AeroDaaS: A Programmable Drones-as-a-Service Platform for Intelligent Aerial Systems
Kautuk Astu, Suman Raj, Priyanshu Pansari, Yogesh Simmhan

TL;DR
AeroDaaS is a flexible, scalable platform that simplifies programming UAVs for real-time AI applications by providing modular, service-oriented components for sensing, navigation, and analytics across heterogeneous systems.
Contribution
It introduces AeroDaaS, a novel service-oriented framework that abstracts UAV complexities and enables real-time coordination and scalability for aerial AI applications.
Findings
Requires less than 40 lines of code for applications
Minimal platform overhead of less than 20 ms per frame
Supports real-world and simulated UAV applications
Abstract
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…
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Taxonomy
TopicsUAV Applications and Optimization · Advanced Neural Network Applications · Robotics and Sensor-Based Localization
