Smart Farming and Precision Agriculture: Leveraging IoT and Data Analytics to Improve Crop Efficiency and Sustainability

Abstract

Smart farming and precision agriculture are modern approaches in the agricultural sector that utilize the Internet of Things (IoT) and data analytics to improve production efficiency and environmental sustainability. This research aims to explore how IoT technology and data analytics are applied in precision agriculture to face global challenges, such as increasing food needs and resource constraints. Qualitative methods are used with a literature study approach or library research, which focuses on the critical analysis of various scientific sources, including journals, reports, and related books. The results show that IoT provides the ability to monitor soil conditions, weather, and crops in real-time through sensors, while data analytics allows for the interpretation of that data for more accurate decision-making. These technologies contribute to more efficient management of resources, such as water and fertilizers, as well as the reduction of environmental impact through precise control of inputs. In addition, the adoption of this technology also has socio-economic implications, such as increasing the productivity of smallholders and supporting agribusiness sustainability. However, challenges such as high initial investment costs and the need for farmer training remain major obstacles. The study concludes that IoT and data analytics have great potential to revolutionize the agricultural sector by creating more efficient, environmentally friendly, and sustainable agricultural practices. Therefore, a policy strategy that supports the adoption of this technology is needed, especially in developing countries.