FAME Goes Mobile with Colorado Field Inventory
The Odyssey Unfolds
We set forth to help Canon City with their data collection problem, hoping to extend the
solution throughout the corporation. We soon realized that we did not fully understand
their problem or goals and began to more pointedly question the staff requests.
Navigation Point: Don’t assume you understand a mobility problem based only on how
end users or managers explain it to you. Especially don’t assume you understand the
ultimate goal upon first hearing it.
Why did they need to get latitude/longitude points into our system? Canon City field staff
were required as a result of our reengineering project to enter new facilities designs into
the system. Typically these designs were for line extensions. Often the lines to be
extended were not in the system. GPS measurements were being taken to provide a
correct starting point for the designs. Most locations were in rugged terrain, with 40 acre
lots, few roads and even fewer mapped landmarks.
What would a collected point location mean in the AM/FM system? A point could be a
pole, a modeled object in our system. However, a point location could also be used to
locate transformers or other devices which might hang on a pole. Two points could
define a span of conductor. Further, points could define the location of components and
spans in an underground system. Ultimately points could be used to describe many
more parts of the electrical system, ranging from transmission lines to individual meter
locations. Thus we reached the first major issue in our data collection plan. What
objects would be appropriate for Canon City staff to collect? When do individual data
collection efforts begin to fall outside the centrally planned scope of the AM/FM system?
Navigation Point: Providing field data collection capabilities raises the issue of local
responsibility for data maintenance and scope. Be prepared to wade in.
How many points did they need to collect? Once we heard that lines were not in the
system, we became curious as to the extent of this problem. It often turns out to be
difficult to estimate the quantity of something left undone. We worked with the Canon
City managers to estimate that half of the district was unmapped. They generally knew
the location and extent of unmapped areas and could provide some data concerning
number of transformers.
Why were the collected points wrong or unsuitable? This was the question that kicked
off our pilot. Trying to answer the question became confusing. We looked at all issues
associated with importing latitude/longitude into our system. We looked at the
theoretical accuracy of consumer grade GPS systems before and after selective
availability was turned off. We watched the staff collect data. We theorized that some
degree of finer resolution in data collection was needed. All we really knew was that
some points created from GPS measurements fell on the wrong side of the street in our
AM/FM system.
The Odyssey Gets a Project Plan—And Funding
Asking all those pesky questions gave us issues we could summarize for UtiliCorp
energy delivery management. The primary problem was not that Canon City staff
needed methodology and tools to collect field data, but that they needed to do a lot of
field data collection because half the district was unmapped. Given that the press of
rapid growth in the area had caused the problem, it was probably unrealistic to expect
the existing staff to work even harder to learn a new set of skills for data collection while
muddling along with inadequate maps. Energy delivery management tasked the AM/FM
team with outsourcing the field survey and developing an efficient methodology for
getting the collected data into the system.
At the point of planning a field data collection procurement, we worked with energy
delivery management to resolve organizational issues. We discovered that the Canon
City staff desired to collect substantially more data than was deemed in scope by energy
delivery management. The equation “points equals poles” became a problem. Scope of
the AM/FM project had never allowed for collection or maintenance of data on individual
poles. Canon City staff strongly preferred to collect and maintain individual pole
locations and data. The compromise reached was that poles with transformers or other
devices hanging on them would be collected, transformer station numbers attached to
poles would be collected, poles indicating significant changes in direction would be
collected.
Once it was determined which objects were to be collected, we begin to work on the
data structure of the collection software. We wanted to create an efficient way to load
field data into our Smallworld AM/FM system. Many of our electrical objects had
complex parent-child relationships. Our first idea was to duplicate these relationships in
the field data collection software, in order to produce output identical to our data
structure. However, configuration of vendor-supplied software to duplicate our structure
proved to be time consuming and difficult. UtiliCorp had a desire for a data loader
product that would be flexible and easily used for all our electrical objects. We ended up
working with yet another vendor to configure a data loader which would take ascii files
exported from the data collection software and load them correctly into FAME.
By the time everyone’s piece of the effort was completed, summer was almost over. Our
initial data collection efforts were to take place in the southern Colorado Rockies at 8000
feet. We had authorized 28 days of field data collection. We pressed hard to begin the
data collection efforts. We attempted to run sample data through the field collection
software and into the loader, but the field vendor had difficulty producing sample data.
We went ahead to the field anyway.
Navigation Point: Always allow time to test the collection and load process before going
to the field, no matter how much snow is predicted. There will be problems with the data
structure, you will not be able to see all of the problems without running a bunch of data
through your processes, and you must attempt to solve all the problems before collecting
mountains of real data.
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