Airflow as a Working Mechanism
AIr™ is the patented, drone-agnostic airflow cleaning method that uses a drone’s own rotor wash for waterless, non-contact surface maintenance. It combines aerodynamics, AI-driven control, and autonomous systems to extend aerial vehicles from inspection into useful physical work.
Most drones are used for imaging, inspection, or payload transport. AIr™ focuses on a different capability: using the drone’s inherent rotor downwash as the active working mechanism for cleaning and debris delegation on surfaces where physical contact, liquid use, or manual access are constrained.
By managing drone position, altitude, orientation, and flight path, the method generates targeted airflow interactions that can remove dust, shift loose debris, or direct material toward collection zones — without brushes, water, or additional payload. This is what enables AIr™-equipped drones to remain well below the critical 250-gram regulatory threshold while still performing physical surface work.
Asset managers frequently ask how to scale drone airflow cleaning across large infrastructures like solar arrays. Pictured is an illustrative deployment model based on stated assumptions. Results will vary by drone class, flight altitude, airflow beam width, array spacing, soiling rate, and wind conditions.
AI, Vision & Aerodynamic Control
The AIr™ control stack draws on computational fluid dynamics (CFD), reinforcement learning, and computer vision to manage airflow interactions precisely.
Reinforcement learning is used to refine flight paths and airflow exposure across varying surface geometries and soiling conditions. Field testing in Phoenix, Arizona, demonstrated significant dust removal after a single airflow exposure following three weeks without rain.
Computer vision and real-time sensing help identify soiling levels, surface boundaries, and environmental constraints in flight, enabling dynamic path adjustments without manual intervention. This control-layer focus fits Aerial Agency’s goal of advancing the patented method toward software and platform approaches, while leaving room for proprietary hardware integration.
CFD Analysis
Computational fluid dynamics is used to simulate how rotor wash interacts with different surfaces, panel spacings, debris sizes, and environmental conditions. This supports more consistent positioning, safer pressure management on delicate surfaces such as solar PV anti-reflective coatings or architectural glass, and highly predictable cleaning outcomes across diverse deployments.
Field Validation
Early trials of the AIr™ method included work in the Rajasthan desert in India, with additional development and testing conducted in Chile and the United States. These trials established the practical baseline for airflow cleaning in dusty, access-constrained, and outdoor infrastructure environments.
Related Academic Work
Independent academic studies have since examined drone downwash as a mechanism for PV panel dust removal, corroborating the physical principles of the AIr™ method:
- KFUPM (2022): Study including Cleaning of Photovoltaic Panels Utilizing the Downward Thrust of a Drone (Energies) demonstrated that regular drone downwash flights remove accumulated dust and restore energy output. Tests in Dhahran, Saudi Arabia showed panel current increasing by up to 61.2% under specific horizontal drone movements.
- ETH Zurich / University of Zurich (2024): A Characterization of the Induced Airflow around a Quadrotor (arXiv) provided a validated, computationally lightweight model of far-field rotor downwash. It describes jet structure, tip-to-tip scaling, and inter-rotor flow geometry.
These publications do not predate or replace the AIr™ patent, which was filed in July 2014 with a granted claim for the drone-agnostic airflow cleaning method. However, they demonstrate that drone-generated airflow cleaning has since become a validated subject of independent technical investigation.
Applications
While solar energy remains a central use case, the method scales across multiple industries. View our applications gallery to see AIr™ applied across Energy & Utilities, the Built Environment, Agriculture, and Space & Beyond.