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Using A. I to Combat Issues with Seaweed (by Akash Pandya)


Using A. I to Combat Issues with Seaweed (by Akash Pandya)

As my family and I flew to the Caribbean island of Antigua several years ago, we were all excited to relax on the beach and enjoy one of the last few weeks before school started. However once at the resort, we were informed of issues with high amounts of sargassum seaweed that had overtaken the shore making it difficult to enjoy the waters on the beach. Furthermore, seaweed has an infamous stench that would make longer stays at the beach quite difficult. My whole family and I were upset by the fact that the beaches were largely unapproachable due to the seaweed issue and we would later find out that this was an issue that not only impacts Antigua but many other coastal areas as well. We observed a similar issue, though a smaller amount, on a recent trip to the Florida east coast. I thought to myself that there must be ways to better track when these patterns of seaweed could arrive at these coastal regions via artificial intelligence. By leveraging these patterns there may be a possibility to both predict potential locations of high accumulation and better combat the problem from negatively impacting the vital tourism business in these areas.

It is believed that the seaweed issue that plagues the Caribbean Islands, Mexico, and even the coasts of the United States stems from the increase in global temperatures and climate change (Source). Historically, many scientists and fishermen agree that sargassum plays a vital role in ocean habitat with well over 100 species of fish and marine animals living around its complex ecosystem (Source). However, the amount has increased substantially in the past ten years, complicating not only tourism but also the fishing industry, where in some instances the sargassum is so thick it prevents boats from leaving port.

There are two ways to potentially combat the seaweed issue. First, artificial intelligence could be implemented to track the patterns of seaweed coming to shores and using this intel to create a timeline of when it may arrive. Second, a scanner could be created to track the amount of seaweed in the ocean. Using this knowledge, the impacted coastal locations would be able to better forecast the scope of the problem and may even be able to prevent the seaweed from reaching the shores and annoying tourists. If a high amount is projected, there is likely little that can be done to stop the accumulation. In this case, the local towns and resorts will benefit from the advanced knowledge to staff cleanup crews and acquire the proper equipment (e.g., in Antigua they had a team with multiple dump trucks and bulldozers to haul it away on a daily basis). However, if it’s a relatively smaller amount, there may be an opportunity to block it (e.g., nets) before it hits the shoreline.

This is a high priority for many Caribbean destinations and other coastal regions that rely on tourism to fund their economy. Recently, the Centre for Resource Management and Environmental Studies (CERMES) from the University of the West Indies (The UWI) held a special hybrid of real-time and virtual instruction at the Charnocks headquarters of the Ministry of Maritime Affairs and the Blue Economy on the challenges and opportunities presented in controlling the spread of sargassum seaweed (Source). During this workshop, participants received instruction on a variety of aspects related to this environmental issue. They discussed the socio-economic challenges caused by sargassum including the cost to clean up, loss of tourism booking / revenue, impact to recreational areas / access to beach, etc. In addition, they talked about the negative impact to the fishing industry where access to boats / necessary equipment was restricted by the buildup of seaweed. Based on a study by Hazel A. Oxenford and Patrick McConney, CERMES (Source), areas with significant accumulation may experience up to 30-50% less harvest. The workshop also talked about the structure of the sargassum, its potential opportunities, and ways to manage confirmed sightings. For example, the seaweed can be applied to several uses including bioplastics, agricultural fertilizers, building materials, etc. This is an area were better artificial intelligence can both provide advance guidance on what coastal areas will be impacted and the potential degree of accumulation.

This is just one of several examples of local communities taking action. By implementing artificial intelligence the coastal areas could better combat the seaweed issue, aid the local economy, and allow for a better tourism experience.

Akash Pandya

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