Regular building inspections are a key means of identifying defects before getting worse or causing a building failure. As a tool for building condition inspections, Unmanned Aerial Vehicles (UAVs) or drones offer considerable potential allowing especially high-rise buildings to be visually assessed with economic and risk-related benefits. One of the critical problems encountered in automating the system is that the whole process involves a very complicated and significant amount of computational tasks, such as UAV control, localisation, image acquisition and abnormality analysis using machine learning techniques. Distributed software agents interact and collaborate each other in complicated systems and improve the reliability, availability and scalability. This research introduces a ubiquitous concept of software-agents to a drone-based building inspection system that is applied to crack-detection on concrete surfaces. The architecture and new features of the proposed system will be discussed.