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Capturing IoT Telematics Data Used for Smart Cities

Traffic and congestion are major problems for cities across the world. In fact, these problems are currently poised to worsen in the future, since these difficulties will increase as urban population centers continue to grow. Cities are under growing pressure to improve their infrastructure; however, they have less space and often tightening budgets. Data gathered from traffic patterns are becoming part of the solution. This addresses congestion, gridlock, pollution, and vehicular accidents. 

Most cities typically decide where to place new electronic crosswalks, traffic lights, turn restrictions, medians, and other upgrades based on accident reports. The difficulty with relying on these reports alone is that drivers don’t mention avoided accidents to the police, etc. This can mean that an intersection has become dangerous, but city officials have no way to know until it’s too late. Without analytics, cities are powerless to prevent initial accidents and injuries. Instead, they have to react after incidents happen and analytics can help pinpoint problem areas before issues even arise. 

Telematics Data from IoT-Enabled Devices

Using what’s known as the Internet of Things data (IoT), cities can begin the transition to smart cities. Large urban centers have hundreds of traffic cameras; but, it’s almost impossible to manage every individual camera feed. Traffic cameras can be upgraded using analytics to pinpoint problematic areas. Analytics monitors the bulk of the data collected. Meanwhile, city employees can pay closer attention to data feeds from important areas. 

Telematics, a subset of IoT, utilizes sensors like GPS mounted on vehicles. Numerous systems already exist, such as taxis, buses, etc. These vehicles use sensors to monitor speed, braking, and maneuvering to identify dangerous drivers. For instance, if vehicles are braking hard in a specific intersection or on a certain road, there may be a need for a turn lane. Telematics can also incorporate data gathered from outside vehicles. Houston is a prominent example of a city that uses IoT devices on the outside of vehicles to monitor air quality. Vehicle-mounted cameras can also analyze interactions with pedestrians or on-the-ground traffic conditions.

This technology provides actionable information for smart cities in the same way, as well as improves the effectiveness of infrastructure and transit services. Cities can only make the transition into smart cities by collecting and analyzing the right data. Using telematics data, cities can make their existing infrastructure and future investments go much farther than otherwise possible. Cities that wait to utilize IoT tools will find themselves falling behind other municipalities at an increasingly rapid pace.

Municipal Vehicles Telematics Systems

One of the easiest places for most cities to begin is by using their already-existing municipal fleets. Buses, waste-collection vehicles, emergency response vehicles, and others often already use various telematics systems. By applying analytics tools to these vehicles’ telematics systems, these municipal fleets end up serving a double function. Using municipal vehicles’ telematics systems alongside data collected from private and other public vehicles adds to the data available to city employees. 

Commercial fleet operators may share anonymous telematics data if it helps improve fuel efficiency, driver productivity, and accident prevention. The U.S. Postal Service also shares its telematics data with cities, making it an accessible resource. The Postal Service uses more than 200,000 vehicles, making it the largest civilian vehicle fleet in the world. Even a relatively small number of vehicles can give massive amounts of data. 

Geotab conducted a study in 2018 utilizing telematics data from more than 1.25 million vehicles. The study analyzed the data these vehicles collected and concluded that a small number of vehicles have the potential to give actionable insights into cities’ air quality. As few as 10 vehicles can map 50% or more of a small to medium-size city, and 20 vehicles can map just under 80%. Small fleets can collect this data in a relatively short period of time. 20 vehicles could map 65% of a city in about three months and 45% in just a month.1

Telematics data can, contrary to many expectations, be far more effective and affordable than fixed IoT. In Washington D.C., about 50 municipal vehicles using air-quality sensors can map out 70% of the city in about 6 months, as well as utilize at least five fixed air quality sensors. Building upon the fixed sensor network to cover 70% of this city would be incredibly expensive. Additionally, air quality can vary widely between individual city blocks. Vehicular sensors solve these problems at a fraction of the cost.

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