Detecting Microplastics in Seawater with a Novel Optical Sensor Based on Artificial Intelligence Models

Ocean pollution is a significant and growing menace, not only to marine environments, but to the entire planet due to the interconnected nature of biosphere ecosystems. Every day, vast amounts of plastic waste are dumped into the oceans and, more specifically, millions of microplastics endanger marine flora and fauna in the short, medium, and long term. Finding solutions to detect, characterize, and remove these tiny particles is a critical challenge that requires continuous innovation in the coming years to protect seas and oceans. In this context, this paper presents a microplastic detection and identification sensor based on optical principles for particle detection, combined with microscopy and artificial intelligence algorithms for identification, differentiating microplastics from other natural or synthetic particles. An innovative approach enables the inspection of continuous water flows and, while originally designed as a benchtop sensor, minor adaptations can leverage this feature to create a portable version suitable for deployment in real-world scenarios. The sensor requires comprehensive training of detection algorithms, followed by validation tests to optimize efficiency in each deployment, whether at the laboratory scale or in real-world scenarios. The objective is to achieve efficiencies greater than 85–90% in both cases. To this end, two deployments have been carried out (one of which is still ongoing), with the aim of extracting lessons to optimize the sensor and ultimately develop a final version that can aid in microplastic detection and the preservation of marine ecosystems.