IoT network insights drive smart city planning
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A cloud-enabled sensor network helps city officials meet resident needs and collaborate with neighboring communities.
Dozens of sensors deployed in downtown Cary, North Carolina, are part of a long-range network that collects ambient data to inform infrastructure and community decisions.
The long-range wide-area network (LoRaWAN) operates on a low bandwidth and provides a broad range of coverage for “sustainably lower” costs, said Justin Sherwood, the city’s deputy chief information officer and smart cities coordinator.
The sensors operate on a sub-gigahertz radio frequency, similar to ones used by AM and FM radio signals or police radios, to transmit packets of encrypted data to city servers, he said.
“We did a lot of piloting with different applications, different platforms, different sensor types, trying to understand what smart cities look like … in the future,” he said.
An internet-of-things network was an obvious choice to facilitate the collection of smart city data, Sherwood said. “That’s where LoRaWAN comes into play for us. It’s a connectivity that we can rely on.”
It uses very little power and it was easy for Cary to add devices that transmit data over a long range. In partnership with SemTech and the SAS Institute, Cary has been building a LoRa IoT network in the downtown area, with sensors scattered throughout the city’s greenways and various facilities.
The devices capture various types of data, including moisture, CO2 emissions, the number of pedestrians, available parking and more. For instance, one sensor in the network can track air quality at busy intersections while another tracks traffic congestion.
Then, the city’s three gateways, which are devices that facilitate the connection between data sources and end users, collect the information and send it to the city’s Microsoft Azure cloud environment. “None of that happens internally.… [Data] goes straight from the sensor to our Azure environment,” Sherwood said.
One advantage of the LoRaWAN network is built-in data redundancy enabled by the gateways. One sensor can link to two gateways, so if one gateway goes down the sensor can still contact the other, he said.
Another advantage is the device’s ability to customize the type of data the sensors gather. For example, a sensor used for people counting can be programmed to detect a host of variables such as count, date, time and speed or to only pick up one or two fields. This allows Cary to gather the specific data it needs, Sherwood added.
For example, before expanding a community park, it’s helpful to know how people use it. It’s important “to understand patterns and understand what people are doing so we can better serve them,” Sherwood said. If sensor data indicates park visitors tend to head to the grocery store or a restaurant afterwards, “there’s an opportunity for us to do more food trucks at a certain time or certain day of the week.”
The LoRa network can also foster data-sharing relationships with neighboring communities—in stormwater management, for example.
Since Cary resides at the top of a basin, rainwater that collects in the city travels downhill to regional partners, he said. The LoRa network can help with monitoring, forecasting and alerting users in neighboring municipalities to prevent flooding and other damage.
“The data is there to help make decisions in the future,” Sherwood said.