An Architecture for Real Time Monitoring Aerial Adhoc Network

Qazi, Sameer; Alvi, Arsalan Ahmad; Qureshi, Adil Mazhar; Khawaja, Bilal A.; Mustaqim, Muhammad

doi:10.1109/fit.2015.36

Cited by 12 publications

(5 citation statements)

References 9 publications

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“…Based on the UAVs' flight speed, altitude, density, angle of arrival, and transmission range, the authors of refs. [31][32][33] examined the performance of UAV networks. The connectivity between UAVs and between UAVs and MGNs determines how well the UAV network performs.…”

Section: Literature Reviewmentioning

confidence: 99%

A constructive airborne‐ground matrix algorithm for modern telecommunication systems

Arun Raj A,

Xavier S,

Kathrine G

et al. 2023

IET Networks

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Conventional Mobile Communication Systems (MCS) reliably transfer critical messages from authorised remote information sources like military bases and ground control stations in the war field. As tactical advancement grows rapidly, the challenges of transmitting tactical messages via conventional satellite methods increase the processing overhead related to cost, Line of Sight (LOS) communication, packet loss, delay, and retransmission requests. Modern mobile communication systems use Airborne Node Networks (ANN) between satellites and Mobile Ground Nodes (MGNs) as they provide many advantages in mobile communication systems. Hence airborne network reduces the burden of satellites as they are only used as relay stations. The mobility problem caused by ANN and MGNs is solved by proposing a novel constructive airborne‐ground matrix algorithm known as the Who‐To‐Whom (WTW) matrix. With the help of this matrix acting as a reference index, it determines which nodes relate to whom at every time interval T in the tactical environment. This WTW matrix holds precise status/information about connectivity among all stakeholders in the operating environment by carefully and effectively accounting for frequent location changes. The methodology of the proposed matrix is that it contains the physical parameters of the nodes and their behaviour in the tactical environment. The WTW matrix construction algorithm discusses how the reference matrix is constructed in every aerial node to monitor the mobile ground nodes by leading them to safety and providing aerial guidance as they move along the tactical environment. The performance metrics are measured with other existing schemes, and the merits and demerits of the proposed WTW matrix are identified and discussed in detail.

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Section: Literature Reviewmentioning

confidence: 99%

A constructive airborne‐ground matrix algorithm for modern telecommunication systems

Arun Raj A,

Xavier S,

Kathrine G

et al. 2023

IET Networks

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“…UAVs for smart cities surveillance in real-time have been proposed previously [11]- [12]. The use of UAVs in smart farming is also being explored by researchers [13].…”

Section: Related Workmentioning

confidence: 99%

“…3. Future smart agriculture machinery like drones will frequently be having flights covering huge areas, and real-time communication with such drones/UAVs could only be with the help of cellular networks [11]. Newer cellular technologies such as 4G LTE, 5G, and B5G are not only facilitating large communication ranges but also permit large data transmission capability, which will be suitable for applications like realtime video transmission from agriculture drones [12,104].…”

Section: Ixcellular Technologiesmentioning

confidence: 99%

IoT-Equipped and AI-Enabled Next Generation Smart Agriculture: A Critical Review, Current Challenges and Future Trends

2022

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Smart agriculture techniques have recently seen widespread interest by farmers. This is driven by several factors, which include the widespread availability of economically-priced, low-powered Internet of Things (IoT) based wireless sensors to remotely monitor and report conditions of the field, climate, and crops. This enables efficient management of resources like minimizing water requirements for irrigation and minimizing the use of toxic pesticides. Furthermore, the recent boom in Artificial Intelligence can enable farmers to deploy autonomous farming machinery and make better predictions of the future based on present and past conditions to minimize crop diseases and pest infestation. Together these two enabling technologies have revolutionized conventional agriculture practices. This survey paper provides: (a) A detailed tutorial on the available advancements in the field of smart agriculture systems through IoT technologies and AI techniques; (b) A critical review of these two available technologies and challenges in their widespread deployment; and (c) An in-depth discussion about the future trends including both technological and social when smart agriculture systems will be widely adopted by the farmers globally.

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“…Mustaqim et al [22] examined the UAV-to-UAV and UAV-to-ground communication in a FANET environment using wideband and high-gain antenna arrays. Qazi et al [23] proposed an architecture which is well-suited for UAV-based surveillance. Further, they examined line of sight (LoS) and nonline of sight (NLoS) propagation in aerial ad hoc networks, especially when UAVs are flying at very low-speed and altitudes.…”

Section: Related Workmentioning

confidence: 99%

SCRAS Server-Based Crosslayer Rate-Adaptive Video Streaming over 4G-LTE for UAV-Based Surveillance Applications

et al. 2019

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This research focuses on intelligent unmanned aerial vehicle (UAV)-based, real-time video surveillance to ensure better monitoring and security of remote locations over 4G-LTE cellular networks by maximizing end-user quality of experience (QoE). We propose a novel server-based crosslayer rate-adaptive scheme (SCRAS) for real-time video surveillance over 4G-LTE networks using UAVs. Our key contributions are: (1) In SCRAS, mobile UAVs having preprogrammed flight co-ordinates act as servers, streaming real-time video towards a remote client; (2) server-side video rate adaptation occurs in 4G-LTE based on the physical characteristics of the received signal conditions due to variations in the wireless channel and handovers; (3) SCRAS is fully automated and independent of client assistance for rate adaptation, as it is intended for real-time, mission-critical surveillance applications; (4) SCRAS ensures that during rate adaptation, the current video frame should not be damaged by completing the current group of packet (GoP) before adaptation. Our simulations in NS3 provide credible evidence that SCRAS outperforms recently proposed schemes in providing better QoE for real-time, rate-adaptive, video surveillance over 4G-LTE under varying channel quality and frequent handovers that occur during flight by UAVs.

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An Architecture for Real Time Monitoring Aerial Adhoc Network

Cited by 12 publications

References 9 publications

A constructive airborne‐ground matrix algorithm for modern telecommunication systems

A constructive airborne‐ground matrix algorithm for modern telecommunication systems

IoT-Equipped and AI-Enabled Next Generation Smart Agriculture: A Critical Review, Current Challenges and Future Trends

SCRAS Server-Based Crosslayer Rate-Adaptive Video Streaming over 4G-LTE for UAV-Based Surveillance Applications

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