Plug and play monitoring - developing novel solutions for marine observations with divers as citizen scientists

Rationale:
Massive deployments of low-cost autonomous sensors can deliver large amounts of high-quality data and provide novel solutions for marine monitoring. This can help overcome limitations of remote sensing (e.g. inability to "see" below clouds or sea surface) and reduce costs. One such approach that has gained recent traction is "citizen science" where interested laypeople collect data on smart phones, tablets, inexpensive sensors (tinytags) or SCUBA divers' computers.
However, it is often difficult to collate this information due to location, access, data formats, missing data quality control, and there is a lack of tools for contextual visualisation (e.g. coupled to remote sensing). A simple "plug and play" approach is required, where off-the-shelf sensors can be easily interfaced with a data collection and analysis system. The system should support multiple platforms, devices and sensors, for alphanumerical data, images and videos.
The aim of this project is to develop the enabling technology and to analyse the potential of low-cost monitoring solutions for physically and biologically relevant data from marine environments. Initially the project will focus on working with SCUBA divers to source water temperature from dive computers to test the emerging technology, with scope to include other measurements like salinity and oxygen later.

Methodology:
Initial work will focus on the development of appropriate software interfaces to collect temperature data from dive computers, using the "diveintoscience" platform as a base. This builds upon Linux-Apache-MySQL-PHP (LAMP) architecture, particularly to improve upload and visualisation facilities for citizens, professional scientists, and decision-makers. A machine-learning ensemble-based methodology will be developed for:
(a) Assessing the quality of the submitted data automatically;
(b) Integrating with other traditional (e.g. scientific diving), citizen (e.g. coastal temperature network), and remote sensed datasets (e.g. satellites);
(c) Visualisation.
Comparisons with satellite sea surface temperatures will be used to validate the data. Dive-computer specific algorithms for automated correction of the measurements will be developed. Additional citizen data will be sourced from dive organisations.
To exploit the data scientifically, maps of depth- and time-resolved inshore temperatures will be created to determine the arrival times of isotherms at the coast and to detect hydrographic features such as fronts and thermoclines, primarily in UK shelf seas. This will be linked to biological data (e.g. young fish surveys) to assess the impact on populations of young fish, species distribution, and commercial activities such as aquaculture. Comparisons with model hindcasts (from Copernicus) will be done to assess limitations in accuracy and resolution.