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Under new IMO regulations, shipping companies must regularly report fuel data from 2019. Therefore, ships must regularly measure and report data on companies using methods such as tank measurements, flow meters or oil receipts. When a ship is operating at sea, measuring and monitoring the fuel level in the ship's tank is a very difficult and inaccurate problem because the ship is always tilted strongly in different sea conditions. Due to the strong tilting and shaking conditions, the fuel level in the tank is always fluctuating and unstable. This paper focuses on studying the use of Kalman algorithm to filter noise when measuring fuel level to get accurate data on fuel level in the tank in real time. From there it is possible to accurately calculate the amount of fuel remaining in the tanks on board and automatically report the fuel data to the company in real time under different operating conditions of the new IMO ships in terms of fuel consumption. Shipping companies must regularly report ship fuel data from November 1, 2021. Therefore, ships must regularly measure and report data on companies using methods such as tank measurements, flow meters or oil receipts. When a ship is operating at sea, measuring and monitoring the fuel level in the ship's tank is a very difficult and inaccurate problem because the ship is always tilted strongly in different windy conditions. Due to the strong tilting and shaking conditions, the fuel level in the tank is always fluctuating and unstable. This paper focuses on studying the use of Kalman to filter noise when measuring fuel level to get accurate data of fuel level in the tank in real time. From there, it is possible to accurately calculate the amount of fuel remaining in the tanks on board and automatically continuously report fuel data to the company in real time under different operating conditions of the ship.