A sense of place: How IoT sensor data powers smart cities
What makes a smart city smart? Data. Terabytes of it from a myriad of sources, both public and private. And the more data a city has to work with, the smarter decisions it can make about infrastructure spending, ordinances and more.
IoT sensors are a key source of this data. Take, for example, a city that’s growing so rapidly that its streets can no longer accommodate all the additional vehicles. Same with its sidewalks, which are packed with pedestrians, many of whom trek blocks to their destination because that’s the closest they can find a parking spot. And, on top of everything, there are now countless numbers of e-scooters zipping in and out of vehicular and pedestrian traffic.
This growth has a lot of obvious upsides, starting with additional sales and property taxes to expand roads and public transportation. But there are also downsides, such as trying to pinpoint where the money can have the most impact. Even the fastest-growing cities still have to spend tax revenue judiciously because there is always more demand than budget.
One type of IoT sensor, for example, is video cameras which can be utilized to count pedestrians and vehicles and, as a result, identify traffic trends. Video can also help identify near misses between pedestrians and vehicles that indicate the need for signalized crosswalks, raised medians and pedestrian bridges to minimize jaywalking.
Another type of sensor is audio, which can be used on its own or in conjunction with video. For example, audio sensors can identify screeching tires that indicate near misses, which drivers may not report and thus will fly under the radar until they escalate into accidents and injuries.
When a smart city understands how traffic is trending, it can head off these and other problems. This proactiveness helps make taxpayers perceive the city as a wise steward of their money.
The audio and video, for example, can be used to augment data from other types of sensors, such as infrared detectors for pedestrians and cyclists. Together, all of these IoT devices enable smart cities to make data-driven decisions about where to add transit stops and signalized crosswalks, or where to implement congestion-based tolls or additional paid parking.
Sensors also can detect waste — literally. Companies such as Big Belly and Enevo use sensors to detect when public, business and residential trash bins are full. This helps minimize traffic and pollution because solid waste vehicles now go only where they’re needed, instead of following routes where only some dumpsters and trash cans need to be emptied. The reduced pollution isn’t just vehicle emissions; it’s also the trucks’ noise pollution, which is another known health hazard in urban areas.
Mobile sensors can provide more and deeper insights — often for a fraction of the cost compared to blanketing a city with thousands or tens of thousands of fixed sensors. For example, the Environmental Defense Fund (EDF) uses vehicle-mounted air quality sensors to map pollution levels in cities such as Houston.
Mobile sensors can also be installed on vehicles that a smart city already owns, such as buses and police cruisers, but they don’t have to be installed in the entire fleet to produce enough data. A September 2018 study by the EDF and Geotab found that data from just 20 vehicles could be enough to map almost 80% of a small or medium-sized city.
Businesses and citizens also may be willing to share data their vehicles already produce if they believe it will reduce traffic jams and pollution. For example, the U.S. Postal Service wants to share its data about road conditions with smart cities.
An obvious concern is privacy, but a lot of work is underway to make it easy for vehicle owners to share anonymized versions of their data with third parties, such as departments of transportation. TM Forum, for one, developed APIs and processes mobile operators and others can use to anonymize customer data.
As cities grow, so do their potential sources of IoT data. It’s up to smart cities to use that data to ensure that growth doesn’t come at the expense of quality of life.
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