A Smart Security Drones for Farms Using Software Architecture

A Smart Security Drones for Farms Using Software Architecture

Yoki Karl (Daegu Catholic University, Gyeongsan, South Korea), Haeng-Kon Kim (Daegu Catholic University, Gyeongsan, South Korea), and Jong-Halk Lee (Daegu Catholic University, Gyeongsan, South Korea)
Copyright: © 2020 |Pages: 10
DOI: 10.4018/IJSI.2020100103
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Predators like lions and elephants, around farms to kill and destroy a farm's livestock. For this reason, productivity in agriculture decreases over time resulting in poor production of crops and even killing of poultry animals. The development drone for driven agriculture based on image process and IoT technology provides an effective way to ensure the protection of farms and agriculture against wild animals. An automatic drone flies after receiving a signal from server with machine learning to hunt wild animals outside the farm. The focus is on object detection which is also the highlight of this project. Furthermore, the UAV drone was developed through UAV technologies, with functionalities necessary for the successful deployment of a fully autonomous UAV operation over agriculture and traffic networks. The UAV is able to navigate autonomously at different altitudes and plan for mission goals such as locating, identifying, tracking, and the development of reliable software and hardware architectures. This article proposes a UML diagram including the design of the unmanned aerial vehicle system and software in it. The software is called embedded software. Model-based testing is a resolution for testing the embedded software.
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Developed countries have already begun using drones in precision farming (Zhang & Kovacs, 2012; Aditya & Kulkarni, 2016) photogrammetry and remote sensing (Everaerts, 2008; Colomina & Molina, 2014). It is very fast and could reduce a farmer's workload. In general, drones are equipped with cameras and sensors for crop monitoring. In the past, a variety of drone models that operate on military and civilian applications (Van Blyenburgh, 1999). In agriculture, Yamaha (Giles & Billing, 2015) developed the first drone model. pests in Yamaha RMAX helicopter applications and crop monitoring in agriculture has been introduced. However, Yamaha shut down production in 2007. Technical analysis of unmanned aerial vehicles in precision farming is to analyze their applicability in farms such as surveillance crops (Bendig et al., 2012). The world suffers daily natural disasters such as earthquakes during which many people lose their lives. Similarly, farms are also attacked by predators such as lions. Bumble bees can be used during the attack to determine the damage and its scope in the field of agriculture. Bumble bees are known as drones (UAVs). Unmanned aerial vehicle (UAV) platforms today are a valuable source of data for problem inspection, monitoring, mapping, and 3D modeling (Remondino et al., 2011). Unmanned aerial vehicles (UAVs) are ships capable of flying unmanned on board. They can be remotely controlled by an operator or can be independently controlled by pre-programmed flight paths. In our work, areas of application where images of unmanned aerial vehicles are used include agricultural safety. The drone can acquire images quickly for early impact assessment. Using the UML diagram software methods, this paper presents a drone development based on image processing and IoT technology that provides an effective way to ensure the protection of farms and agriculture against wild animals. In addition, the results provide precision performance compared and analyzed with the following features available for evaluation. The rest of this article is structured as follows: First, we present a comprehensive architecture for intelligent security drone operations using software architecture - development design phase. Diagram methodology UML and piezoelectric loudspeaker system circuit will be explained in this section. And then, the implementation phase of the development will describe the implementation and, finally, provide an analysis of the results obtained, namely the evaluation and the system conclusion.

Current Issue; As the economy grows, the demand for quality of life and material goods increases. The problem of the aging of farmers has also become important, contributing to the weakening of the quality and quantity of human resources. The lack of agricultural security technology still exists. In fact, the problem of “human hunting” in the agricultural sector of the non-agricultural security sector is becoming serious. The main problem for farmers is the lack of knowledge of modern agricultural techniques. Farmers continue to use old and obsolete farming methods, while technology has improved a lot. Numerous sectors of the economic cost attributed to livestock losses.

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