Publication | Open Access
The Path to Smart Farming: Innovations and Opportunities in Precision Agriculture
629
Citations
53
References
2023
Year
Precision AgricultureEngineeringMachine LearningDigital AgricultureAgricultural EconomicsTechnology AdoptionAgricultural CyberneticsFarming SystemSmart FarmingSustainable AgricultureInternet Of ThingsPublic HealthSmart AgriculturePrecision FarmingAgricultureIot Data AnalyticsAgricultural TechnologyFarming SystemsTechnologyBig Data
Precision agriculture uses advanced technology and data analysis to increase productivity, reduce waste, and mitigate environmental impacts while feeding a growing population. This review examines recent advances in precision agriculture—including IoT and big data—and aims to overview innovations, challenges, and future prospects. The article analyzes the current state of precision agriculture, highlighting innovations such as drones, sensors, and machine learning, and discusses challenges of data management, technology adoption, and cost‑effectiveness.
Precision agriculture employs cutting-edge technologies to increase agricultural productivity while reducing adverse impacts on the environment. Precision agriculture is a farming approach that uses advanced technology and data analysis to maximize crop yields, cut waste, and increase productivity. It is a potential strategy for tackling some of the major issues confronting contemporary agriculture, such as feeding a growing world population while reducing environmental effects. This review article examines some of the latest recent advances in precision agriculture, including the Internet of Things (IoT) and how to make use of big data. This review article aims to provide an overview of the recent innovations, challenges, and future prospects of precision agriculture and smart farming. It presents an analysis of the current state of precision agriculture, including the most recent innovations in technology, such as drones, sensors, and machine learning. The article also discusses some of the main challenges faced by precision agriculture, including data management, technology adoption, and cost-effectiveness.
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