Optimal Detection of Oil Contamination at Sea by the FPSO Algorithm

Abstract

Leakage of oil from pipelines and oil tankers into seas and oceans is ecologically important and can have significant social and economic impacts on the environment. An early detection of deliberate or accidental oil spills can reduce serious hazards that may threaten coastal residents and help identify pollutants. Iran has been surrounded by seas from the north and the south and they provide us with valuable natural resources, in general, and oil reserves in particular. Besides, the seas are where oil is mined and oil tankers pass. Therefore, protecting the seas against oil contamination is essential. Due to the vastness of seas and the need for early detection of contamination source, modern methods must be employed to prevent excessive environmental damage. Unfortunately, a few studies have been conducted on it to date. In the present study, a number of robots controlled by the Fuzzy Particle Swarm Optimization (FPSO) algorithm were used to discover the source of contamination. In this paper a z coefficient was added to FPSO algorithm derived from fuzzy logic and contamination condition. This z coefficient informed the velocity of particles in a PSO model. We showed that using a fuzzy logic can improve the treatment of standard PSO algorithm in detecting oil contamination.