Title: associate professor
Association/Company: Università Ca’ Foscari Venezia
Biography:
Roberto Pastres è professore associato di ecologia presso il Dipartimento di Scienze Ambientali, Informatica e Statistica dell’Università Ca’ Foscari di Venezia. La sua attività di ricerca riguarda la valutazione della sostenibilità ambientale dell’acquacoltura e lo sviluppo di modelli predittivi per la messa in opera di modelli gestionali basati sull’acquacoltura di precisione. Ha coordinato il progetto H2020 GAIN ed attualmente coordina il progetto INTERREG Ita-Slo BeBlue.
Speech session
New technologies in aquaculture (precision aquaculture, artificial intelligence, robotics, nanotechnology)
Speech
A “Digital Twin” for designing and managing aquaponic systems
Abstract
Aquaponics allows one to produce fish and vegetables, markedly reducing the use of water as well as nitrogen and phosphorus emissions. The design and management of aquaponic systems, however, is complex, as one needs to optimize the flows of matter and energy, to maximize the yield and ensure the welfare of the farmed species. To promote the adoption of these systems, the BeBlue project, https://www.ita-slo.eu/it/beblue, developed a prototype of “Digital Twin”, for simulating in real time the functioning of these farming systems. The model was applied to two pilot plants, including a marine aquaponic systems, in which seabream, samphire and seaweeds are begin co-produced.
Speech session 2
Speech
Digitalizing aquaculture: quality control and real time data processing
Abstract
Automatic sensors for the detection of the main water quality parameters (Temperature, Dissolved Oxygen, pH and Salinity) are presently available at acceptable costs. The collected data, however, should be processed for obtaining information useful for aquafarm operators. The processing should include the evaluation of data quality: this step is, sometime, overlooked. Combining statistical tools and dynamic models, it is possible to include it in integrated predictive systems, which could simulate water quality in relation to the metabolic activity of farmed organisms, thus providing indications for optimizing control actions.