Session: SYMP 4-3: Adaptive Aerospace Systems
Paper Number: 140435
140435 - Uav Assisted Sensor Deployment for Infrastructure Monitoring Using Video Streaming
The maintenance and monitoring of civil infrastructure plays a pivotal role in guaranteeing the safety, longevity, and operational efficacy of crucial societal assets. Traditionally, structural health monitoring (SHM) has depended on a combination of manual inspections and the deployment of sensors by on-site work crews. Although these methods have proven effective to a degree, they are encumbered by significant drawbacks, such as the requirement for specialized access equipment, extensive time investments, high susceptibility to human error, and a notable lack of real-time insight into the infrastructure's condition. The aftermath of natural and man-made disasters further exacerbates these challenges, demanding rapid yet safe assessments that are frequently hampered by the prevailing hazardous conditions.
In response to these limitations, this paper proposes the utilization of unmanned aerial vehicles (UAVs), specifically hexacopter drones for this case, as a means to enhance and streamline the process of sensor deployment across various civil infrastructure types. Hexacopter drones, characterized by their six rotors, offer more stability, increased lifting capabilities, and improved flight control compared to their quadcopter counterparts. These attributes make them particularly suited for the precise and reliable placement of sensors, even in environments that are challenging or risky for human inspectors to access. Moreover, the integration of active video streaming technology within this UAV-assisted sensor deployment system enables the real-time, remote monitoring of the deployment and retrieval processes. The platform’s video streaming system is equipped with a lightweight kc04 camera, optimized for drone flight, which delivers live footage at 700TVL resolution. This camera system enables the drone to wirelessly transmit its point of view (POV) over distances of up to 3000 meters. The camera’s broad fisheye perspective enhances the pilot’s spatial awareness, especially during complex deployment tasks. This capability not only boosts the efficiency and accuracy of data collection but also diminishes most of the hazards associated with traditional manual inspection methods.
The deployment system on the drone incorporates an electro-permanent magnet (EPM) mechanism for efficient deployment and retrieval. EPMs are favorable in this application as they only require minimal power to change the state of magnetization without the need to consume power otherwise. Both the sensor packages and deployment UAV are equipped with EPMs for ease of mounting and an added measure of safety. Additionally, The EPMs are integrated within a lightweight 3D-printed frame constructed from polylactic acid (PLA). The frame is designed to guide the sensor package into the docking EPM, further streamlining the retrieval process. Miniature cameras are strategically placed on the frame of the UAV to optically validate the interaction between the package, UAV, and the surrounding environment.
The implementation of hexacopter drones for the purpose of SHM addresses several critical gaps in the current methodology for civil infrastructure monitoring. First, it reduces the time and physical risk involved in deploying sensors, particularly in locations that are either difficult to reach or present safety concerns. Second, it offers a level of real-time visibility into the status of the infrastructure, thereby facilitating more timely and informed decision-making in both maintenance planning and emergency response actions. By combining the enhanced operational capabilities of these drones with real-time video streaming, a comprehensive approach meant to advance the field of civil infrastructure health monitoring is presented.
Presenting Author: Joud N. Satme University of South Carolina
Presenting Author Biography: Jude Satme is a mechanical engineering graduate research assistant at the University of South Carolina with an undergraduate degree in electrical engineering. Satme's research expertise lies in the field of signal processing and UAV-deployable sensing platforms. His current research focuses on edge computing systems and online machine learning state estimation for high-rate dynamic applications.
Authors:
Joud N. SatmeRyan Yount
Nikita Goujevskii
Luke Jannazzo
Austin R. J. Downey
Uav Assisted Sensor Deployment for Infrastructure Monitoring Using Video Streaming
Paper Type
Technical Paper Publication