Big Data Analytics, Data Science, ML&AI for Connected, Data-driven Precision Agriculture and Smart Farming Systems: Challenges and Future Directions

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dc.contributor.authorHan, David
dc.contributor.authorRodriguez, Mia
dc.date.accessioned2023-11-28T15:37:17Z
dc.date.available2023-11-28T15:37:17Z
dc.date.issued2023-05-09
dc.description.abstractBig data and data scientific applications in the modern agriculture are rapidly evolving as the data technology advances and more computational power becomes available. The adoption of big data has enabled farmers and producers to optimize their agricultural activities sustainably with cutting-edge technologies, resulting in eco-friendly and efficient farming. Wireless sensor networks and machine learning have had a direct impact on smart and precision agriculture, with deep learning techniques applied to data collected via sensor nodes. Additionally, internet of things, drones, and robotics are being incorporated into farming techniques. Digital data handling has amplified the information wave, and information and communication technology have been used to deliver benefits to both farmers and consumers. This work highlights the technological implications and challenges that arise in data-driven agricultural practices as well as the research problems that need to be solved.
dc.description.departmentManagement Science and Statistics
dc.identifier.citationHan, D., & Rodriguez, M. (2023). Big Data Analytics, Data Science, ML&AI for Connected, Data-driven Precision Agriculture and Smart Farming Systems: Challenges and Future Directions. Paper presented at Cyber-Physical Systems and Internet of Things Week 2023, San Antonio, TX, USA. https://doi.org/10.1145/3576914.3588337
dc.identifier.isbn979-8-4007-0049-1
dc.identifier.otherhttps://doi.org/10.1145/3576914.3588337
dc.identifier.urihttps://hdl.handle.net/20.500.12588/2249
dc.language.isoen_US
dc.publisherAssociation for Computing Machinery
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United Statesen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/
dc.subjectbig data
dc.subjectdata analytics
dc.subjectdata science
dc.subjectprecision agriculture
dc.subjectsmart farming systems
dc.titleBig Data Analytics, Data Science, ML&AI for Connected, Data-driven Precision Agriculture and Smart Farming Systems: Challenges and Future Directions
dc.typeArticle

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