IA-GES-BLOOM-CM: Creating synergies between biologist and engineers to develop tools for Cyanobacteria Bloom Management
Start Date
23-5-2022 2:30 PM
End Date
23-5-2022 2:45 PM
Abstract
IA-GES-BLOOM-CM is a synergy project for boosting the collaboration of researchers of different fields to develop disruptive solutions for Cyanobacteria Bloom (CB) management. Its aim is to bring together researchers from Biology, Economy, Automation, and Information & Communication Technologies to make them envision and develop new tools for the early detection and prediction of Cyanobacteria Blooms (CBs). The original proposal provides for using Modeling and Simulation to predict where and when CBs take place; intelligently-guiding Autonomous Surface Vehicles (boats, ASVs) to optimize the observations of relevant 3D information related to CBs; and deploying an Internet of Things infrastructure with Artificial Intelligence to bring and summarize the information (acquired by the ASVs sensors and provided by the simulations) to/for the managers of water bodies. Discussions among researchers are key to decide how to exploit the technologies and the biologist expertise to achieve a final solution that not only fulfills the current demands by the authorities but that also opens opportunities for future requirements and procedures. During this presentation we will provide an overview of the main ideas of the project and of its initial developments.
IA-GES-BLOOM-CM: Creating synergies between biologist and engineers to develop tools for Cyanobacteria Bloom Management
IA-GES-BLOOM-CM is a synergy project for boosting the collaboration of researchers of different fields to develop disruptive solutions for Cyanobacteria Bloom (CB) management. Its aim is to bring together researchers from Biology, Economy, Automation, and Information & Communication Technologies to make them envision and develop new tools for the early detection and prediction of Cyanobacteria Blooms (CBs). The original proposal provides for using Modeling and Simulation to predict where and when CBs take place; intelligently-guiding Autonomous Surface Vehicles (boats, ASVs) to optimize the observations of relevant 3D information related to CBs; and deploying an Internet of Things infrastructure with Artificial Intelligence to bring and summarize the information (acquired by the ASVs sensors and provided by the simulations) to/for the managers of water bodies. Discussions among researchers are key to decide how to exploit the technologies and the biologist expertise to achieve a final solution that not only fulfills the current demands by the authorities but that also opens opportunities for future requirements and procedures. During this presentation we will provide an overview of the main ideas of the project and of its initial developments.