Marine Internet of Things (M-IoT)

The Marine Internet of Things is a proposal for a suite of sensors and digital devices connected through Internet of Things technology to monitor and model endangered coral reef habitats. Coral reefs provide important environmental services, protecting coastal towns from severe weather, tourism revenue, and essential habitats for other marine flora and fauna. They are also incredibly sensitive to changes in environmental conditions, and monitoring and modelling the health of coral reefs is therefore important to their conservation. The Marine Internet of Things suite includes in-vivo biological sensors, autonomous underwater vehicles, unmanned aerial vehicles, surface buoys, along with in-situ machine learning, reef model integration, and big data analytics connected through Internet of Things technology. Furthermore, data collected from these technologies will not only help researchers conduct a qualitative evaluation of a reef’s health, but also detect illegal fishing, shipping, and management of invasive species and algal outbreaks that degrade reef health. The proposal for the Marine Internet of Things was originally proposed to monitor sensitive and threatened reefs off the coast of Australia, including the Great Barrier Reef and Ningaloo Reef. 

One potential critique for this suite of technologies is the potential for e-waste. As important as more data and information is for research and conservation, researchers themselves need to be conscious of making sure that the environmental impact of conducting research is minimized. 


Data 61. (2017, June 29).“Coral Reef Monitoring and Response.” 


See also:


Yang, J., Wen, J., Jiang, B., Lv, Z. and Sangaiah, A.K., 2018. Marine depth mapping algorithm based on the edge computing in Internet of things. Journal of Parallel and Distributed Computing, 114, pp.95-103; Meera, M. S., and Sethuraman N. Rao. “Comparative analysis of IoT protocols for a marine IoT system.” In 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 2049-2053. IEEE, 2018; Yang, Jiachen, Chang Wang, Qiming Zhao, Bin Jiang, Zhihan Lv, and Arun Kumar Sangaiah. “Marine surveying and mapping system based on Cloud Computing and Internet of Things.” Future Generation Computer Systems 85 (2018): 39-50.


Artificial Intelligence, Biodiversity, Ecological Modelling, Ecological Monitoring, Internet of Things, Monitoring