A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Oil Spill Detection using Deep Neural Networks for Cleaning Robot Applications
One of the most prominent environmental challenges of the twenty-first century is ocean contamination. Oil spills are caused by accidents involving oil tankers and drilling rigs. Furthermore, oil spills can have detrimental effects on coastal ecosystems and marine life. In this research, the design of a hybrid flying and floating intelligent drone is proposed for identifying and cleaning oil spills applications in open seas and along shorelines. The proposed robot hybrid design is based on quadrotor technology, which can fly and float on the water surface and has a cleaning mechanism for cleaning small-scale oil spills in the water. The Deep Neural Networks (DNN) is utilized to identify possible oil spills. Several DNN models are developed and examined to determine the best model for the proposed robot application. Finally, based on the proposed design, the 3D-printed prototype uses shaped floating aids carved into their multihull, and other hardware components such as a DC motor, servomotor, controller board, and camera are integrated into the robot.
Oil Spill Detection using Deep Neural Networks for Cleaning Robot Applications
One of the most prominent environmental challenges of the twenty-first century is ocean contamination. Oil spills are caused by accidents involving oil tankers and drilling rigs. Furthermore, oil spills can have detrimental effects on coastal ecosystems and marine life. In this research, the design of a hybrid flying and floating intelligent drone is proposed for identifying and cleaning oil spills applications in open seas and along shorelines. The proposed robot hybrid design is based on quadrotor technology, which can fly and float on the water surface and has a cleaning mechanism for cleaning small-scale oil spills in the water. The Deep Neural Networks (DNN) is utilized to identify possible oil spills. Several DNN models are developed and examined to determine the best model for the proposed robot application. Finally, based on the proposed design, the 3D-printed prototype uses shaped floating aids carved into their multihull, and other hardware components such as a DC motor, servomotor, controller board, and camera are integrated into the robot.
Oil Spill Detection using Deep Neural Networks for Cleaning Robot Applications
Sajid, Hassan (author) / Mubeen, Muhammad (author) / Zarooni, Shaikha Al (author) / Maheshwari, Vishwesh Kumar (author) / Jaradat, Mohammad A. (author) / Khalil, Ahmed (author)
2024-06-03
1275987 byte
Conference paper
Electronic Resource
English
ROBOT FOR OIL SPILL PROTECTION AND OIL SPILL PROTECTION METHOD USING THE SAME
| European Patent Office | 2015
| British Library Conference Proceedings | 1998