Geomatic Technologies Queensland Main Roads Streetlight Audit

Brisbane, Australia 2005 – Geomatic Technologies (GT), has completed a data capture project on behalf of Ergon Energy, to survey all streetlights located on main roads throughout the Queensland distribution network.

The project required GT to mobilize a fleet of 2WD mapping vehicles fitted with the company’s Asset Inspection and Mapping System (AIMS). The configuration comprised of differential GPS, data capture software and QA tools in order to coordinate and describe the road lighting along highways and major residential streets in Queensland. Over 40,000 streetlights were visited and data supplied to the Ergon asset management and GIS division included;

1. Powerpole coordinate
2. Powerpole street address
3. Powerpole ID & label
4. Streetlight type
5. Streetlight wattage
6. Streetlight orientation
7. Streetlight bracket type
8. Streetlight control type
9. Streetlight model
10. Streetlight manufacturer
11. Streetlight manufacture date

A number of local features at each streetlight were also recorded to support the Ergon maintenance programme through special areas such as pedestrian crossings.

At the commencement of the project GT were advised that there were expected to be up to 40 different street lights installed throughout Queensland. However the GT teams soon discovered an additional 60 light types that had not previously been recorded. The AIMS data capture software was configured on a weekly basis during the first months of the project to accommodate the variety of new infrastructure that was discovered.

Following a staff induction and OHS programme managed by Ergon, fieldwork was completed over an eight month timeframe, during which over 80 towns were visited across a distribution network of over 500,000 sq miles. The GT survey teams experienced temperatures in outback Queensland of over 110°F while also experiencing tropical storms along the Queensland Pacific coastline.

The information captured by the project is being used within Ergon as the critical dataset supporting their major road patrol maintenance programme.

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