Real-Time Ocean Prediction via a Grid of Autonomous Self-powered Swarm of Ocean Sensors

Ships are estimated to spend annually an extra $25B worth of fuel because of encountering ocean waves en route. In terms of Greenhouse Gas (GHG) emissions, this extra fuel translates to more than 10% of total emissions by the world’s transportation sector. Part of the reason that waves take this much energy to combat is that the details of incoming waves are usually not known a priori. Therefore, the effort at the bridge (pilothouse) is mainly focused on the ship’s stability as it advances in waves, rather than optimizing fuel consumption in an unpredictable seaway. Our idea is to use a swarm of autonomous self-powered smart ocean sensors (hardware), combined with data-driven-based prediction algorithms already developed (software) in order to be able to predict ocean waves. Each unit of our ocean sensors can actively and autonomously position itself at a designated location for a given time period in order to measure waves’ height, frequency, and direction which are required for our prediction and smart routing/steering algorithm. This idea, when implemented, paves the path for a smart and efficient automatic steering in a seaway, that we estimated can easily save 15% of the cost of current method of advancing in waves. In this chapter, we provide a brief overview of state of the art technologies, challenges, current state of this project, and the future outlook.