# Quadcopters in Smart Agriculture: Applications and Modelling  
[PERSON]  
1 Lab-STICC, UMR 8265 CNRS, ENSTA Bretagne, 29806 Brest Cedex 9, France; [EMAIL_ADDRESS] (K.K. ); [EMAIL_ADDRESS] (B.C. ); [EMAIL_ADDRESS] (M.A.-U.) [PERSON]  
1 Lab-STICC, UMR 8265 CNRS, ENSTA Bretagne, 29806 Brest Cedex 9, France; [EMAIL_ADDRESS] (K.K. ); [EMAIL_ADDRESS] (B.C. ); [EMAIL_ADDRESS] (M.A.-U.) [PERSON]  
2 Department of Electrical Engineering, Faculty of Engineering, University of Balamand,  
Tripoli P.O. Box 100, Lebanon; [EMAIL_ADDRESS]  
[PERSON]  
1 Lab-STICC, UMR 8265 CNRS, ENSTA Bretagne, 29806 Brest Cedex 9, France; [EMAIL_ADDRESS] (K.K. ); [EMAIL_ADDRESS] (B.C. ); [EMAIL_ADDRESS] (M.A.-U.) [PERSON]  
1 Lab-STICC, UMR 8265 CNRS, ENSTA Bretagne, 29806 Brest Cedex 9, France; [EMAIL_ADDRESS] (K.K. ); [EMAIL_ADDRESS] (B.C. ); [EMAIL_ADDRESS] (M.A.-U.) Footnote 1: [[https://www.mdpi.com/journal/applsci](https://www.mdpi.com/journal/applsci)]([https://www.mdpi.com/journal/applsci](https://www.mdpi.com/journal/applsci))  
Footnote 2: [[https://www.mdpi.com/journals/pdf/100/09/10](https://www.mdpi.com/journals/pdf/100/09/10)]([https://www.mdpi.com/journals/pdf/100/09/10](https://www.mdpi.com/journals/pdf/100/09/10))  
However, despite these advancements, the agriculture sector continues to face many challenges worldwide, including desertification, water scarcity, pollution, and the excessive use of chemicals and resources [6]. To address these issues, smart agriculture emerged in the early 21 st century, focusing on optimizing resource use and improving both the quality and quantity of agricultural output. In this modern phase, new technologies like Artificial Intelligence (AI), IoT, and UAVs are integrated into the agriculture sector to make it smarter and more efficient [4; 7; 8; 9; 10]. UAVs are among the modern technologies being extensively used in smart agriculture due to their flexibility, autonomous operation, cost-effectiveness, ability to avoid certain adverse weather conditions, and capacity to complete agricultural missions efficiently and in less time. Playing a significant role in smart agriculture, UAVs have captured researchers' interests, as they are considered essential tools for monitoring vast areas and performing precision applications [11; 12; 13; 14]. Among the various types of UAVs, this paper focuses on rotary-wing UAVs, specifically quadcopters, due to their multiple capabilities and features, such as agility, ability to hover, ease of use, and more. Quadcopters surpass other UAVs and are the most commonly chosen and popular drones in various fields [15; 16; 17], including academic projects, agricultural applications, military purposes, entertainment, and more, as illustrated in Figure 1.  
Although quadcopters have various applications across different fields, this paper focuses specifically on their role in smart agriculture. Given the significant impact quadcopters have on the agriculture sector, it is crucial to explore their diverse features and capabilities. This paper examines the types of quadcopters used specifically for agricultural missions and discusses the various applications that are uniquely accomplished by quadcopters. Additionally, as the core of the system, quadcopters must be precisely modeled to replicate real-world conditions and achieve the highest possible accuracy. Therefore, this paper explores their modelling in various aspects, such as configurations, reference frames, movements, and mathematical motion equations, to design an efficient model. To the best of our knowledge, this is the only paper in the literature that provides a comprehensive survey of quadcopters in smart agriculture. The rest of this paper is divided into five sections. Section 2 explores the different types of quadcopters used in smart agriculture. Section 3 discusses the various agricultural missions that quadcopters can perform and provides examples for each application. Section 4 examines quadcopter modelling in terms of configurations and mathematical equations.