Leveraging Data in Precision Agriculture: A Review of Key Applications and Technologies
Keywords:
Precision Agriculture, Data Handling, Big Data, IoT, Remote Sensing, Machine Learning, Cloud Computi ng, Predicti ve Analyti cs, Sustainable AgricultureAbstract
Precision agriculture, also known as site-specific crop management (SSCM), is a farming management concept that uses data-driven technologies to monitor and optimize agricultural practices. By leveraging advanced tools such as GPS, drones, remote sensing, and Internet of Things (IoT) devices, farmers can collect vast amounts of data related to soil health, crop growth, weather patterns, and resource use. Effecti ve data handling is key to translating this information into actionable insights that improve productivity, reduce environmental impact, and ensure sustainability. This review explores the current technologies, methodologies, and challenges associated with precision agriculture and the role of data handling in enabling its potential.
References
Zhang C, Kovacs JM. The application of small unmanned aerial systems for precision agriculture: a review. Precision agriculture. 2012 Dec;13:693-712.
Liakos KG, Busato P, Moshou D, Pearson S, Bochtis D. Machine learning in agriculture: A review. Sensors. 2018 Aug 14;18(8):2674.
Gebbers R, Adamchuk VI. Precision agriculture and food security. Science. 2010 Feb 12;327(5967):828-31.
Schimmelpfennig D. Farm profits and adoption of precision agriculture. USDA Economic Research Report;
;217:1-46.
Patil VC, Al-Gaadi KA, Biradar DP, Rangaswamy M. Internet of things (Iot) and cloud computing for agriculture: An overview. Proceedings of agroinformatics and precision agriculture (AIPA 2012), India. 2012 Aug 1;292:296.
