The Internet of Things (IoT) is a concept first discussed by entrepreneur Kevin Ashton in 1999 when he was developing radio frequency ID (RFID) tags as a method for tracking inventory. The IoT concept is based on the ever-increasing number of objects in the physical world which are equipped with computing power, sensors, actuators, and – most importantly - network connectivity, and the fact that these objects, while running their own proprietary operating systems and carrying out their own specific design functions, are also interoperable within the global Internet ecosystem. For example, a smartphone carried by a human being, a Coca-Cola vending machine with a wireless connection back to the vending distributor’s intranet, and an Aquabotix research ROV feeding data back to a university Web server are all wildly different objects, but all of them are part of the Internet of Things. Researchers estimate that by 2020, there will be almost 50 billion distinct objects in the IoT infrastructure.
The IoT is one of those concepts that are incredibly interesting, and which have the potential to also become incredibly important. Right now, that Coca-Cola vending machine and the Aquabotix ROV and the smartphone don’t have a lot to say to one another. Some pundits are fond of imagining scenarios wherein the researcher operating the ROV parks the vehicle and walks home, and some yet-to-be-developed algorithm correlates the powered-off status on the ROV, her geographic location from the smartphone, historical data about ROV researcher thirstiness in the post-work environment, and the proximity of the Coke machine to cause a message to popup on her phone suggesting that she might want to stop by the vending machine and grab a Coke.
That’s a neat idea in theory (although if my smartphone starts giving me unsolicited advice to buy soda, I’m going to turn it off and go live in the woods) but in real life the practical applications of the IoT are likely to be a lot bigger than boosting retail point-of-sale numbers. If the history of technology is any guide (hint: it is), a lot of those applications are not going to be known in advance. We’re going to find them as we go along, as new data produces new insights. Those insights will make new applications for the data possible. In the underwater world, it is very likely that the relationship between ROVs and the IoT are an undiscovered country – we don’t yet know what we don’t know. We’re going to have to find out.
The main driver of that discovery process, for some time to come, is likely to be the collection of all sorts of data. One of the key selling points of ROVs for underwater work is that they make the collection of information about the underwater world possible, sometimes for the first time, and also remarkably inexpensive. This combination of newly-possible data acquisition, and the newfound cheapness of that same acquisition, is going to be a driver of all sorts of data collection which was not even imagined ten or twenty years ago. For example, sonar mapping of a harbor is something that used to cost [hundreds of thousands of dollars – my out-of-my-butt estimate] and require [millions of dollars – similarly a guess] worth of equipment to do it, and so it was something done at an interval of years or decades (if ever) and only at sites of critical importance. Today that sonar mapping can be done for thousands of dollars, with ROVs that fit easily within the budget of a small commercial marina – and so vastly more harbor mapping is being done. The same new horizons are opening up in environmental data, data on fisheries, temperature and sediment data around coastal or riparian industrial sites, and a hundred other types of information.
As that data comes in, the people who earn their living in these industries and areas are likely to find amazing new ways to use the information – and those applications will in turn feed more data into the system in a virtuous cycle. This discovery process is likely to be an extremely exciting time for people in underwater industries – and ROVs are likely to be one of the foremost tools used in the discovery process.