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Agriculture is India’s most common job, yet it lacks innovation and technology. As the world’s population expands, so does the demand for more food. Pesticides are used on farms to boost yield. The toxicity of the fertilizer has serious health repercussions for the farmer. So, it’s recommended to measure the amount of pesticide used and only apply it when necessary. We devised an insect-finding and insecticide-spraying mechanism. This is accomplished by employing a drone or Uninterrupted Ariel Vehicle. The drone has a camera that can photograph fields and lift pesticides weighing 3 to 4kg. After locating the insect, the insecticide is sprayed through the nozzles. In the proposed model, the Deep Convolutional Neural Network (CNN) has reached state of the art in image processing and object detection issues. Deep CNN has the potential to self-learn hidden features that help with insect detection. When compared to other similar approaches, experimental findings on a real dataset to illustrate the usefulness of the suggested methodology. We identified insects on the crop with 90% accuracy using deep CNN. It helps farmers to increase crop yield while also shielding them from the detrimental effects of spraying pesticides on the field manually.

This paper uses the Haida iFLY-U3 fixed-wing UAV for image data acquisition. Based on UAV low-altitude photogrammetry technology, field control measurement method, such as Agisoft PhotoScan and Pix4D Mapper software, can process and produce DEM and DOM. Practical research on the processes and key technologies of digital products is under process. The field checkpoint measurement for the accuracy of DOM digital products made by low-altitude digital photogrammetry technology creates a basis for the practical application and development of digital products. The main contents of this paper are as follows: (a) The basic principles and processes of digital products for drone remote sensing image production, such as control point layout and measurement methods. (b) Based on the UAV photography technology, the digital product DOM and the field measurement control point accuracy evaluation are generated. (c). The polynomial curve digital model method is used to solve the elevation correction value, and the quadratic polynomial fitting model of the elevation point of the internal digital product is established, and the precision analysis is carried out.

This paper conducts a systematic literature review with bibliometric analysis for drone-related research in Emergency Medical Services (EMS). Forty publications were extracted from the SCOPUS database during 2015–2019 for further analysis. The results show the current research landscape and guide future research directions. Interestingly, the occurrence of the COVID-19 pandemic made the use of drones necessary to assist EMSs lifesaving tasks to reduce fatality, which has also attracted more attention from the academic community. It was found that the co-evolution of drone technologies and entrepreneurial activities in the EMS ecosystem offers drone uses beyond medical applications.

Landing is the most challenging and risky aspect of basic multirotor drone flight, and only simple landing methods exist for autonomous drones. We explore methods for autonomous drone landing in two scenarios. In the first scenario, we examine methods for landing on known landing pads using fiducial markers and a gimbal-mounted monocular camera. This method has potential in drone applications where a drone must land more accurately than global positioning system (GPS) can provide (e.g. package delivery in an urban canyon). We expand on previous methods by actuating the drone’s camera to track the marker over time, and we address the complexities of pose estimation caused by fiducial marker orientation ambiguity. In the second scenario, and in collaboration with the Rover-Aerial Vehicle Exploration Network (RAVEN) project, we explore methods for landing on solidified lava flows in Iceland, which serves as an analog environment for Mars and provides insight into the effectiveness of drone-rover exploration teams. Our drone uses a depth camera to visualize the terrain, and we are developing methods to analyze the terrain data for viable landing sites in real time with minimal sensors and external infrastructure requirements, so that the solution does not heavily influence the drone’s behavior, mission structure, or operational environments.

The study delineates an innovative approach for enhancing an unmanned aerial vehicle (UAV) by equipping it with docking and battery-swapping mechanisms that draw inspiration from nature. The docking mechanism, which derives inspiration from a bat’s secure hanging posture and the adaptive structure of orchid flowers, ensures stable docking of the UAV. A battery-swapping system, modeled after the hermit crabs shell exchange process, facilitates swift and reliable battery replacement. These bio-inspired mechanisms, implemented on the X-UAV Mini Talon platform using 3D-printed components for structural modifications, not only optimize operational efficiency and versatility but also enable the UAV with vertical take-off and landing (VTOL) capabilities. This research underscores the potential of biomimicry in UAV design, demonstrating the feasibility and adaptability of these innovative solutions for practical implementation.

In This paper, a mixed robust sliding mode with fuzzy logic controller is applied to a nonlinear quadrotor Unmanned Aerial Vehicle (UAV). Based on the technique of variable structure control (VSC) with sliding mode, we can construct the controller that possesses the merits of both fuzzy Logic Controller (FLC) and Sliding Mode Controller (SMC), It is called a Fuzzy Sliding Mode Controller (FSMC). It provides a simple way to solve the main drawback of VSC by reducing the amount of chattering effect using a fuzzy control part in the proposed controller. Also, the VSC part makes the system stable which treats the main disadvantage of fuzzy controller when being used alone. Numerical simulation of the proposed controller is presented and discussed. Furthermore, a comparison with the SMC is also made.