Abstract: Cleaning systems proposed in the art have technical construct limitations in the cleaning mechanisms used, which leads to a lower ratio of power consumed to area cleaned, directly affecting the cleaning efficiency. Thus, an Unmanned Aerial Vehicle (UAV) Propelled Autonomous Multiplane Cleaning System (UPAMCS) is disclosed. An UAV and Mopping Interface Mechanism (UAV-MIM) connects a UAV to one or more mopping systems comprising an epicyclic gear driven moppers with no additional power devices used. A maneuvering mechanism disclosed enables the UAV to propel the mopping systems to reach any geometric shape or inclination. The UPAMCS provides cost, time, and power efficient surface cleaning. The UPAMCS is also equipped with vision cameras and LiDAR for guidance during landing and crawling over surfaces along with additional surface defect detection by processing the captured images.

Abstract: Current inspection processes employed for pipeline networks data acquisition aided with manually locating and recording defects/observations, thus leading labor intensive, prone to error and a time-consuming task thereby resulting in process inefficiencies. Embodiments of the present disclosure provide systems and methods for that leverage artificial intelligence/machine learning models and image processing techniques to automate log and data processing, reports and insights generation thereby reduce dependency on manual analysis, improve annual productivity of survey meterage and bring in process and cost efficiencies into overall asset health management for utilities, thereby enhancing accuracy in defect identification, analysis, classification thereof.

Abstract: Current inspection processes employed for pipeline networks data acquisition aided with manually locating and recording defects/observations, thus leading labor intensive, prone to error and a time-consuming task thereby resulting in process inefficiencies. Embodiments of the present disclosure provide systems and methods for that leverage artificial intelligence/machine learning models and image processing techniques to automate log and data processing, reports and insights generation thereby reduce dependency on manual analysis, improve annual productivity of survey meterage and bring in process and cost efficiencies into overall asset health management for utilities, thereby enhancing accuracy in defect identification, analysis, classification thereof.