<\/span><\/p>\nThis two-year project, funded by the Science and Technology Cooperation Sino-Malta Fund, aims to propose an alternative unmanned solution via the development of a hybrid drive biomimetic underwater robotic cage-monitoring system. This robotic system will incorporate state-of-the-art digital technologies to provide reliable underwater 3D positioning and localisation, Spatio-temporal warnings for water quality, fish biomass estimations and benthic identification systems. Additionally, computer vision modelling will be used to support the digitalisation of environmental monitoring in Malta, specifically survey and mapping of benthic habitats. This technology has the potential of reducing the cost of breeding, improve the efficiency of breeding, and realise a safe and sustainable approach for the comprehensive monitoring of deep-sea cages and marine environment.<\/span><\/p>\n
<\/span>Expected Outcomes:<\/h5>\n\n- Design and construct innovative integrated rigid-flexible coupling hybrid-drive bionic underwater robotic system prototypes with the capability of autonomous 3D positioning and localisation within deepwater environments, and reduced noise and disturbance during unmanned underwater monitoring.<\/li>\n
- Design and construct a spatial prediction model for water quality in marine environments and aquaculture.<\/li>\n
- Develop and construct a Biomass Estimation Model for fish biomass estimates based on multi-module convolutional networks.<\/li>\n
- Develop and construct an automated benthic detection and identification system of key marine features (endangered species, invasive species, benthos type, lost or damaged maritime infrastructure} through machine learning, machine vision prototypes and artificial neural networks.<\/li>\n
- Demonstrate the integrated platform for digital deep water net cage comprehensive monitoring system in China. This demonstration will showcase the application of the water quality prediction model and the biomass estimation model.<\/li>\n
- Demonstrate in Malta the benthic habitat model for live identification of Maltese marine benthic habitats from ROV captured video in the depth range 10-10 meters.<\/li>\n<\/ul>\n
<\/div>\n
Impact of Research:<\/span>
<\/p>\n<\/p>\n
The outcomes of this project will likely contribute to promote an environmentally healthier development of the aquaculture industry, resulting in economic, social environmental and political\/diplomatic benefits.<\/p>\n
<\/p>\n
1) Political and diplomatic benefits<\/h6>\n
This project involves the cooperation with international partners that has to potential to promote the cooperation in the market promotion of high-tech solution in the field of deep-cages aquaculture, contributing to the introduction of innovative solutions based on digital transformation. This will in turn promote th continuous expansion of new areas of international cooperation between Malta and China.<\/p>\n
<\/p>\n
2) Economic benefits<\/h6>\n
The main aim of this project is to carry out the design of an underwater bionic robot system which integrates:<\/p>\n
\n- A water quality spatio-temporal warning system<\/li>\n
- A biomass estimation system<\/li>\n
- An automated benthic population recognition system<\/li>\n<\/ul>\n
The development and implementation of such a system has the potential to upgrade the traditional aquaculture model towards a more efficient ecologically-sustainable aquaculture system, based on digital transformation. This will allow to develop an aquaculture production process based on more scientific, digital, and precise data, thus reducingthe economic loss often caused by a blin aquaculture production, while improving the environmental impact.<\/p>\n
<\/p>\n
3) Ecological Benefits<\/h6>\n
The implementation of this project has the potential to provide scientific data to monitor real-time changes of environmental factors in the aquaculture process. The research will combine physical models and simulations to reduce the harm caused by water qualit mutations to fish growth, while providing real-time fish growth data that will improve the production processes. This will allow for a more accurate and scientific decision-making process for the use of bait, fertilization and drugs in the aquaculture process, that is likely to result in a significant reduction of wastes. Thus, such technology and approach will contribute towards reducing the impact that the aquaculture industry usually has on the environment and surronding ecosystems, while promoting the transition towards more sustainable models.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"
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