Fuel Spill Monitoring for Fishing Smack using Raspberry Pi
Manisha N L1, Silpa P A2
1Manisha N L*, Student, Department of Electronics and Communication Engineering, Sahrdaya College of Engineering and Technology, Kodakara, India.
2Dr. Silpa P A, Assistant Professor, Department of Electronics and Communication Engineering, Sahrdaya College of Engineering and Technology, Kodakara, India.
Manuscript received on June 25, 2021. | Revised Manuscript received on July 02, 2021. | Manuscript published on July 30, 2021. | PP: 75-80 | Volume-10 Issue-2, July 2021. | Retrieval Number: 100.1/ijrte.B61700710221| DOI: 10.35940/ijrte.B6170.0710221
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Fuel spill monitoring for fishing smacks is a live fuel leak detector that can alert the vessel’s crew and captain about the leakage by using a web camera connected to a Raspberry Pi. The fuel spill was resolved using the Convolution Neural Network (CNN). Also, the Coast Guard and the Environmental Protection Agency were informed about the location of the oil discharge through telegrams. Here, a picture of the spill, as well as its latitude and longitude, a live Google map location, and a no spill picture with a GPS location whenever the spillage stops, will be shared. As a result, the team could take immediate action without delay. This spill detection system is linked to an accident detection system. Hence, we can safeguard fishing vessels and marine activities without any harm to human kind, as well as to the living beings in the sea.
Keywords: Convolution Neural Network, Machine Learning, Oil Spill, Raspberry Pi.