Han, DavidRodriguez, Mia2023-11-282023-11-282023-05-09Han, 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/10.1145/3576914.3588337979-8-4007-0049-1https://doi.org/10.1145/3576914.3588337https://hdl.handle.net/20.500.12588/2249Big 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.en-USAttribution-NonCommercial-NoDerivs 3.0 United Stateshttp://creativecommons.org/licenses/by-nc-nd/3.0/us/big datadata analyticsdata scienceprecision agriculturesmart farming systemsArticle