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Two Billion Daily Records From Across Globe, Now at Your Finger Tips.

March 30th, 2018

  Data

Leverage a Vast Network of Connected Vehicle Data for a Smarter Tomorrow
 

Imagine having access to powerful information from thousands of vehicles traveling across the globe every day – information that provides you with the capability to make data-driven decisions with every turn. With the collection of real-time and historical data consisting of two billion daily records, Geotab and Assured Telematics are providing you with the power of insight from a global sensor network of vehicles.

Assured Telematics is the first Geotab VAR to take advantage of these datasets by turning them into real-world applications. We want to help our customers incorporate previously non-existent data into more efficient fleet management. So, whether you want information about dangerous driving sections, weather conditions, service centers, or points of interest, Assured Telematics has turned categorized analytics into easy-to-use decision makers.

 

Download Dataset Info Sheet

 

 

Weather data

 

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Hyper Local Temperature

This dataset is generated from Geotab’s GO devices and pulls in temperature data from all vehicles where we’re able to extract the ambient air temperature. Geotab refines this data to remove any anomalous data or outliers from the published dataset. Temperature data is then aggregated to the 7 character geohash level (153m x 153m) every 60 minutes.

 

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Hyper Local Barometric Pressure

This dataset is generated from Geotab’s GO devices and pulls in temperature data from all vehicles where we’re able to extract the ambient air temperature. Geotab refines this data to remove any anomalous data or outliers from the published dataset. Temperature data is then aggregated to the 7 character geohash level (153m x 153m) every 60 minutes.

 

 

Location Analytics

 

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Truck Parking Locations

This dataset provides locations where heavy duty trucks (class 7 and 8) tend to park. Finding a parking location for these massive trucks can sometimes be a difficult task. This dataset provides an aggregation of potential parking locations for these trucks in addition to an hourly distribution of popularity for the parking location. Data from the last 6 months is included on a rolling basis.

 

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Service Centre Metrics

This dataset represents the location of automobile service centers based on aggregate service center visits. In addition to the location of visits, this dataset includes aggregate metrics for average time spent for a repair, frequency of visit to the service center, etc. It should be noted that in this dataset we do not distinguish the type of repair so this should be taken into considering average time spent at the location. It may be for a simple oil change, for an accident repair, or any other service circumstance. Data from the last year is included in the rolling basis.

 

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Fuel Station Metrics

This dataset represents the location of fuel stations (gas, diesel, EV charging stations) and various metrics associated with these stations including average amount of time spent at the station, popular hours, and direction of travel. The data is based on the previous 6 months of data and is updated on a monthly basis.

 

 

Urban Infrastructure

 

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Dangerous Driving Areas

This dataset identifies dangerous areas for driving according to harsh braking and accident level events within a specific area. Each week, a new set of dangerous driving areas is produced and encapsulates 1 year of rolling data (i.e. from the previous month back 1 year). Associated with each dangerous area is a severity score that is based on the frequency of occurrences in the area and the severity of said occurrences.

 

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Search for Parking

This dataset provides an aggregation of areas within a city that experience issues because drivers are circling to locate a parking spot, causing driver frustration and adding to GHG emissions. Cities can use this data to identify problem areas, adjust signage, and more. This dataset represents data for cities that are over 100,000 in population. Data from the last 6 months on a rolling basis.

 

areas of idiling data set

Areas of Idling

This dataset is intended to show a city where its areas of engine idling occur. The dataset breaks idling down by vehicle type, class (where applicable), and fuel (i.e. gas or diesel). The dataset is based on cities with greater than 50,000 population, and is updated monthly and based on a rolling 6-month time interval.

 

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Cell Coverage Dark Spots

This dataset is intended to show a city where there are issues with cellular coverage (regardless of carrier). This dataset is updated on a monthly basis and represents a rolling 6 months of data.

 

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Commercial Vehicle Point of Origin

For cities over 50,000 in population, this dataset shows the point of origin for commercial vehicles coming into the city on a daily basis. The point of origin is taken as the originating location of the vehicle during the morning hours. The same is done for commercial vehicles leaving the city on a daily basis.

 

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Road Impediments

This dataset represents the location and severity of potholes detected in a city. The data is produced on a monthly basis and comprises data from the previous 6 months. In addition to the location of the potholes, through the severity of the pothole detected through the Z-axis on the accelerometer, Geotab also provides a severity score in addition to the average monthly volume over the pothole and a breakdown by class of vehicle traveling over the road impediment.

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