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Konya A, Nematzadeh P. Recent applications of AI to environmental disciplines: A review. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:167705. [PMID: 37820816 DOI: 10.1016/j.scitotenv.2023.167705] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 10/06/2023] [Accepted: 10/07/2023] [Indexed: 10/13/2023]
Abstract
The rapid development and efficiency of Artificial Intelligence (AI) tools have made them increasingly popular in various fields and research domains. The environmental discipline is now experiencing an exponential interest in harnessing the potential of AI over the past decade. We have reviewed the latest applications of AI tools in the environmental disciplines, highlighting the opportunities they present and discussing their advantages and disadvantages in this field. After the emergence of deep learning algorithms in 2010, interest in using AI tools for environmental tasks has grown exponentially. Among the studied articles, over 65 % of environmental tasks that demonstrate interest in using AI tools initially relied on conventional statistical and mathematical models. Using AI tools can greatly benefit the areas of environmental science and engineering. One of the main advantages of utilizing AI tools is their ability to analyze and process large amounts of data efficiently. Recently, the European Union established a European supercomputing ecosystem program to advance science and enhance the quality of life for its citizens. Nine of these projects prioritize environmental and sustainable goals. Despite the benefits of AI, it is still in its early stages of development, which comes with environmental concerns. The amount of power consumed and the time required to train an AI model can greatly affect the carbon emissions it produces, exacerbating the challenges posed by climate change. Efforts are currently underway to develop AI technology that is environmentally sustainable, minimizes energy consumption, and has a low carbon footprint. Selecting the appropriate AI model architecture can reduce energy consumption by almost 90 %. The main finding suggests that collaboration between environmental and AI professionals becomes crucial in leveraging the full potential of AI in addressing pressing environmental challenges.
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Affiliation(s)
- Aniko Konya
- University of Illinois, Chicago, IL 60637, USA.
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Hassoun A, Cropotova J, Trollman H, Jagtap S, Garcia-Garcia G, Parra-López C, Nirmal N, Özogul F, Bhat Z, Aït-Kaddour A, Bono G. Use of industry 4.0 technologies to reduce and valorize seafood waste and by-products: A narrative review on current knowledge. Curr Res Food Sci 2023; 6:100505. [PMID: 37151380 PMCID: PMC10160358 DOI: 10.1016/j.crfs.2023.100505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 04/07/2023] [Accepted: 04/16/2023] [Indexed: 05/09/2023] Open
Abstract
Fish and other seafood products represent a valuable source of many nutrients and micronutrients for the human diet and contribute significantly to global food security. However, considerable amounts of seafood waste and by-products are generated along the seafood value and supply chain, from the sea to the consumer table, causing severe environmental damage and significant economic loss. Therefore, innovative solutions and alternative approaches are urgently needed to ensure a better management of seafood discards and mitigate their economic and environmental burdens. The use of emerging technologies, including the fourth industrial revolution (Industry 4.0) innovations (such as Artificial Intelligence, Big Data, smart sensors, and the Internet of Things, and other advanced technologies) to reduce and valorize seafood waste and by-products could be a promising strategy to enhance blue economy and food sustainability around the globe. This narrative review focuses on the issues and risks associated with the underutilization of waste and by-products resulting from fisheries and other seafood industries. Particularly, recent technological advances and digital tools being harnessed for the prevention and valorization of these natural invaluable resources are highlighted.
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Affiliation(s)
- Abdo Hassoun
- Univ. Littoral Côte D’Opale, UMRt 1158 BioEcoAgro, USC ANSES, INRAe, Univ. Artois, Univ. Lille, Univ. Picardie Jules Verne, Univ. Liège, Junia, F-62200, Boulogne-sur-Mer, France
- Sustainable AgriFoodtech Innovation & Research (SAFIR), Arras, France
- Corresponding author. Sustainable AgriFoodtech Innovation & Research (SAFIR), Arras, France.
| | - Janna Cropotova
- Department of Biological Sciences, Ålesund, Norwegian University of Science and Technology, Larsgårdsvegen 4, 6025, Ålesund, Norway
- Corresponding author.
| | - Hana Trollman
- School of Business, University of Leicester, Leicester, LE2 1RQ, UK
| | - Sandeep Jagtap
- Sustainable Manufacturing Systems Centre, School of Aerospace, Transport & Manufacturing, Cranfield University, Cranfield, MK43 0AL, UK
| | - Guillermo Garcia-Garcia
- Department of Agrifood System Economics, Centre ‘Camino de Purchil’, Institute of Agricultural and Fisheries Research and Training (IFAPA), P.O. Box 2027, 18080, Granada, Spain
| | - Carlos Parra-López
- Department of Agrifood System Economics, Centre ‘Camino de Purchil’, Institute of Agricultural and Fisheries Research and Training (IFAPA), P.O. Box 2027, 18080, Granada, Spain
| | - Nilesh Nirmal
- Institute of Nutrition, Mahidol University, 999 Phutthamonthon 4 Road, Salaya, Phutthamonthon, Nakhon Pathom, 73170, Thailand
| | - Fatih Özogul
- Department of Seafood Processing Technology, Faculty of Fisheries, Cukurova University, 01330, Balcali, Adana, Turkey
| | - Zuhaib Bhat
- Division of Livestock Products Technology, SKUAST-Jammu, Jammu, 181102, J&K, India
| | | | - Gioacchino Bono
- Institute for Biological Resources and Marine Biotechnologies, National Research Council (IRBIM-CNR), Mazara Del Vallo, Italy
- Dipartimento di Scienze e Technologie Biologiche, Chimiche e Farmaceutiche (STEBICEF), Università Di Palermo, Viale Delle Scienze, 90128, Palermo, Italy
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Erichsen AC, Middelboe AL. Introduction to the special series, "The future of marine environmental monitoring and assessment". INTEGRATED ENVIRONMENTAL ASSESSMENT AND MANAGEMENT 2022; 18:888-891. [PMID: 35610555 PMCID: PMC9328192 DOI: 10.1002/ieam.4640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 05/22/2022] [Accepted: 05/23/2022] [Indexed: 06/15/2023]
Abstract
Traditional marine monitoring can be a resource-intensive process that often covers a network of sampling stations where data are collected manually by divers, or discretely using in situ water samples at different depths at fixed positions followed by laboratory analysis. As such, environmental status is often reported after a delay of months or years. However, things are set to change for the better. Recent advances in technologies, such as remote sensing, machine learning techniques, modeling for non-experts, acoustic monitoring, and intelligent integration of modeling and sensor measurements will revolutionize the future of marine environmental monitoring and monitoring systems. This special series touches upon some of the new technologies and models that may be an integrated part of ecosystem assessment and management in the future. Although technologies are being developed and integrated for marine monitoring around the world, the integration with ecosystem models is still in the early days. Still, this series highlights inspirational examples of the time ahead of us. Integr Environ Assess Manag 2022;18:888-891. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
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