Detection, Localization and Analysis of Oil Spills in Water Through Wireless Thermal Imaging and Spectrometer Based Intelligent System

In this study, a marine robotic system is designed to locate and to quantify the surface water pollution in lakes and ponds with the consideration of the influences of neighboring buildings and trees. The proposed system consists of an aerial robot and a marine robot, which are actuated by pattern recognition at the base station with safe path planning. In the designed system,on quadrotor a Forward Looking Infra Red (FLIR) thermal imaging camera is employed to spot oil spills following a neural network method, while a wireless digital camera is used to identify the apropos path by imparting edge detection techniques. The surrounding buildings and trees dysfunction the digital camera’s reflectivity, thereby disparate from optimal path planning. To dwindle the experimental impediment, the Voronoi algorithm is employed by fractionating the experiment’s domain into small sub-sections. After that, Dijkstra’s algorithm is considered to assure the optimal path planning from the starting point to the target. Fuzzy logic is introduced to direct boats towards the target. Global positioning system (GPS), sonar and navigation sensors based boat follow the trajectory defined by the aerial robot towards target point and take samples for quantification test through the spectrometer. These results then sent to the base station for pattern recognition using neural networks. Such systems can efficiently and effectively navigate the water pollution problems as disaster response.