Remote NT Housing Repair Triage System Ranks Fault Urgency, Not Tenant Identity

A student team built ReachNT, a prototype system for triaging repair requests in remote Northern Territory public housing, where jobs often wait weeks because of trip costs. The system ranks repairs by urgency, groups nearby communities into shared weekly trips, and explains to tenants why their repair waited. Because no public NT repair dataset exists, the team generated synthetic requests, while geography, house counts and response-time data come from real sources and are labeled accordingly in the demo. The urgency model reaches a ROC-AUC of 0.84 on unseen wording and catches 99.3% of dangerous reports only when combined with human review. Its confidence scores proved poorly calibrated, so the team chose not to show confidence percentages to tenants.