Newcastle City Council
City-Centre Asset Survey — 2022
Inakalum surveyed every asset and public place across Newcastle’s 3.1 km² city centre on foot — over 30,000 datapoints in ten weeks. Ten locally-recruited agents (selected from 50+ applicants), one survey manual, the Inakalum smartphone capture app, and AI analysis of every high-resolution photograph captured to add metadata. Delivered as KML for ingestion directly into NCC’s own GIS.
- Customer
- Newcastle City Council
- Survey window
- Mar – Oct 2022 (10 weeks field survey)
- Area covered
- 3.1 km² city centre
- Total datapoints
- 30,000+
- Field team
- 10 locally-recruited agents (from 50+ applicants)
Over 28,000 assets and 2,000 public places, in ten weeks.
Newcastle demonstrated the walking model at high volume. Ten agents, a tightly-organised survey programme, and an asset taxonomy that covered everything from individual street-lamp columns to parking facilities. The result: a city-centre dataset richer and more current than NCC’s existing records.
Street-lamp columns
Every lamp column geotagged, photographed and categorised. AI image analysis was used to identify which columns carried additional apparatus — CCTV, signage, banners, communications equipment.
Gullies
Drainage gullies captured across the city centre — the dense, easy-to-miss assets that matter for highway flood management and maintenance scheduling.
Road signs
Every traffic and information sign, recorded with category and photographs. Critical for compliance and renewal planning.
Public places
Distinct public places — squares, paved areas, planters, gathering spaces — recorded as polygons. The dataset behind public-realm and accessibility programmes.
Plus 359 manholes, 411 trees and 492 parking facilities — among the 28,000+ assets in the full inventory.
Metadata that scales beyond what a surveyor can record in the field.
The on-foot capture method produced high-resolution photographs of every asset. Inakalum’s AI pipeline then went back through those photographs to add metadata that would have been too time-consuming to record manually.
“The walking survey gave us the raw imagery. The AI pipeline then went through it and identified, in seconds, which lamp columns carried additional apparatus and which didn’t. That’s a classification you can’t reasonably ask a surveyor to do live in the field, but it’s exactly what an asset-management team needs to plan a programme.” — Inakalum project record, October 2022
Standard KML, ready for NCC’s own GIS.
The full asset and public-places dataset was delivered as a KML export — the standard geospatial interchange format every modern GIS platform supports — for ingestion into NCC’s own systems. No custom integration, no proprietary lock-in.
Per-asset records
Every record carried type, GPS position, mandatory photographs and (where AI-analysed) additional category tags. Searchable by NCC officers via the council’s own platform.
Multi-type structured dataset
Point assets, linear assets and polygon assets all delivered in the same KML structure — 28,000+ assets and 2,000+ public places, distinguishable by type and category in the final dataset.
Foundation for follow-on work
The Newcastle dataset established the city-centre baseline that subsequent council programmes could refer back to — the kind of one-time foundation survey that supports asset-management, accessibility and smart-city activity for years.
Same methodology. Different geographies.
Newcastle was the city-centre asset audit at high volume in 2022. Dublin extended the model to multi-year kerbside re-surveys in 2024/25. The methodology, the smartphone capture app and the three-stage QA pipeline are the same; the asset taxonomy and the re-survey cadence change with the brief.
