I feel like I’m tempting fate by writing about snowplowing in the middle of November, but here goes!
As part of and leveraging the OpenCity initiative in Chicago, some data-hounds pulled together a slick interface for viewing real-time snow plow data, and turning this into an estimate of which streets have been plowed.
Each of the city’s snow plows is outfitted with a GPS system. When a storm hits, the plows begin transmitting their location to the city in real-time. The city puts this data online and constantly updates it to power their real-time Plow Tracker map.
We took that location data – where was plow x at time y? – and used it to figure out which streets plows have driven through.
In a city like Chicago, this GIS data offers benefits to the public, politicians and management alike. The ability to understand response times compared to expected levels of service for a given snow event allows for better planning, budgeting and setting policy objectives. But sometimes it is fun to “gamify” real life events too:
One new feature that excites [the developers], mainly for the unforeseen potential it offers, is the snow plowleader-board. It ranks snow plows by the number of traces that have been recorded, which implies the distance they’ve plowed. “I’m all about people rooting for certain plows. We might offer to let people ‘claim’ a plow, name a plow, get updates from that plow. Maybe there could be bets on which will plow the most.”
For a community like Revelstoke, where we live, and others in the interior of BC; snowfalls regularly exceed 15cm in a storm event, and total snowfalls for the season can exceed 400cm, if we were to leverage something like this, the programming behind this software would need to be modified to include the various pieces of equipment used and what each of them does in a shift, sidewalk plows, plow trucks (that might be just sanding), graders, blowers, and loaders. Understanding the workflow of snow removal would change the rules for determining from the many intersecting and parallel GPS tracks, which roads have been plowed, which ones have had windrows removed, or which ones have just had sidewalk clearing completed. Overall, nothing that a decent programmer couldn’t handle, given some direction and parameters.
While complicated, (though not impossible), the real question right now is this: is there value in this transparent snow removal data from a public perspective in a small town? My gut feel is not immediately, in a real-time way like Chicago, but definitely over a season or multiple seasons for determining the level of service response to snow events and the cost associated with this service. To answer the question of value, the next question is: how much is this service worth, (ie how much would a resident be willing to pay to have finer-grain understanding of the amount of snow clearing undertaken, and the efficiency of the system as a whole), and would this allow City council to make better informed policy and budget decisions?
Could these objectives be achieved without fancy software and GPS tracking in every vehicle? Some thoughts on this:
- The potential financial outcomes could be achieved, but likely through a trial and error process, without the added benefit of spatial data and a visual representation for the public and transparency of service in general.
- The ability to measure individual unit performance and reward excellent service would be elusive at best without GPS and GIS integration in a useable app.
- Tracking performance (quality of service) based on complaints and service audits may be possible, but the GIS integration adds a visual element to performance data relating to time, location and the last vehicle passing the location prior to that time.
An important part of decision-making for capital spending is the concept of return on investment. Basically, in this case a positive return on investment would be realized by determining how many years it would take for the following equation to equal zero or be positive:
(The savings from efficiencies found through improved snow removal and clearing practices) – (Purchase and installation costs + annual maintenance costs of the system).
Transparency in government and services is good and should be sought where the data is readily available or easily gathered. In other cases, the technology or means to collect and manage the data just aren’t there yet. GPS tracking of vehicles is used in many municipalities as a means of determining fuel consumption and accountability of vehicle workflow, but turning this basic data into a detailed analysis of snow removal efforts is definitely a huge step forward.
Is there a risk that this information could harm a municipality? Good policies and shift management should minimize any risk from claims against the City. One concern that isn’t mentioned in the Chicago app is privacy – in a small community, it is possible that real-time publicly accessible data could become a privacy concern for the drivers of these vehicles.
At this stage, I think this data would be a nice to have, not a need to have. If nothing else, this is a project that inspires me to consider what is possible with tools such as GPS and GIS that are readily available to municipalities in North America.
What are your thoughts on adding GPS data and GIS technology to the snow plowing arsenal?
All opinions are my own and unless otherwise stated, do not represent those of the City of Revelstoke.