The increasing adoption of UAVs equipped with advanced sensors and GPU-accelerated edge computing has enabled real-time AI-driven applications in domains such as precision agriculture, wildfire monitoring, and environmental conservation. However, the integrated design and orchestration of navigation, sensing, and analytics, together with seamless real-time coordination across drone, edge, and cloud resources, remains a significant challenge. To address these challenges, we propose AeroDaaS, a service-oriented framework that abstracts UAV-based sensing complexities and provides a Drone-as-a-Service (DaaS) model for intelligent decision-making. AeroDaaS offers modular service primitives for on-demand UAV sensing, navigation and analytics as composable microservices, ensuring cross-platform compatibility and scalability across heterogeneous UAV and edge-cloud infrastructures. AeroDaaS also supports plug-and-play scheduling modules, including Waypoint and Analytics schedulers, which enable trajectory optimization and real-time coordination of inference workloads. We implement and evaluate AeroDaaS for six real-world DaaS applications, of which two are evaluated in real-world scenarios and four in simulation. AeroDaaS requires less than 40 lines of code for the applications and has minimal platform overhead of less than 20 ms per frame and about 1 GB memory usage on Orin Nano and a AMD RTX 3090 GPU workstation. These results are promising for AeroDaaS as an efficient, flexible and scalable UAV programming framework for autonomous aerial analytics.

翻译：随着配备先进传感器和GPU加速边缘计算能力的无人机日益普及，实时人工智能驱动应用在精准农业、野火监测和环境保护等领域得以实现。然而，导航、感知与分析的一体化设计与编排，以及跨无人机、边缘与云端资源的无缝实时协同，仍然是重大挑战。为应对这些挑战，我们提出AeroDaaS——一种面向服务的框架，该框架抽象了基于无人机的感知复杂性，并提供用于智能决策的无人机即服务模型。AeroDaaS提供模块化的服务原语，将按需无人机感知、导航与分析作为可组合的微服务，确保跨异构无人机及边缘-云基础设施的平台兼容性与可扩展性。AeroDaaS还支持即插即用调度模块（包括航点调度器与分析调度器），可实现轨迹优化与推理工作负载的实时协同。我们在六个真实场景的DaaS应用中实现并评估了AeroDaaS，其中两个在真实场景评估，四个在仿真环境中评估。AeroDaaS仅需少于40行代码即可部署应用，且在Orin Nano与AMD RTX 3090 GPU工作站上具有低于20毫秒/帧的极小平台开销及约1GB内存占用。这些结果表明AeroDaaS作为一种高效、灵活且可扩展的无人机编程框架，在自主空中分析领域具有广阔前景。