@Article{B1,
AUTHOR = {Velusamy, Parthasarathy and Rajendran, Santhosh and Mahendran, Rakesh Kumar and Naseer, Salman and Shafiq, Muhammad and Choi, Jin-Ghoo},
TITLE = {Unmanned Aerial Vehicles (UAV) in Precision Agriculture: Applications and Challenges},
JOURNAL = {Energies},
VOLUME = {15},
YEAR = {2022},
NUMBER = {1},
ARTICLE-NUMBER = {217},
%URL = {https://www.mdpi.com/1996-1073/15/1/217},
ISSN = {1996-1073},
ABSTRACT = {Agriculture is the primary source of income in developing countries like India. Agriculture accounts for 17 percent of India’s total GDP, with almost 60 percent of the people directly or indirectly employed. While researchers and planters focus on a variety of elements to boost productivity, crop loss due to disease is one of the most serious issues they confront. Crop growth monitoring and early detection of pest infestations are still a problem. With the expansion of cultivation to wider fields, manual intervention to monitor and diagnose insect and pest infestations is becoming increasingly difficult. Failure to apply on time fertilizers and pesticides results in more crop loss and so lower output. Farmers are putting in greater effort to conserve crops, but they are failing most of the time because they are unable to adequately monitor the crops when they are infected by pests and insects. Pest infestation is also difficult to predict because it is not evenly distributed. In the recent past, modern equipment, tools, and approaches have been used to replace manual involvement. Unmanned aerial vehicles serve a critical role in crop disease surveillance and early detection in this setting. This research attempts to give a review of the most successful techniques to have precision-based crop monitoring and pest management in agriculture fields utilizing unmanned aerial vehicles (UAVs) or unmanned aircraft. The researchers’ reports on the various types of UAVs and their applications to early detection of agricultural diseases are rigorously assessed and compared. This paper also discusses the deployment of aerial, satellite, and other remote sensing technologies for disease detection, as well as their Quality of Service (QoS).},
DOI = {10.3390/en15010217}
}


@Article{B2,
title = {Review on the Technological Development and Application of UAV Systems},
journal = {Chinese Journal of Electronics},
volume = {29},
number = {2},
pages = {199-207},
year = {2020},
issn = {},
doi = {10.1049/cje.2019.12.006},	
%url = {https://cje.ejournal.org.cn/en/article/doi/10.1049/cje.2019.12.006},
author = {FAN Bangkui and LI Yun and ZHANG Ruiyu and FU Qiqi}
}


@article{B3,
    author = {Busulwa, Richard and Pathiranage, Nandana Wasantha and Pickering, Mark Edward},
    title = {Integration of critical digital technologies into hospitality and tourism curricula: evidence from QS-ranked universities},
    journal = {Journal of Hospitality and Tourism Technology},
    year = {2025},
    month = {05},
    abstract = {关键数字技术在酒店与旅游课程中的整合：QS排名大学的实证研究本研究旨在探讨关键既有与新兴数字技术（DTs）在酒店与旅游（H\&amp;T）管理学位课程及其不同类型课程中的整合程度, 评估其整合是否充分, 并发现改进整合的机会本研究采用定量内容分析方法, 对133个学位课程与748门课程的在线教学资料进行分析。教学资料包括课程描述、学习目标与成果、教学内容主题以及考核信息。尽管行业及商业功能相关的系统/应用已被较好地整合到课程中, 大多数关键既有数字技术的整合频率仍然偏低; 而关键新兴数字技术的整合程度则令人担忧地低。本研究提供了关键数字技术整合的实证证据, 揭示当前优势与不足, 并提出改进整合的建议。This study aims to investigate the extent to which critical established and emerging digital technologies (DTs) are integrated into hospitality and tourism (H\&amp;T) management degrees and into different types of H\&amp;T management subjects, as well as the sufficiency of this integration, and any integration improvement opportunities.The authors undertook quantitative content analysis of the online curricula artifacts of 133 H\&amp;T degrees and 748 H\&amp;T subjects. The online curricula artifacts included online subject descriptions, subject learning aims and learning outcomes, subject topic content and subject assessment information.The authors found that, while industry and business function-specific software systems/applications are well integrated into H\&amp;T curricula, most critical established DTs are rarely integrated, and integration of critical emerging DTs is alarmingly low.The authors provide empirical evidence of current critical DTs integration strengths and shortcomings and suggest integration improvement strategies.},
    issn = {1757-9880},
    doi = {10.1108/JHTT-06-2024-0388},
    %url = {https://doi.org/10.1108/JHTT-06-2024-0388},
    eprint = {https://www.emerald.com/jhtt/article-pdf/doi/10.1108/JHTT-06-2024-0388/9766061/jhtt-06-2024-0388.pdf},
}



@INPROCEEDINGS{B4,
  author={Sharma, Manish K. and Singal, Gaurav and Gupta, Suneet K. and Chandraneil, Basa and Agarwal, Saksham and Garg, Deepak and Mukhopadhyay, Debajyoti},
  booktitle={2021 6th International Conference for Convergence in Technology (I2CT)}, 
  title={INTERVENOR: Intelligent Border Surveillance using Sensors and Drones}, 
  year={2021},
  volume={},
  number={},
  pages={1-7},
  keywords={Target tracking;Surveillance;Terrorism;Intrusion detection;Sonar;Software;Servers;Autonomous Systems;Unmanned Aerial Vehicle;IoT;Sensor;Intrusion Detection System;Border Security;Artificial Intelligence},
  doi={10.1109/I2CT51068.2021.9418199}}


@article{B5,
author = {Aroosa Kanwal},
title ={Dreaming with drones: Palestine under the shadow of unseen war},
journal = {The Journal of Commonwealth Literature},
volume = {57},
number = {1},
pages = {240-258},
year = {2022},
doi = {10.1177/0021989420951839},
%URL = {https://doi.org/10.1177/0021989420951839},
eprint = {https://doi.org/10.1177/0021989420951839},
abstract = { This article discusses how the first-person genre, especially a Gazan wartime diary, allows both writer and reader to imagine new possibilities for understanding contemporary colonial drone warfare, which is instrumental in the strategic silencing and invisibilization of war victims. By creating this zone of invisibilization (one that I will name the “dronesphere”) through obfuscating loss of life, war perpetrators aim to drown out the voices of opposition and resistance in Gaza. This is precisely why an increasing autonomy of military technologies that I call the “anthropomorphizing of drones” has triggered fierce debates over the unaccountability for war crimes committed against those on the receiving end of such autonomous weaponry. One specific case that deserves serious attention in this regard is the deafening silence surrounding Israel’s use of lethal drones to assassinate people in Palestine, which has led to the strategic silencing and invisibility of Palestinian deaths and a struggle for survival through the use of top-down control via drones in the region. However, Atef Abu Saif’s use of “strategic anthropomorphism” in his wartime diary The Drone Eats with Me: A Gaza Diary does not grant the drone absolute autonomy in death-dealing but imagines Drone as a fictional character. Instead, the execution of Gazans is presented as a prolonged reconnaissance performance, which not only allows Gazans to see drones as an extension of (absent) drone operators’ bodies, but also to register their protest against the Israeli authorities by imagining Drone as a living entity. Therefore, using the authority of direct experience that Youval Noah Harari calls “flesh witnessing” (2008), Abu Saif’s wartime diary enables the formation of Palestinian subjectivities held under the sign of erasure, thereby claiming their rights as social and political human bodies. }
}


@article{B6,
author = {Dominika Kunertova},
title = {Drones have boots: Learning from Russia’s war in Ukraine},
journal = {Contemporary Security Policy},
volume = {44},
number = {4},
pages = {576--591},
year = {2023},
publisher = {Routledge},
doi = {10.1080/13523260.2023.2262792},
%URL = {https://doi.org/10.1080/13523260.2023.2262792},
eprint = {https://doi.org/10.1080/13523260.2023.2262792}
}



@Article{B19,
AUTHOR = {Ariante, Gennaro and Del Core, Giuseppe},
TITLE = {Unmanned Aircraft Systems (UASs): Current State, Emerging Technologies, and Future Trends},
JOURNAL = {Drones},
VOLUME = {9},
YEAR = {2025},
NUMBER = {1},
ARTICLE-NUMBER = {59},
%URL = {https://www.mdpi.com/2504-446X/9/1/59},
ISSN = {2504-446X},
ABSTRACT = {Unmanned aircraft, commonly referred to as drones, represent a valuable alternative for various operational tasks due to their versatility, flexibility, cost-effectiveness, and reusability. These features make them particularly advantageous in environments that are hazardous or inaccessible to humans. Recent developments have highlighted a significant increase in the use of unmanned aircraft within metropolitan areas. This growth has necessitated the implementation of new regulations and guidelines to ensure the safe integration of UAS into urban environments. Consequently, the concept of UAM has emerged. UAM refers to an innovative air transportation paradigm designed for both passengers and cargo within urban settings, leveraging the capabilities of drones. This review manuscript explores the latest advancements for UAS, focusing on updated regulations, definitions, enabling technologies, and airspace classifications relevant to UAM operations. Additionally, it provides a comprehensive overview of unmanned aircraft systems, including their classifications, key features, and primary applications.},
DOI = {10.3390/drones9010059}
}


@article{B7,
  title={Classifications, applications, and design challenges of drones: A review},
  author={Mostafa Hassanalian and Abdessattar Abdelkefi},
  journal={Progress in Aerospace Sciences},
  year={2017},
  volume={91},
  pages={99-131},
  %url={https://api.semanticscholar.org/CorpusID:114913580}
}


@article{B8,
author = {Omolara, Abiodun Esther and Alawida, Moatsum and Abiodun, Oludare Isaac},
title = {Drone cybersecurity issues, solutions, trend insights and future perspectives: a survey},
year = {2023},
issue_date = {Nov 2023},
publisher = {Springer-Verlag},
address = {Berlin, Heidelberg},
volume = {35},
number = {31},
issn = {0941-0643},
%url = {https://doi.org/10.1007/s00521-023-08857-7},
doi = {10.1007/s00521-023-08857-7},
abstract = {This paper presented an exhaustive survey on the security and privacy issues of drones. These security concerns were thoroughly dissected, particularly the aspect of cybersecurity, which was classified into nine levels. These levels include emerging issues, communication-based attacks, sensors, hardware, hardware-based attacks, software attacks, and physical attacks on the drone itself. Furthermore, we discussed the other non-cybersecurity challenges of drones, such as terrorism, mid-air collisions, illegal surveillance, smuggling, electronic snooping, and reconnaissance, alongside proffering possible solutions.&nbsp;Many of the discovered aspects of drone cybersecurity issues were then quantitatively analyzed using a multi-criteria decision-making problem-solving technique. The questionnaire responses from the general public, experts, and stakeholders in the aviation industry were analyzed. The findings revealed variations in cyber-attack techniques such as distributed denial-of-service (DDoS), denial-of-service (DoS), hacking, jamming, spoofing, electronic snooping, eavesdropping, advanced persistent threat (APT), reconnaissance, hijacking, man-in-the-middle attack, and so on. However, the majority of the participants in the survey, which constitute 70\%, were unaware of the existing drone cybersecurity challenges. The remaining 30\% were aware of the current drone security issues. Meanwhile, both parties are looking for an immediate solution that will fully provide an atmosphere of prospects in the drone industry. Following that, we presented our experience with drone security and privacy, as well as potential future research directions. This paper is unique in that it discusses the various types of drone cyber-attacks and non-cyber-attack scenarios that threaten the socio-economic system, aviation industry, national security, as well as public security and privacy concerns. It also offers solutions to the cyber-attack and non-cyber-attack cases that have been investigated. As a result, the findings of this study could be used to create, develop, and implement more secure cloud systems to safeguard drones from cyber and non-cyber-attacks.},
journal = {Neural Comput. Appl.},
month = aug,
pages = {23063–23101},
numpages = {39},
keywords = {Drone and cybersecurity, Drone cybersecurity challenges, Trending insight of cyber-attack, Internet of drone security, National security, Security and privacy and cyberspace future}
}


@inproceedings{B9,
author = {Mantas, Evangelos and Patsakis, Constantinos},
title = {GRYPHON: Drone Forensics in Dataflash and Telemetry Logs},
year = {2019},
isbn = {978-3-030-26833-6},
publisher = {Springer-Verlag},
address = {Berlin, Heidelberg},
%url = {https://doi.org/10.1007/978-3-030-26834-322},
abstract = {The continuous decrease in the price of Unmanned Aerial Vehicles (UAVs), more commonly known as drones, has pushed their adoption from military-oriented to a wide range of civilian and business applications. Nevertheless, the many features that they offer have started being maliciously exploited. The latter coupled with the fact that accidents or malicious acts may occur to drones has sparked the interest towards drones forensics.Trying to fill in the gap of the literature, this work focuses on a particular field of drone forensics that of forensics on the flight data logs. Therefore, we investigate one of the most widely used platforms, Ardupilot and the dataflash and telemetry logs. In this work, we discuss a methodology for collecting the necessary information, analysing it, and constructing the corresponding timeline. In this regard, we have developed an open source tool that is freely available and tested it on data provided by VTO Labs.},
booktitle = {Advances in Information and Computer Security: 14th International Workshop on Security, IWSEC 2019, Tokyo, Japan, August 28–30, 2019, Proceedings},
pages = {377–390},
numpages = {14},
keywords = {Log files, Ardupilot, Forensics, Drone, UAV},
location = {Tokyo, Japan}
}


@article{B10,
author = {Clark, Devon R. and Meffert, Christopher and Baggili, Ibrahim and Breitinger, Frank},
title = {DROP (DRone Open source Parser) your drone},
year = {2017},
issue_date = {August 2017},
publisher = {Elsevier Science Publishers B. V.},
address = {NLD},
volume = {22},
number = {S},
issn = {1742-2876},
%url = {https://doi.org/10.1016/j.diin.2017.06.013},
doi = {10.1016/j.diin.2017.06.013},
abstract = {The DJI Phantom III drone has already been used for malicious activities (to drop bombs, remote surveillance and plane watching) in 2016 and 2017. At the time of writing, DJI was the drone manufacturer with the largest market share. Our work presents the primary thorough forensic analysis of the DJI Phantom III drone, and the primary account for proprietary file structures stored by the examined drone. It also presents the forensically sound open source tool DRone Open source Parser (DROP) that parses proprietary DAT files extracted from the drone's nonvolatile internal storage. These DAT files are encrypted and encoded. The work also shares preliminary findings on TXT files, which are also proprietary, encrypted, encoded, files found on the mobile device controlling the drone. These files provided a slew of data such as GPS locations, battery, flight time, etc. By extracting data from the controlling mobile device, and the drone, we were able to correlate data and link the user to a specific device based on extracted metadata. Furthermore, results showed that the best mechanism to forensically acquire data from the tested drone is to manually extract the SD card by disassembling the drone. Our findings illustrated that the drone should not be turned on as turning it on changes data on the drone by creating a new DAT file, but may also delete stored data if the drone's internal storage is full.},
journal = {Digit. Investig.},
month = aug,
pages = {S3–S14},
numpages = {12},
keywords = {Computer forensics, Cyber forensics, DAT file structure, DJI, DJI Phantom III, Digital forensics, Drone, Drone forensics, Embedded systems forensics, IoT forensics, Mobile forensics, Open source DRone Parser, Phantom III, TXT file structure, UAV, UAV forensics}
}


@Article{B11,
AUTHOR = {Zhao, Ziyu and Wang, Yongquan and Liao, Genwei},
TITLE = {Digital Forensic Research for Analyzing Drone and Mobile Device: Focusing on DJI Mavic 2 Pro},
JOURNAL = {Drones},
VOLUME = {8},
YEAR = {2024},
NUMBER = {7},
ARTICLE-NUMBER = {281},
%URL = {https://www.mdpi.com/2504-446X/8/7/281},
ISSN = {2504-446X},
ABSTRACT = {With the frequent occurrence of drone-related criminal cases, drone forensics has become a hot spot of concern. During drone-related criminal investigations, the implicated drones are often forcibly brought down, which poses significant challenges in conducting forensic analysis. In order to restore the truth of criminal cases, it is necessary to extract data not only from the external TF card but also from internal chip memory in drone forensics. To address this issue, a drone data parser (DRDP) is proposed to extract internal and external data from criminal-implicated drones. In this paper, we present comprehensive forensics on the DJI Mavic 2 Pro, analyzing the main file structure and encryption model. According to its file structures, three case studies are conducted on various file types (DAT files, TXT files, and default files) to verify the effectiveness and applicability of the designed procedure. The results show that the encrypted data of the implicated drone, such as GPS information, flight time, flight altitude, flight distance, three velocity components (x, y, z) and other information can be extracted and decrypted correctly, which provides evidence for the identification of the case facts.},
DOI = {10.3390/drones8070281}
}


@INPROCEEDINGS{B12,
  author={Mohammed, Abdul Sami and Abul Hasanaath, Ahmed and Moinuddeen, AbuMuhammad and Mohammad, Nazeeruddin},
  booktitle={2023 International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT)}, 
  title={A Comparative Study of Drone Forensic Tools and Techniques}, 
  year={2023},
  volume={},
  number={},
  pages={752-758},
  keywords={Forensics;Surveillance;Cellular phones;Wildlife;Machine learning;Internet of Things;Data communication;Unmanned Aerial Vehicles;Drone Security;Machine Learning;Drone Forensics},
  doi={10.1109/IDCIoT56793.2023.10053530}}


@article{B13,
author = {Mohsan, Syed Agha Hassnain and Othman, Nawaf Qasem Hamood and Li, Yanlong and Alsharif, Mohammed H. and Khan, Muhammad Asghar},
title = {Unmanned aerial vehicles (UAVs): practical aspects, applications, open challenges, security issues, and future trends},
year = {2023},
issue_date = {Mar 2023},
publisher = {Springer-Verlag},
address = {Berlin, Heidelberg},
volume = {16},
number = {1},
issn = {1861-2776},
%url = {https://doi.org/10.1007/s11370-022-00452-4},
doi = {10.1007/s11370-022-00452-4},
abstract = {Recently, unmanned aerial vehicles (UAVs) or drones have emerged as a ubiquitous and integral part of our society. They appear in great diversity in a multiplicity of applications for economic, commercial, leisure, military and academic purposes. The drone industry has seen a sharp uptake in the last decade as a model to manufacture and deliver convergence, offering synergy by incorporating multiple technologies. It is due to technological trends and rapid advancements in control, miniaturization, and computerization, which culminate in secure, lightweight, robust, more-accessible and cost-efficient UAVs. UAVs support implicit particularities including access to disaster-stricken zones, swift mobility, airborne missions and payload features. Despite these appealing benefits, UAVs face limitations in operability due to several critical concerns in terms of flight autonomy, path planning, battery endurance, flight time and limited payload carrying capability, as intuitively it is not recommended to load heavy objects such as batteries. As a result, the primary goal of this research is to provide insights into the potentials of UAVs, as well as their characteristics and functionality issues. This study provides a comprehensive review of UAVs, types, swarms, classifications, charging methods and regulations. Moreover, application scenarios, potential challenges and security issues are also examined. Finally, future research directions are identified to further hone the research work. We believe these insights will serve as guidelines and motivations for relevant researchers.},
journal = {Intell. Serv. Robot.},
month = jan,
pages = {109–137},
numpages = {29},
keywords = {UAVs, Path planning, Batteries, Charging, Swarms, Applications}
}


@article{B14,
author = {Alotaibi, Fahad Mazaed and Al-Dhaqm, Arafat and Al-Otaibi, Yasser D.},
title = {A Novel Forensic Readiness Framework Applicable to the Drone Forensics Field},
journal = {Computational Intelligence and Neuroscience},
volume = {2022},
number = {1},
pages = {8002963},
doi = {https://doi.org/10.1155/2022/8002963},
%url = {https://onlinelibrary.wiley.com/doi/abs/10.1155/2022/8002963},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1155/2022/8002963},
abstract = {The Drone Forensics (DRFs) field is a branch of digital forensics, which involves the identification, capture, preservation, reconstruction, analysis, and documentation of drone incidents. Several models have been proposed in the literature for the DRF field, which generally discusses DRF from a reactive forensic perspective; however, the proactive forensic perspective is missing. Therefore, this paper proposes a novel forensic readiness framework called Drone Forensics Readiness Framework (DRFRF) using the design science method. It consists of two stages: (i) proactive forensic stage and (ii) reactive forensic stage. It considers centralized logging of all events of all the applicants within the drone device in preparation for an examination. It will speed up gathering data when an investigation is needed, permitting the forensic investigators to handle the examination and analysis directly. Additionally, digital forensics analysts can increase the possible use of digital evidence while decreasing the charge of performing forensic readiness. Thus, both the time and cost required to perform forensic readiness could be saved. The completeness, logicalness, and usefulness of DRFRF were compared to those of other models already existing in the DRF domain. The results showed the novelty and efficiency of DRFRF and its applicability to the situations before and after drone incidents.},
year = {2022}
}


@INPROCEEDINGS{B15,
  author={Yousef, Maryam and Iqbal, Farkhund},
  booktitle={2019 IEEE/ACS 16th International Conference on Computer Systems and Applications (AICCSA)}, 
  title={Drone Forensics: A Case Study on a DJI Mavic Air}, 
  year={2019},
  volume={},
  number={},
  pages={1-3},
  keywords={Drones;Tools;Mobile handsets;Digital forensics;Aircraft;Data mining;Drone;UAV;DJI Mavic Air;Digital Forensics;Drone Forensics;Forensic Investigations;Mobile forensics},
  doi={10.1109/AICCSA47632.2019.9035365}}



@Article{B16,
AUTHOR = {Salamh, Fahad E. and Karabiyik, Umit and Rogers, Marcus K.},
TITLE = {RPAS Forensic Validation Analysis Towards a Technical Investigation Process: A Case Study of Yuneec Typhoon H},
JOURNAL = {Sensors},
VOLUME = {19},
YEAR = {2019},
NUMBER = {15},
ARTICLE-NUMBER = {3246},
%URL = {https://www.mdpi.com/1424-8220/19/15/3246},
PubMedID = {31344784},
ISSN = {1424-8220},
ABSTRACT = {The rapid pace of invention in technology and the evolution of network communication has produced a new lifestyle with variety of opportunities and challenges. Remotely Piloted Aerial Systems (RPAS) technology, which includes drones, is one example of a recently invented technology that requires the collection of a solid body of defensible and admissible evidence to help eliminate potential real-world threats posed by their use. With the advent of smartphones, there has been an increase in digital forensic investigation processes developed to assist specialized digital forensic investigators in presenting forensically sound evidence in the courts of law. Therefore, it is necessary to apply digital forensic techniques and procedures to different types of RPASs in order to create a line of defense against new challenges, such as aerial-related incidents, introduced by the use of these technologies. Drone operations by bad actors are rapidly increasing and these actors are constantly developing new approaches. These criminal operations include invasion of privacy, drug smuggling, and terrorist activities. Additionally, drone crashes and incidents raise significant concerns. In this paper, we propose a technical forensic process consisting of ten technical phases for the analysis of RPAS forensic artifacts, which can reduce the complexity of the identification and investigation of drones. Using the proposed technical process, we analyze drone images using the Computer Forensics Reference Datasets (CFReDS) and present results for the Typhoon H aerial vehicle manufactured by Yuneec, Inc. Furthermore, this paper explores the availability and value of digital evidence that would allow a more practical digital investigation to be able to build an evidence-based experience. Therefore, we particularly focus on developing a technical drone investigation process that can be applied to various types of drones.},
DOI = {10.3390/s19153246}
}


@article{B17,
author = {Kao, Da-Yu and Chen, Min-Ching and Wu, Wen-Ying and Lin, Jsen-Shung and Chen, Chien-Hung and Tsai, Fuching},
title = {Drone Forensic Investigation: DJI Spark Drone as A Case Study},
year = {2019},
issue_date = {2019},
publisher = {Elsevier Science Publishers B. V.},
address = {NLD},
volume = {159},
number = {C},
issn = {1877-0509},
%url = {https://doi.org/10.1016/j.procs.2019.09.361},
doi = {10.1016/j.procs.2019.09.361},
journal = {Procedia Comput. Sci.},
month = jan,
pages = {1890–1899},
numpages = {10},
keywords = {Drone forensics, Digital forensics, Time Synchronization, DJI Spark}
}



@INPROCEEDINGS{B18,
  author={Barton, Thomas Edward Allen and Hannan Bin Azhar, M.A.},
  booktitle={2017 Seventh International Conference on Emerging Security Technologies (EST)}, 
  title={Forensic analysis of popular UAV systems}, 
  year={2017},
  volume={},
  number={},
  pages={91-96},
  keywords={Drones;Forensics;Phantoms;Mobile communication;Media;Tools;Workstations;digital forensics;drone forensics;Linux;DJI Phantom;AR Drone 2.0;open source tools},
  doi={10.1109/EST.2017.8090405}}


@INPROCEEDINGS{B19,
  author={Yousef, Maryam and Iqbal, Farkhund and Hussain, Mohammed},
  booktitle={2020 11th International Conference on Information and Communication Systems (ICICS)}, 
  title={Drone Forensics: A Detailed Analysis of Emerging DJI Models}, 
  year={2020},
  volume={},
  number={},
  pages={066-071},
  keywords={Analytical models;Law enforcement;Forensics;Atmospheric modeling;Phantoms;Data mining;Sparks;Drones;UAV;Digital Forensics;Drone Forensics;Mobile Forensics},
  doi={10.1109/ICICS49469.2020.239530}}













