In order to assess the airspace risk of unmanned aerial vehicles (UAVs) operating at low altitudes, the third-party risks of UAV urban operations were defined: the risks caused by drones to people on the ground who are not involved in operations and do not profit from operations, and the sources and objects of the risk were clarified. Taking into account the drone crash, noise, on-board camera, and ground environment factors, a UAV urban logistics risk index evaluation model was constructed. First, the UAV image regression model was used to construct a three-dimensional grid, and then a comprehensive third-party risk index model of UAV urban logistics was built based on the casualty and noise risks. Finally, the Southern District of Civil Aviation University of China was selected as an example scene, and surface data were obtained through a field investigation and instrument measurements. Then, the risk of drone operations in the airspace 30–60 m above this area was evaluated. The results showed that the third-party risk was lower when the UAV flying altitude above a building was greater. However, in other areas such as lakes, woods, roads, open spaces, a lower flight altitude had a lower risk. A comparison of the whole airspace showed that the third-party risk was the lowest when the drone operated at an altitude of 30 m. The results also showed that the third-party risk above the lake and greenery was the lowest when on the same plane, followed by the lower risk above the buildings and open squares, with the highest third-party risk above the canteen passage.

The implementation of medical drones can quickly and efficiently expand the coverage range of an area, allowing for a faster response to incidences of out-of-hospital cardiac arrest and improving the subsequent survival rate of such incidences, while promoting sustainable health development goals under the configuration standards for automatic external defibrillators in China. In response to the problem of the selection of locations for medical drone vertiports (for take-off and landing) that are equipped with automatic external defibrillation facilities, a survival function was introduced to establish a model for site selection, with the primary optimization objective of maximizing the average survival rate of patients and taking the operating costs of a system into account. At the same time, considering the constraints of drone phase operation time, energy consumption, coverage range, etc., a medical drone vertiport site selection model was established for emergency cardiac arrest needs. An improved immune algorithm was applied to the model’s calculations and the analysis of the results, using the Jinnan District in Tianjin as an example. The results show that the proposed model and algorithm are feasible and applicable. The Jinnan District in the city of Tianjin requires a total of 24 medical drone vertiports in order to achieve full coverage of an area under the “golden 4-minute” rescue time. When the average survival rate of patients is 0.9, the operation results are deemed optimal, and the average survival rate of patients is 64.06%. Compared to ground ambulances currently used in hospitals, the implementation of medical drones could significantly shorten response time, improve the average survival rate of patients by 41.96%, and effectively improve the existing low survival rate and the accessibility of medical services. The results of this study can provide decision-making support for the planning of automatic external defibrillators in public places and the construction of sustainable and efficient emergency medical service systems.

Check-in service is that passengers need experience flow in airport, and decides the first impression given passengers, so it plays an important role on the ground service quality. Based on the DMAIC model of Six Sigma, this paper applied DMAIC to improve check-in service performance in Hang Zhou Xiao Shan airport. According to DMAIC process, this paper systematically defines five stages of definition, measurement, analysis, improvement and control in check-in service. In each of those phases, the quality management methods and the statistical techniques is used. By employing the management of the Six Sigma DMAIC process, check-in service in Hang Zhou Xiao Shan airport quality improved distinctly, also provides new idea for optimization our airports' ground services.

With the rapid development of the low-altitude economy, the intensive take-offs and landings of Unmanned Aerial Vehicles (UAVs) performing logistics transport tasks in urban areas have introduced significant safety risks. To reduce the likelihood of collisions, logistics operators—such as Meituan, Antwork, and Fengyi—have established fixed departure and arrival air routes above vertiports and designed fixed flight air routes between vertiports to guide UAVs to fly along predefined paths. In the complex and constrained low-altitude urban environment, the design of safe and efficient air routes has undoubtedly become a key enabler for successful operations. This research, grounded in both current theoretical research and real-world logistics UAV operations, defines the concept of UAV logistics air routes and presents a comprehensive description of their structure. A parametric model for one-way round-trip logistics air routes is proposed, along with an air route evaluation model and optimization method. Based on this framework, the research identifies four basic configurations that are commonly adopted for one-way round-trip operations. These configurations can be further improved into two optimized configurations with more balanced performance across multiple metrics. Simulation results reveal that Configuration 1 is only suitable for small-scale transport; as the number of delivery tasks increases, delays grow linearly. When the task volume exceeds 100 operations per 30 min, Configurations 2, 3, and 4 reduce average delay by 88.9%, 89.2%, and 93.3%, respectively, compared with Configuration 1. The research also finds that flight speed along segments and the cruise segment capacity have the most significant influence on delays. Properly increasing these two parameters can lead to a 28.4% reduction in the average delay. The two optimized configurations, derived through further refinement, show better trade-offs between average delay and flight time than any of the fundamental configurations. This research not only provides practical guidance for the planning and design of UAV logistics air routes but also lays a methodological foundation for future developments in UAV scheduling and air route network design.