OCEAN EXPLORATION USING AR AND VR
Ms. Padma Priya1, Lalith Mohan C2, Haran M3, Priyadharshini M4, Sanjay R5 |
1Assistant professor, Department of Information Technology, SNS College Of Technology, Coimbatore, Tamil Nadu, India |
2,3,4,5 Student, Department of Information Technology, SNS College Of Technology, Coimbatore, Tamil Nadu, India |
Abstract
Exploring the ocean is very difficult process, as it takes some practice to go inside the water atmosphere. This project mainly concentrates on the exploration of the underwater ocean environment and creating a virtual environment from which formation can be derived. It is achieved with the help of some mechanisms which also includes a ROV also called Remotely Operated Vehicles. Remotely Operated Vehicle (ROV) carrying a sealing mechanism attached to it. By using the information obtained, we can give some conclusions regarding many hazards and predict some disasters of the coastal areas. More than 80 percent of the ocean has never been mapped, explored, or even seen by humans. Exploring the ocean is important because it can help us to understand how we are affected and been affected by climatic changes. Also, it can help us in understanding and response to earthquakes, tsunamis and other coastal hazards. Technology used to explore outer space and the ocean ncludes submersibles, remotely operated vehicles (ROVs), satellites, rovers, diving/scuba gears, buoys, mega corers, column samplers and sonar for mapping. Among these Scuba diving is the most often used method to explore the ocean. Nowadays, there are not as many people to do scuba diving for exploring the ocean, and in another method the cost of ROVs is very high to afford. In this project we are creating an ROV using a 360-degree camera and some equipment to build our own ROV. By using this we can send the ROV underwater and capture the species in the ocean and also it is helpful in identifying the coastal hazards by sending signals to the nearby stations. It is very useful for the students who are just beginning to explore the ocean but couldn’t afford such high prices as a beginner.
Keywords: Crop yield prediction, IBM cognos Analytics, dashboards.