Public Works Inspection: A Low-Cost, Ai-Enhanced Drone Methodology for Remote Communities

Infrastructure inspection is crucial for ensuring the safety and operational efficiency of public works. However, many public agencies in northern Brazil lack the necessary procedures, equipment, and qualified personnel for effective supervision. This study proposes, applies, validates a standardized, cost-effective methodology integrating low-cost drones, consumer-grade cameras, and open-source software with AI-based diagnostic support. By using scale bars instead of expensive RTK GPS systems, the methodology reduces equipment costs to approximately $500, representing up to 80% less than conventional configurations, while achieving sub-centimeter accuracy and detecting structural defects and anomalies. Case studies on urban pavement, bridges, buildings, and dams in Gold Coast, Australia, validate its precision across diverse infrastructure, demonstrating performance comparable to high-cost systems. This accessible framework empowers public agencies, particularly in remote and economically challenged regions, to conduct efficient, safe inspections without financial strain. By democratizing advanced technology, this approach enhances infrastructure management, offering a scalable, replicable model for global adoption in construction oversight.