Relevant bibliographies by topics / Drone architecture

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Drone architecture'

Author: Grafiati
Published: 4 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Drone architecture"

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Gao, Ying, Yangliang Liu, Quansi Wen, Hongliang Lin, and Yijian Chen. "Secure Drone Network Edge Service Architecture Guaranteed by DAG-Based Blockchain for Flying Automation under 5G." Sensors 20, no. 21 (2020): 6209. http://dx.doi.org/10.3390/s20216209.

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With the development of the Internet of Things (IoT), the number of drones, as a consumer-level IoT device, is rapidly increasing. The existence of a large number of drones increases the risk of misoperation during manual control. Therefore, it has become an inevitable trend to realize drone flying automation. Drone flying automation mainly relies on massive drone applications and services as well as third-party service providers, which not only complicate the drone network service environment but also raise some security and privacy issues. To address these challenges, this article proposes a
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Wadhwa, Shivani, Divya Gupta, Shalli Rani, Maha Driss, and Wadii Boulila. "Empowering drones in vehicular network through fog computing and blockchain technology." PLOS ONE 20, no. 1 (2025): e0314420. https://doi.org/10.1371/journal.pone.0314420.

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The performance of drones, especially for time-sensitive tasks, is critical in various applications. Fog nodes strategically placed near IoT devices serve as computational resources for drones, ensuring quick service responses for deadline-driven tasks. However, the limited battery capacity of drones poses a challenge, necessitating energy-efficient Internet of Drones (IoD) systems. Despite the increasing demand for drone flying automation, there is a significant absence of a comprehensive drone network service architecture tailored for secure and efficient operations of drones. This research
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Du, Jiang, Qiang Wei, Yisen Wang, and Xingyu Bai. "DEGNN: A Deep Learning-Based Method for Unmanned Aerial Vehicle Software Security Analysis." Drones 9, no. 2 (2025): 110. https://doi.org/10.3390/drones9020110.

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With the increasing utilization of drones, the cyber security threats they face have become more prominent. Code reuse in the software development of drone systems has led to vulnerabilities in drones. The binary code similarity analysis method offers a way to analyze drone firmware lacking source code. This paper proposes DEGNN, a novel graph neural network for binary code similarity analysis. It uses call-enhanced control graphs and attention mechanisms to generate dual embeddings of functions and predict similarity based on graph structures and node features. DEGNN is effective in cross-arc
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Yin, Tung. "Game of Drones." Texas A&M Law Review 2, no. 4 (2015): 635–73. http://dx.doi.org/10.37419/lr.v2.i4.3.

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This Article considers the threat posed by drone terrorism and the technological and legal issues involved in setting up defensive responses. First, the Article provides an overview of current drone technology, legal views on weaponized military drones, and a discussion of the potential appeal of drones as vehicles for terrorism. Next, it discusses the current laws and regulations pertaining to private drones. The Article then lays out the three challenges to defending against drone terrorism: detecting potentially hostile drones, identifying them, and destroying or neutralizing them. Finally,
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Takva, Çağatay, and Zeynep Yeşim İlerisoy. "Flying Robot Technology (Drone) Trends: A Review in the Building and Construction Industry." Architecture, Civil Engineering, Environment 16, no. 1 (2023): 47–68. http://dx.doi.org/10.2478/acee-2023-0004.

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Abstract With the emergence of Industry 4.0, the use of robotic technologies is among today’s trends. The innovations that this revolution brought to robotic construction in the fields of communication, control, and software also improve flying robot technology. In the study, the place and importance of drone technology, which is one of the flying robot technologies at the intersection of Industry 4.0 and AEC (architecture, engineering, and construction) industry, in architecture is defined. The research aims to analyze the digital fabrication studies with drone technology in the field of arch
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Abdullah, Abdullah, and Shailendra Mishra. "ML-based Intrusion Detection for Drone IoT Security." Journal of Cybersecurity and Information Management 14, no. 1 (2024): 64–78. http://dx.doi.org/10.54216/jcim.140105.

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The integration of drones into various industries brings about cybersecurity challenges due to their reliance on internet connectivity. To address this, we propose a comprehensive cybersecurity architecture leveraging machine learning (ML) algorithms and Internet of Things (IoT) technologies within the Internet of Drones (IoD) framework. Our architecture employs IoT-enabled sensors strategically placed across the drone ecosystem to collect and analyze data on system behaviors, communication patterns, and environmental variables. This data is then processed by a centralized platform equipped wi
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Alturki, Nazik, Turki Aljrees, Muhammad Umer, et al. "An Intelligent Framework for Cyber–Physical Satellite System and IoT-Aided Aerial Vehicle Security Threat Detection." Sensors 23, no. 16 (2023): 7154. http://dx.doi.org/10.3390/s23167154.

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The small-drone technology domain is the outcome of a breakthrough in technological advancement for drones. The Internet of Things (IoT) is used by drones to provide inter-location services for navigation. But, due to issues related to their architecture and design, drones are not immune to threats related to security and privacy. Establishing a secure and reliable network is essential to obtaining optimal performance from drones. While small drones offer promising avenues for growth in civil and defense industries, they are prone to attacks on safety, security, and privacy. The current archit
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Appelbaum, Deniz, and Robert A. Nehmer. "Using Drones in Internal and External Audits: An Exploratory Framework." Journal of Emerging Technologies in Accounting 14, no. 1 (2017): 99–113. http://dx.doi.org/10.2308/jeta-51704.

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ABSTRACT: Recently the FAA relaxed restrictions on the use of drones or Unmanned Aircraft Systems (UASs) for commercial purposes. Markets for commercial drone use are in the technology trigger phase of the Gartner Group's Hyper Cycle, with developments occurring rapidly in real estate, agriculture (farming), the film industry, insurance, and other areas. Examination and inspection applications of drones have been proposed in heavy industry and cell tower inspection. Previous research suggests an incremental structure for implementing technological innovations such as continuous auditing (CA).
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Mirzaeinia and Hassanalian. "Minimum-Cost Drone‒Nest Matching through the Kuhn‒Munkres Algorithm in Smart Cities: Energy Management and Efficiency Enhancement." Aerospace 6, no. 11 (2019): 125. http://dx.doi.org/10.3390/aerospace6110125.

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The development of new concepts for smart cities and the application of drones in this area requires different architecture for the drones’ stations (nests) and their placement. Drones’ stations are designed to protect drones from hazards and utilize charging mechanisms such as solar cells to recharge them. Increasing the number of drones in smart cities makes it harder to find the optimum station for each drone to go to after performing its mission. In classic ordered technique, each drone returns to its preassigned station, which is shown to be not very efficient. Greedy and Kuhn‒Munkres (Hu
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Truong, Xuan Tung. "DEEP LEARNING TECHNIQUE - BASED DRONE DETECTION AND TRACKING." Journal of Military Science and Technology, no. 73 (June 15, 2021): 10–19. http://dx.doi.org/10.54939/1859-1043.j.mst.73.2021.10-19.

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The usage of small drones/UAVs is becoming increasingly important in recent years. Consequently, there is a rising potential of small drones being misused for illegal activities such as terrorism, smuggling of drugs, etc. posing high-security risks. Hence, tracking and surveillance of drones are essential to prevent security breaches. This paper resolves the problem of detecting small drones in surveillance videos using deep learning algorithms. Single Shot Detector (SSD) object detection algorithm and MobileNet-v2 architecture as the backbone were used for our experiments. The pre-trained mod
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Dissertations / Theses on the topic "Drone architecture"

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Ludington, Ben T. "Particle filter tracking architecture for use onboard unmanned aerial vehilces." Available online, Georgia Institute of Technology, 2006, 2006. http://etd.gatech.edu/theses/available/etd-11142006-152845/.

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Thesis (Ph. D.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2007.<br>Vachtsevanos, George, Committee Chair ; Heck, Bonnie, Committee Member ; Vela, Patricio, Committee Member ; Yezi, Anthony, Committee Member ; Johnson, Eric, Committee Member.
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Spieß, Christian [Verfasser]. "A Flight Physics Model and Controller Architecture for a Synchropter Drone / Christian Spieß." München : Verlag Dr. Hut, 2020. http://d-nb.info/1222352249/34.

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Schutz, Maxime. "Développement d’une architecture de RADAR à pénétration de sol dédié à une intégration sur drone." Thesis, Limoges, 2020. http://aurore.unilim.fr/theses/nxfile/default/3515bb91-73ce-4b5c-b1e5-206debe347e8/blobholder:0/2020LIMO0071.pdf.

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Le GPR (Ground Penetrating Radar) ou géoradar est utilisé pour la prospection des sous-sols. Par ailleurs, le marché des drones a rapidement évolué ces dernières années et la performance des solutions volantes actuelles vient offrir de nouvelles perspectives quant à leur utilisation. L’association des technologies du drone et du géoradar est alors une idée très attractive. De nombreux défis et incertitudes sont liés au rayonnement des basses fréquences, utiles pour une meilleure pénétration, et qui impliquent une taille conséquente du système antennaire. De plus, une maîtrise du coût et de la
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Sconyers, Christopher. "Particle filter-based architecture for video target tracking and geo-location using multiple UAVs." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47734.

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Research in the areas of target detection, tracking, and geo-location is most important for enabling an unmanned aerial vehicle (UAV) platform to autonomously execute a mission or task without the need for a pilot or operator. Small-class UAVs and video camera sensors complemented with "soft sensors" realized only in software as a combination of a priori knowledge and sensor measurements are called upon to replace the cumbersome precision sensors on-board a large class UAV. The objective of this research is to develop a geo-location solution for use on-board multiple UAVs with mounted video ca
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Basson, Lionel. "Control allocation as part of a fault-tolerant control architecture for UAVs." Thesis, Stellenbosch : University of Stellenbosch, 2011. http://hdl.handle.net/10019.1/6722.

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Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2011.<br>ENGLISH ABSTRACT: The development of a control allocation system for use as part of a fault-tolerant control (FTC) system in unmanned aerial vehicles (UAVs) is presented. This system plays a vital role in minimising the possibility that a fault will necessitate the reconfiguration of the control, guidance or navigation systems of the aircraft by minimising the difference between the desired and achievable aircraft performance parameters. This is achieved by optimising the allocation of control ef
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Elmagri, Loay Hatem Rajab. "Architecture and Drones: Accomodating Unmanned Aerial Vehicles." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/87584.

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Through out history, technological advancements have reshaped the built environment and its Architecture. The cities that we live in today were only made possible by the technologies of the first, second, and third industrial revolutions. Today, we are witnessing another technological revolution based on open source data and artificial intelligence. As there is an enormous amount of prosperous innovations that would directly impact Architecture design tools, building and finishing materials, and construction methods, there are also other innovations that would require spaces, buildings, a
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Maxa, Jean-Aimé. "Architecture de communication sécurisée d'une flotte de drones." Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30102/document.

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Grâce aux progrès de miniaturisation des systèmes embarqués, les mini-drones qu'on appelle en anglais Small Unmanned Aerial Vehicle (UAVs) sont apparus et permettent de réaliser des applications civiles à moindres coûts. Pour améliorer leurs performances sur des missions complexes (par exemple, pour contourner un obstacle), il est possible de déployer une flotte de drones coopératifs afin de partager les tâches entre les drones. Ce type d'opération exige un niveau élevé de coopération entre les drones et la station de contrôle. La communication entre les drones de la flotte est donc un enjeu i
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Samal, Mahendra Engineering &amp Information Technology Australian Defence Force Academy UNSW. "Neural network based identification and control of an unmanned helicopter." Awarded by:University of New South Wales - Australian Defence Force Academy. Engineering & Information Technology, 2009. http://handle.unsw.edu.au/1959.4/43917.

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This research work provides the development of an Adaptive Flight Control System (AFCS) for autonomous hover of a Rotary-wing Unmanned Aerial Vehicle (RUAV). Due to the complex, nonlinear and time-varying dynamics of the RUAV, indirect adaptive control using the Model Predictive Control (MPC) is utilised. The performance of the MPC mainly depends on the model of the RUAV used for predicting the future behaviour. Due to the complexities associated with the RUAV dynamics, a neural network based black box identification technique is used for modelling the behaviour of the RUAV. Auto-regres
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Bouachir, Ons. "Conception et mise en oeuvre d'une architecture de communication pour mini-drones civils." Toulouse 3, 2014. http://thesesups.ups-tlse.fr/2531/.

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Le domaine des drones, engins volants sans pilotes, généralement appelé UAV pour Unmanned Aerial Vehicle, ont longtemps été un outil militaire. Ces dernières années, avec l'avènement de micro-drones, plus petits, légers et moins coûteux que leurs homologues à étendu l'utilisation des UAV au domaine civil. Afin d'améliorer les performances des drones sur de telles missions, des recherches sont menées afin de rendre les drones coopératifs. Une flotte de drones coopératifs sera alors capable de réaliser plus rapidement des missions plus complexes en partageant les différentes tâches entre les UAV
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Imbulgoda, Liyangahawatte Gihan Janith Mendis. "Hardware Implementation and Applications of Deep Belief Networks." University of Akron / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=akron1476707730643462.

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Books on the topic "Drone architecture"

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Musial, Marek. System architecture of small autonomous UAVs: Requirements and design approaches in control, communication, and data processing. VDM Verlag Dr. Müller, 2008.

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Dibazar, Pedram, and Judith Naeff, eds. Visualizing the Street. Amsterdam University Press, 2018. http://dx.doi.org/10.5117/9789462984356.

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From user-generated images of streets to professional architectural renderings, and from digital maps and drone footages to representations of invisible digital ecologies, this collection of essays analyses the emergent practices of visualizing the street. Today, advancements in digital technologies of the image have given rise to the production and dissemination of imagery of streets and urban realities in multiple forms. The ubiquitous presence of digital visualizations has in turn created new forms of urban practice and modes of spatial encounter. Everyone who carries a smartphone not only
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Cureton, Paul. Drone Futures. Taylor & Francis Group, 2020.

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Drone: Unmanned. Architecture and Security Series. Dpr-Barcelona, 2016.

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Cureton, Paul. Drone Futures: UAS in Landscape and Urban Design. Taylor & Francis Group, 2020.

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Cureton, Paul. Drone Futures: UAS in Landscape and Urban Design. Taylor & Francis Group, 2020.

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Drone Futures: UAS in Landscape and Urban Design. Taylor & Francis Group, 2020.

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Tal, Daniel, and John Altschuld. Drone Technology in Architecture, Engineering and Construction: A Strategic Guide to Unmanned Aerial Vehicle Operation and Implementation. Wiley & Sons, Incorporated, John, 2020.

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Tal, Daniel, and John Altschuld. Drone Technology in Architecture, Engineering and Construction: A Strategic Guide to Unmanned Aerial Vehicle Operation and Implementation. Wiley & Sons, Incorporated, John, 2020.

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Tal, Daniel, and Jon Altschuld. Drone Technology in Architecture, Engineering and Construction: A Strategic Guide to Unmanned Aerial Vehicle Operation and Implementation. Wiley & Sons, Limited, John, 2021.

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Book chapters on the topic "Drone architecture"

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Sinha, Harsh, Nikita Malik, and Menal Dahiya. "Drone Ecosystem: Architecture for Configuring and Securing UAVs." In Proceedings of Fourth International Conference on Computing, Communications, and Cyber-Security. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1479-1_2.

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Koutsoubelias, Manos, Nasos Grigoropoulos, Giorgos Polychronis, Giannis Badakis, and Spyros Lalis. "System Architecture for Autonomous Drone-Based Remote Sensing." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94822-1_13.

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Zetter, Nathaniel. "In the Drone-Space: Surveillance, Spatial Processing, and the Videogame as Architectural Problem." In Surveillance, Architecture and Control. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-00371-5_12.

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Aburasain, R. Y., E. A. Edirisinghe, and M. Y. Zamim. "A Coarse-to-Fine Multi-class Object Detection in Drone Images Using Convolutional Neural Networks." In Digital Interaction and Machine Intelligence. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11432-8_2.

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AbstractMulti-class object detection has a rapid evolution in the last few years with the rise of deep Convolutional Neural Networks (CNNs) learning based, in particular. However, the success approaches are based on high resolution ground level images and extremely large volume of data as in COCO and VOC datasets. On the other hand, the availability of the drones has been increased in the last few years and hence several new applications have been established. One of such is understanding drone footage by analysing, detecting, recognizing different objects in the covered area. In this study co
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Yamamoto, Naoki, and Katsuhiro Naito. "Proposal of Continuous Remote Control Architecture for Drone Operations." In Intelligent Interactive Multimedia Systems and Services. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92231-7_7.

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Vaquero-Melchor, Diego, Iván Campaña, Ana M. Bernardos, Luca Bergesio, and Juan A. Besada. "A Distributed Drone-Oriented Architecture for In-Flight Object Detection." In Lecture Notes in Computer Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92639-1_36.

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Jeelani, Idris, and Masoud Gheisari. "Safety Challenges of Human-Drone Interactions on Construction Jobsites." In Automation and Robotics in the Architecture, Engineering, and Construction Industry. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-77163-8_7.

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Albeaino, Gilles, Masoud Gheisari, and Raja R. A. Issa. "Human-Drone Interaction (HDI): Opportunities and Considerations in Construction." In Automation and Robotics in the Architecture, Engineering, and Construction Industry. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-77163-8_6.

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Kholidy, Hisham A. "A Novel Blockchain Approach for Continuously Authenticating UAVs to Achieve Zero Trust Principles in 5G-Enabled UAVs." In Communications in Computer and Information Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-86240-3_1.

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Abstract Drones can provide real-time data transmission, improved signal quality, and reduced interference through beamforming technology The integration of drones (also known as Unmanned Aerial Vehicles (UAVs)) with 5G connectivity technology is revolutionizing various industries by enabling advanced features and capabilities, especially the reliable and secure network coverage. Security is an essential aspect of any digital or communications system. In drone-powered communication systems, security poses an even greater challenge. This is mainly due to the automated nature of the system and r
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Moyo, Marvellous, Tawanda Mushiri, and Habib Noorbhai. "Design of a Sustainable Rescue and First Aid Drone-Based System for Passenger Car Occupants." In Lecture Notes in Mechanical Engineering. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-28839-5_117.

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AbstractMedical emergencies transpire in passenger cars where most victims fail to access immediate medical assistance bringing about worsening of their health or death. Incorporation of rescue and first aid drone-based systems in Emergency Medical Services has been proposed. The objectives being improving response time of Emergency Medical Services, assessing the victim’s health, assisting in administration of first aid, real time live feed of victim’s vitals to the responders and mainly to outline how sustainability in healthcare can be achieved through adaptation of the proposed system. The
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Conference papers on the topic "Drone architecture"

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Vlasenko, Vitalii, and Andrii Dashkevych. "Drone Image Reconstruction Using Autoencoder Architecture." In 2024 IEEE 5th KhPI Week on Advanced Technology (KhPIWeek). IEEE, 2024. https://doi.org/10.1109/khpiweek61434.2024.10877999.

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Fredericks, Erik M., Mallory Jacobs, and Byron DeVries. "Towards a Metamorphic Testing Architecture for Software-Defined Drone Systems." In 2024 11th International Conference on Software Defined Systems (SDS). IEEE, 2024. https://doi.org/10.1109/sds64317.2024.10883896.

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Lenhard, Tamara R., Andreas Weinmann, Stefan Jäger, and Tobias Koch. "YOLO-Feder Fusionnet: A Novel Deep Learning Architecture for Drone Detection." In 2024 IEEE International Conference on Image Processing (ICIP). IEEE, 2024. http://dx.doi.org/10.1109/icip51287.2024.10647355.

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Souli, Nicolas, Andreas Palamas, Tania Panayiotou, Panayiotis Kolios, and Georgios Ellinas. "A Multi-task Transformer Architecture for Drone State Identification and Trajectory Prediction." In 2024 20th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT). IEEE, 2024. http://dx.doi.org/10.1109/dcoss-iot61029.2024.00051.

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Dahlstrom, Robert (Bob), and Michael Hindmarsh. "Industrial Cleaning and Coating Drones a Look at What’s Coming in 2022." In Coatings+ 2021. SSPC, 2021. https://doi.org/10.5006/s2021-00032.

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Abstract Cleaning, coating, and the nondestructive testing (NDT) of corrosion-susceptible surfaces requires extensive manual labor, often at heights that can create dangerous occupational environments. Drones, also known as uncrewed/unmanned aerial vehicles or systems (UAVs, UASs), can be leveraged to perform some of these tasks, including cleaning and coating, while keeping workers safely on the ground. Drone capabilities have significantly evolved over the past decade, and it is expected that the ubiquity of such systems will continue to increase in the years to come building. This paper foc
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Varra, Guillaume, Frédéric Blanc, Quentin Milliat, Damien Billet, Anthony Atencia, and Antoine Monneau. "Design of a High-performance Flight Control System for Unmanned Helicopters." In Vertical Flight Society 80th Annual Forum & Technology Display. The Vertical Flight Society, 2024. http://dx.doi.org/10.4050/f-0080-2024-1112.

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In the last decade, in order to respond to the emerging market of unmanned applications, Airbus Helicopters has developed a generic Flight Control System (FCS) for heavy unmanned helicopters. This paper describes the development of this system from the applicable high-level requirements to the design of the redundant fail safe-operative architecture and the flight modes. A focus is made on two specific flight sequences: Automatic Take-Off and Landing from ship deck which is one of the most complex maneuvers for a drone and 4D navigation (including relative to a target). The system has been bro
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Selvi, S. Sethu, Raghuram S, and Arathi Manik Rathod. "Slimmer Deep Learning Architectures for Drone Detection." In 2024 5th International Conference on Circuits, Control, Communication and Computing (I4C). IEEE, 2024. http://dx.doi.org/10.1109/i4c62240.2024.10748440.

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Morais, Daniel, Fabio Suim Chagas, Thiago Baldivieso, Gabriela Dias, and Paulo Rosa. "Multi-Drone 3D Reconstruction of Architectural and Structural Entities." In 2024 Brazilian Symposium on Robotics (SBR), and 2024 Workshop on Robotics in Education (WRE). IEEE, 2024. https://doi.org/10.1109/sbr/wre63066.2024.10837817.

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Saha, B., S. Kunze, and R. Poeschl. "Comparative Study of Deep Learning Model Architectures for Drone Detection and Classification." In 2024 IEEE International Mediterranean Conference on Communications and Networking (MeditCom). IEEE, 2024. http://dx.doi.org/10.1109/meditcom61057.2024.10621214.

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Morge-Rollet, Louis, Camélia Slimani, Laurent Lemarchand, Frédéric Le Roy, David Espes, and Jalil Boukhobza. "IDS-DEEP: a strategy for selecting the best IDS for Drones with heterogeneous EmbEdded Platforms." In 2024 IEEE 36th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD). IEEE, 2024. http://dx.doi.org/10.1109/sbac-pad63648.2024.00020.

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Reports on the topic "Drone architecture"

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Card, S., A. Wiethuechter, R. Moskowitz, and A. Gurtov. Drone Remote Identification Protocol (DRIP) Architecture. Edited by S. Zhao. RFC Editor, 2023. http://dx.doi.org/10.17487/rfc9434.

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Pasupuleti, Murali Krishna. Optimal Control and Reinforcement Learning: Theory, Algorithms, and Robotics Applications. National Education Services, 2025. https://doi.org/10.62311/nesx/rriv225.

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Abstract: Optimal control and reinforcement learning (RL) are foundational techniques for intelligent decision-making in robotics, automation, and AI-driven control systems. This research explores the theoretical principles, computational algorithms, and real-world applications of optimal control and reinforcement learning, emphasizing their convergence for scalable and adaptive robotic automation. Key topics include dynamic programming, Hamilton-Jacobi-Bellman (HJB) equations, policy optimization, model-based RL, actor-critic methods, and deep RL architectures. The study also examines traject
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Cook, Stephen, and Loyd Hook. Developmental Pillars of Increased Autonomy for Aircraft Systems. ASTM International, 2020. http://dx.doi.org/10.1520/tr2-eb.

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Increased automation for aircraft systems holds the promise to increase safety, precision, and availability for manned and unmanned aircraft. Specifically, established aviation segments, such as general aviation and light sport, could utilize increased automation to make significant progress towards solving safety and piloting difficulties that have plagued them for some time. Further, many emerging market segments, such as urban air mobility and small unmanned (e.g., small parcel delivery with drones) have a strong financial incentive to develop increased automation to relieve the pilot workl
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