AI to improve accuracy of ocean predictions and advisories issued by INCOIS
The Hyderabad-based INCOIS signed an MoU with Spotflock Technologies Private Limited with an aim to develop a collaborative framework and deep technology applications in the domains of ocean science and services
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INCOIS was established in 1999 under the Ministry of Earth Sciences (MoES). (file)Indian National Center for Ocean Information Services (INCOIS), Hyderabad will increase its use of advanced tools like Artificial Intelligence (AI), and Machine Learning (ML) for improving ocean advisories and services, a source said.
Established in 1999 under the Ministry of Earth Sciences (MoES), INCOIS provides information and advisory on potential fishing zones, issues tsunami early warnings and advisories regarding algal bloom, storm surges, coral bleaching in the Indian Ocean region covering the Bay of Bengal and the Arabian Sea.
Recently, the Hyderabad-based institution signed a memorandum of understanding (MoU) with Spotflock Technologies Private Limited, which works in deep technology having its product engineering and innovation wing in the Telangana capital.
The collaboration aims to investigate the possibility of pooling their capabilities and resources to aid in the development of a collaborative framework and deep technology applications in the domains of ocean science and services.
Sridhar Seshadri, CEO and co-founder of the US-headquartered Spotflock, said: “We will work closely with INCOIS by adopting AI-driven early warning systems so that authorities can expediently react and confine environmental pollution.”
The technological intervention will mainly be used in classifying fish species and tracking their movement along the Indian Ocean, identifying potential fishing zones and providing relevant information, studying the impact of climate change on species population, tracking migration routes, and detection of ocean pollution, the officials said.
The officials also noted that the AI-ML technologies will also be applied in the estimation of seafloor depth and in the prediction of wave conditions.
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