercial truck fleets, they will also improve their ability to respond and to plan. Cities that reap the greatest benefits will be characterized by the following best practices:

1. Top-down management commitment

There will probably be initial resistance to any new GIS-traffic management approach. “Decision makers have to decide that they are going to replace older data collection and performance measurement tools and streamline existing processes,” said Schewel. From there, it becomes a process of fostering this commitment throughout the organization and providing employees with the necessary cross-training.

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2. Before and after metrics

Too often, cities implement new solutions and make infrastructure changes–but neglect to do a followup to measure the results. “Processes need be put in place to measure both the before and after effects of making a change based on the analytics,” said Schewel. A good way to do this is to measure how you are doing a specific function, like reducing traffic jams, before and after you implement a technology solution. One metric could be how often a particular intersection was getting jammed before implementation of traffic monitoring technology that could alert drivers of delays, and how often the intersection was congested afterward.

3. A focus on diagnostics

Cities already have GIS systems in place that can perform advanced mapping functions. Now is the time to make these systems more diagnostic-oriented by equipping them with dynamic feeds from trucking fleets and other sources, analytics, and data modeling that better equip staff to diagnose infrastructure hazards and events as they happen. These diagnostics also help planners and those responsible for scheduling maintenance activities because they can see where the infrastructure problems are.

4. A system install that includes people as well

Too often, system installs are planned without sufficient time or resources set aside for training. A new GIS/traffic management system approach is a big change for many staffers. Cities adding enhanced analytics and IoT shouldn’t underestimate this task, or the fact that many workers, used to doing their jobs for years in certain ways, can be nervous and resistant to change. Time should be set aside to help them understand the new system and how it works so they can get confident and comfortable with the new technology before it goes live.

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