This is how IoT is going to help in advancing the study of the Ocean
Oceans produce over 200 billion pounds of seafood every year and are an important source of livelihood for many people. They are also important ecologically as they cover a vast portion of our planet and long term changes of oceans have a direct impact on human civilization making them an important research area.
Can the Internet of Things help in advancing the study of the ocean? Well, an interesting new project is being carried out by Gloucester Innovation, a technology and business consulting firm focused on IoT and the Lobster Foundation of Massachusetts, whose members fish out of 52 ports using over 300,000 traps off the state’s 192 miles of coastline. This large number of lobster traps could be used to collect a wealth of information about the lobster habitat as well as various parameters about ocean health.
Lobsternet’s goal is to understand more about the lobster habitat as well to monitor the ocean’s health with parameters such as pH level, temperature and biological contaminants. The project also received a grant funding from the Massachusetts Seaport Economic Council. The grant will support the development of more than 200 ocean sensing devices, called ePods that will be nested within lobster pots. Gloucester Innovation claims that earlier sensors deployed in the oceans for research use satellite technology to transmit data which are expensive and the sensor recovery from the ocean beds happen only in months.
Lobsternet plans to use Sigfox network instead and develop cost-effective, small and highly power efficient sensors which can be attached to the lobster traps without hampering their activity. This is due to the fact that devices operating on Sigfox’s low power, wide area network can provide intermittent signals on long distances in a highly power efficient way. Signals can extend up to 20 miles offshore, so the data from the sensors is available daily as the lobster traps are pulled out of the water. The sensors transmit data automatically when they are pulled to the surface. This gives a large amount of spatial data as each lobster trap has a sensor attached and the data is available on a much frequent basis as compared to the earlier method. The data communicated wirelessly on the Sigfox network by the sensors is stored in the ‘marine data cloud’ for further analysis. Predictive analytics could be used to improve the productivity or efficiency of the lobstermen and track ocean changes impacting lobster populations, movements and habitats.
The pilot project is supposed to be launched in US summer 2019 and is expected to generate a vast amount of data points across trap location off the course of Massachusetts. Currently only targeting the lobster industry in Massachusetts, the solution can be used by various authorities to track different ocean parameters. The lobster traps act as sensor units while the boats of the fishermen act as communication hubs. The lobster traps could be replaced by something else depending on the local fishing industries. The solution seems to be a feasible, cost-effective, scalable way for ubiquitous sensing of the ocean parameters which can be used to create a marine data service. It also has enormous scope in predictive analytics based on the data and it is up to the developer’s imagination to create applications based on it.
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