Case Study – The City of Edmonton grows count program and cuts costs by 54%

The City of Edmonton, Alberta, Canada (Pop. 1M+) was tasked with updating their Transportation Master Plan to encourage multi-modal transportation and move away from drive-alone vehicles. The Plan called for additional performance measurements to benchmark improvements, which included longer Turning Movement Counts; Trails, Paths and Walkway Counts; Arterial Classification counts; and Generational Counts in focus neighborhoods.

Transportation Services Department

The Edmonton Transportation Services Department has an annual traffic count program consisting of approximately 300 Turning Movement Counts between April and October. Historically, the City used manual counters to collect their Turning Movement Counts. The Transportation Master Plan update could not come at the cost of the Department’s existing annual count program.

“Miovision certainly helped us achieve more with our count program. Less costs, longer count periods with a higher degree of accuracy have contributed to enhancing our data collection programs. Now if it can be seen, it is counted!!”‘Brian Murphy, Director of Transportation Services, City of Edmonton


The City of Edmonton was presented with three major challenges to the increase of study types and study lengths required by the Transportation Master Plan.

  • The Transportation Department was tasked with reducing operating costs in 2010 without affecting the work required by the Transportation Master Plan. A result, the city needed to generate more data for less money without sacrificing the quality of the data.
  • The city needed to collect longer turning movement counts and new study types without exceeding the total number of hours a seasonal employee can work in a week, creating a significant staffing strain to complete the work required by the Transportation Master Plan.
  • The city needed to collect volume data on trails, paths and walkways to measure current versus future use of the city’s active transportation passageways, yet had no existing method to collect this data.
Study Type Annual Cost Comparison graph

Figure 1: Cost comparison by study type between using manual counters or Miovision’s Video Collection Unit.


Based on positive experiences conducting a number of studies in 2009 with two Miovision units, the City of Edmonton decided to adopt Miovision for their entire count program and purchase four more Video Collection Units to accomplish the counts for the Transportation Master Plan.

Using Miovision’s system to automate traffic counts, Edmonton realized a savings of $150,940, which was achieved in two ways:

  • One Video Collection Unit could affectively replace two manual counters and produce data with an average accuracy rate of 95%.
  • Miovision’s hourly processing rate was lower than labor wages, allowing the city to easily accommodate longer counts and new study types. See figure 1.
Annual Study Costs graph

Figure 2: Cost comparison by study type between using manual counters or Miovision’s Video Collection Unit.

The City of Edmonton realized a 54% savings by automating their traffic collection with Miovision. This allowed the city to maintain their current turning movement count program, count for longer periods and add new study types with a significant reduction to the bottom line. See figure 2.

The city reduced labor with Miovision by sending one Transportation Technician to multiple count sites per day to deploy Video Collection Units, then upload the videos for processing. Using one staff member for multiple studies eliminated many of the labor hours associated with manual count collection. See figure 3.


*Collecting 4,860hrs of data required much less labor with Miovision compared to manual counting.

Finally, the City of Edmonton chose to collect volume data on bicycles and pedestrians throughout the city’s active transportation system using Miovision’s pedestrian and bicycle classifying feature. The city could receive accurate classification and volume for each mode of transportation, and a video record of each study. The data and video results established a baseline measurement to be used in the evaluation of future active transportation adoption.

Annual Labour Required graph

Figure 3: The total labor hours required for manual traffic count collection including travel time compared to the total labor hours required to travel, deploy a Video Collection Unit, and upload videos for processing.


Utilizing Miovision’s system to automate traffic data collection, the City of Edmonton was able to overcome all of their data collection challenges. By implementing the automated technology across their entire count program, the city was able to:
  • Reduce the Transportation Master Plan data collection operating costs by 54%
  • Maintain their Turning Movement Count program plus collect the additional Transportation Master Plan studies
  • Eliminate staffing strain and collect all traffic studies with minimal labor requirements
  • Provide a solution to collect a brand new study type

The partnership between the City of Edmonton and Miovision Technologies contributed to a cost and labor savings for Edmonton’s Transportation Master Plan. This allowed the city to collect data more quickly and easily, helping them reach their “Transform Edmonton” goals.