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Stakeholder Perspectives on Sensors and Automation in the Louisiana Sugarcane Industry

The sugarcane processing industry in the U.S. state of Louisiana is on the verge of a transformation toward increased automation and real-time data analytics through the adoption of sensor networks. As part of this transition, it was imperative to obtain the current insight and feedback on sensors,...

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Detalles Bibliográficos
Autor principal: Mandalika, Anurag
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer India 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10113988/
https://www.ncbi.nlm.nih.gov/pubmed/37363158
http://dx.doi.org/10.1007/s12355-023-01261-4
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author Mandalika, Anurag
author_facet Mandalika, Anurag
author_sort Mandalika, Anurag
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description The sugarcane processing industry in the U.S. state of Louisiana is on the verge of a transformation toward increased automation and real-time data analytics through the adoption of sensor networks. As part of this transition, it was imperative to obtain the current insight and feedback on sensors, automation, and data analytics from sugarcane processors. A short survey was circulated to assess the perspectives of industry stakeholders and seek their feedback on the prime needs for sensors, challenges in incorporating these, and outlook on real-time data analytics and predictive models in processing. Compilation of responses is presented, along with examples of industrially relevant projects that involve sensor networks, real-time data analytics, and artificial intelligence. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12355-023-01261-4.
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spelling pubmed-101139882023-04-20 Stakeholder Perspectives on Sensors and Automation in the Louisiana Sugarcane Industry Mandalika, Anurag Sugar Tech Short Communication The sugarcane processing industry in the U.S. state of Louisiana is on the verge of a transformation toward increased automation and real-time data analytics through the adoption of sensor networks. As part of this transition, it was imperative to obtain the current insight and feedback on sensors, automation, and data analytics from sugarcane processors. A short survey was circulated to assess the perspectives of industry stakeholders and seek their feedback on the prime needs for sensors, challenges in incorporating these, and outlook on real-time data analytics and predictive models in processing. Compilation of responses is presented, along with examples of industrially relevant projects that involve sensor networks, real-time data analytics, and artificial intelligence. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12355-023-01261-4. Springer India 2023-04-19 /pmc/articles/PMC10113988/ /pubmed/37363158 http://dx.doi.org/10.1007/s12355-023-01261-4 Text en © The Author(s), under exclusive licence to Society for Sugar Research & Promotion 2023 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Short Communication
Mandalika, Anurag
Stakeholder Perspectives on Sensors and Automation in the Louisiana Sugarcane Industry
title Stakeholder Perspectives on Sensors and Automation in the Louisiana Sugarcane Industry
title_full Stakeholder Perspectives on Sensors and Automation in the Louisiana Sugarcane Industry
title_fullStr Stakeholder Perspectives on Sensors and Automation in the Louisiana Sugarcane Industry
title_full_unstemmed Stakeholder Perspectives on Sensors and Automation in the Louisiana Sugarcane Industry
title_short Stakeholder Perspectives on Sensors and Automation in the Louisiana Sugarcane Industry
title_sort stakeholder perspectives on sensors and automation in the louisiana sugarcane industry
topic Short Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10113988/
https://www.ncbi.nlm.nih.gov/pubmed/37363158
http://dx.doi.org/10.1007/s12355-023-01261-4
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