Sitting in hotel lobbies, eating breakfast or dinner, or discussing on shorelines from Japan to Hawaii to California to Northern Ireland, swimmers are often looking at their apps and talking about weather, currents, and wind data that they see on their smartphones.
They look at the data in the morning when they first wake up. They look at the data during the day – and many times throughout the evening whether it is in the Tsugaru Channel in Japan, the Molokai Channel in Hawaii, the Catalina Channel in California, the North Channel between Northern Ireland and Scotland, and many other places in between.
It is so frustrating.
Channel swimmers seem to live on those predictions, always hoping for the most tranquil, favorable conditions. But, ultimately, they often face worse conditions than predicted. However, these apps – based on data captured from marine buoys often located tens (or hundreds) of kilometers distant from the actual course of the swimmers – provides the best available information.
Swimmers are usually visiting the area for the first time in their lives and their smartphone apps are what they have. They do not have the experience of fishermen and boaters who live in the area and cross or work in those same waterways, almost on a daily basis. They spend years training for their channel crossings. They spend thousands or tens of thousands of dollars (or pounds or euro or yen or real) to realize their dreams of a successful marathon swim.


During this age of Artificial Intelligence, physical oceanographer Kim Martini, PhD and science media specialist Virginia Schutte,PhD, are creating something better and more accurate – at least initially for coastal waters.
Dr. Martini [shown above on left] and Dr. Schutte [shown above on right] co-founded Tini Scientific that will change the game of guessing by ocean swimmers – and many others involved in the Blue Economy. They explain, “Smartwatches contain the same sensors that scientists use to study the ocean. It’s easier to communicate with them than with oceanographic tech. And they cost thousands less. All we need is an app to tap into these capabilities.
We are creating that app. We are also testing smartwatch sensors against commercial alternatives to verify smartwatch suitability for coastal ocean research. Building software around existing hardware leverages watches’ familiar interface, instant connectivity, and built-in accessibility, all of which make for effortless data collection and sharing. We love collaborating with scientists and outdoor enthusiasts who need meaningful data to better understand and get into the ocean.”
Essentially, they are transforming smartwatches worn by surfers and swimmers into powerful, low-cost tools for environmental monitoring.
They are building an app that turns smart watches worn by ocean goers into smart sensors. They are crowdsourcing the world’s largest coastal data set – captured by the watch on your wrist – to build a hyperlocal, massive coastal ocean database.
“Their experience and their vision is a very welcomed addition to ocean swimming. We absolutely need this data,” said Steven Munatones. “I train in Huntington Beach where I can see Catalina Island every day – when it is not foggy or clouded over. I only know exactly the conditions when I am in the water, training parallel to the coast. Having access to all the data captured by the smartphones of surfers and windsurfers who are in the same waters would be such wonderful information to access. And I have the satisfaction that the Garmin watch that I use also contributes to this valuablecoastal data set.“
Dr. Martini and Dr. Schutte’s goal is to create an app and observation network that will set the stage for partnerships that include co-developing new and experimental tools to meet the needs of science and society – and benefit all those involved in the Blue Economy.
We greatly look forward to the outcome of their research and hard work.
For more information, visit www.tiniscientific.com.
To get a small flavor of what Dr. Martini and Dr. Schutte are up to, click here.

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