Internet of Things (IoT) and Agricultural Unmanned Aerial Vehicles (UAVs) in smart farming: A comprehensive review

By A. Boursianis, Panagiotis D. Diamantoulakis, A. Liopa-Tsakalidi, P. Barouchas, G. Salahas, George K. Karagiannidis, Shaohua Wan, Sotirios K Goudos. Internet of Things, 2020

684 citations recorded by the source corpus.

Abstract Internet of Things (IoT) and Unmanned Aerial Vehicles (UAVs) are two hot technologies utilized in cultivation fields, which transform traditional farming practices into a new era of precision agriculture. In this paper, we perform a survey of the last research on IoT and UAV technology applied in agriculture. We describe the main principles of IoT technology, including intelligent sensors, IoT sensor types, networks and protocols used in agriculture, as well as IoT applications and solutions in smart farming. Moreover, we present the role of UAV technology in smart agriculture, by analyzing the applications of UAVs in various scenarios, including irrigation, fertilization, use of pesticides, weed management, plant growth monitoring, crop disease management, and field-level phenotyping. Furthermore, the utilization of UAV systems in complex agricultural environments is also analyzed. Our conclusion is that IoT and UAV are two of the most important technologies that transform traditional cultivation practices into a new perspective of intelligence in precision agriculture.

Subfields: Ecology, Electrical and Electronic Engineering, Plant Science

View Paper: https://www.semanticscholar.org/paper/cc6896dffe21b7ca5e38dff191dc91c8e0a1f18d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

In Electrical and Electronic Engineering

Quoc-Viet Pham

In Plant Science

Citations in the corpus

Advances in Smart Environment Monitoring Systems Using IoT and Sensors (2020, background): “There are a few other important studies on various application of SEM systems for di ﬀ erent applications, such as smart farming [62], pest monitoring [63], and crop area monitoring [61].”
Machine Learning Applications for Precision Agriculture: A Comprehensive Review (2021, methodology): “In this approach, technologies such as smart sensors, robotics, UAVs, and IoT devices [148], AI, and ML-based computer vision techniques are employed to intelligently harvest the crops.”
Unmanned Aerial Vehicles in Smart Agriculture: Applications, Requirements, and Challenges (2020, background): “Some of the advanced features, such as low maintenance costs, fast set-up time, low acquisition costs, and live data capture, have made UAVs a better option for farmers in the agricultural sector [9].”
Smart Farming Technology Trends: Economic and Environmental Effects, Labor Impact, and Adoption Readiness (2020, background): “These include variable rate applicators [15–17], Internet of things (IoT) [18,19], geo‐positioning systems [20,21], big data [22–24], unmanned aerial vehicles (UAVs, drones) [18,25], automated systems, and robotics [26,27].”
Applications of Remote Sensing in Precision Agriculture: A Review (2020, methodology): “, artificial neural networks) have been used to estimate ET, soil moisture, and crop predictions for automated and precise application of water, fertilizer, herbicide, and insecticides [23].”