UAVs joint optimization problems and machine learning to improve the 5G and Beyond communication

Ullah, Zaib; Al‐Turjman, Fadi; Moatasim, Uzair; Mostarda, Leonardo; Gagliardi, Roberto

doi:10.1016/j.comnet.2020.107478

Cited by 39 publications

(23 citation statements)

References 43 publications

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“…[15]. To enhance system efficiency, other technologies can be aggregated, such as artificial intelligence (machine learning or deep learning), mobile edge computing, and software-defined networks [16]. Associated with specialized sensors, UAVs are becoming powerful sensing systems that complement IoT-based techniques [15].…”

Section: Unmanned Aerial Equipment (Uav) or Dronesmentioning

confidence: 99%

“…Artificial neural networks have been used to reduce energy consumption [17]. Other artificial intelligence (AI) applications are related, for example, to the detection of diseases in crops, to distinguish plant or flower types [18], optimization for UAVs [16], and the detection of insects [19].…”

Section: Artificial Intelligence/data Driven Decisionsmentioning

confidence: 99%

“…On the right side, different approaches based on IoT solutions through digitalization of a "thing" [32] are shown. Each of these solutions can generate a huge amount of data, called big data [33,34], which is collected in real-time and processed by optimization AI-based algorithms for data driven decisions and other technologies [16,17], aiming at monitoring, measuring, tracking or controlling, allowing to improve production results [10,11,13,15,18,19,24,25,[35][36][37][38][39][40][41][42][43][44]. Block chain is an emerging technology and is con-sidered a solution for the cybersecurity of IoT devices [22].…”

Section: Iot In Agriculturementioning

confidence: 99%

See 2 more Smart Citations

Development of Technological Capabilities through the Internet of Things (IoT): Survey of Opportunities and Barriers for IoT Implementation in Portugal’s Agro-Industry

et al. 2021

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The agro-industrial sector consumes a significant amount of natural resources for farming and meat production. By 2050, population growth is expected, generating more demand and, consequently, more consumption of scarce resources. This challenging scenario is a concern of the European Commission, revealed in the Green Deal commitment and by the United Nations’ 12th goal of sustainable development. Thus, organizations must increase productivity and be more sustainable as soon as possible. Internet of Things (IoT) is introduced as a solution to facilitate agro-food companies to be more eco-efficient, mainly facing difficulties on farms, such as food loss and waste, best efficiency in management of resources, and production. The deployment of this technology depends on the stage of maturity and potential of implementation. To assess and characterize companies, with respect of IoT implementation, a survey was applied in 21 micro, small and medium agro-food companies, belonging to milk, honey, olive oil, jams, fruticulture, bakery and pastry, meat, coffee, and wine sectors, in the central region of Portugal. As results, this paper reveals the stage of maturity, level of sophistication, potential, opportunities, solutions, and barriers for implementation of IoT. Additionally, suggestions and recommendations to improve practices are discussed.

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Section: Unmanned Aerial Equipment (Uav) or Dronesmentioning

confidence: 99%

Section: Artificial Intelligence/data Driven Decisionsmentioning

confidence: 99%

Section: Iot In Agriculturementioning

confidence: 99%

See 1 more Smart Citation

Development of Technological Capabilities through the Internet of Things (IoT): Survey of Opportunities and Barriers for IoT Implementation in Portugal’s Agro-Industry

et al. 2021

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“…However, multiple challenges require further investigation, such as the high computational processing, high energy consumption, and high latency. A special focus on the algorithmic challenges involved in UAV-based networks was provided in the study of Ullah et al [114]. They investigated the joint optimization problem to enhance the system efficiency of UAV-assisted next-generation communication systems.…”

Section: A Surveys On Uav Flocks Creation Management and Coordinationmentioning

confidence: 99%

“…Bekmezci et al [50] Flying ad-hoc networks V V × Hayat et al [42] Civil applications V V × Hentati et al [45] Design issues V V + Boccadoro et al [85] Internet of Drones V + × Fotouhi et al [38] Standards of UAV based communications V × + Ullah et al [114] Optimizing communication efficiency V + V Mozaffari et al [79] UAV based communication V × + Saad et al [98] UAV based networks V + V Sharma et al [103] Networking technologies V × + Shakeri et al [101] Cyber-physical applications V V V Wang et al [116] Cyber UAV perspective V V V Alladi et al [111] Blockchain applications V × + Li et al [66] UAV communication V + V Oubbati et al [82] SDN and NFV for UAV assisted networks V V + Zhang et al [135] Air-Ground Integrated Networks V + + XiJun et al [28] UAV swarm communication V V + Bithas et al [16] ML for UAV communication systems V × V Carrio et al [19] Deep Learning for UAVs V × V Mao et al [89] Deep Learning for Wireless networks + + V Chen et al [25] ANNs for wireless networks V × V Zhang et al [23] Deep Learning for wireless networks × + V Kouhdaragh et al [57] ML for UAV-Based Networks Design V × V Alsami et al [5] AI for robotic communication V V V Al-Turjman et al [4] AI-based UAV communication system V × V Wu et al [119] Sensing and Intelligence V V V methods for UAV flock management. Our scope is in the intersection among ML, swarm intelligence (SI), and studies relating to UAVs, which none of the previous surveys have encompassed.…”

Section: A Surveys On Uav Flocks Creation Management and Coordinationmentioning

confidence: 99%

Machine Learning Methods for UAV Flocks Management-A Survey

Azoulay¹,

Haddad

Reches

2021

IEEE Access

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The development of unmanned aerial vehicles (UAVs) has been gaining momentum in recent years owing to technological advances and a significant reduction in their cost. UAV technology can be used in a wide range of domains, including communication, agriculture, security, and transportation. It may be useful to group the UAVs into clusters/flocks in certain domains, and various challenges associated with UAV usage can be alleviated by clustering. Several computational challenges arise in UAV flock management, which can be solved by using machine learning (ML) methods. In this survey, we describe the basic terms relating to UAVS and modern ML methods, and we provide an overview of related tutorials and surveys. We subsequently consider the different challenges that appear in UAV flocks. For each issue, we survey several machine learning-based methods that have been suggested in the literature to handle the associated challenges. Thereafter, we describe various open issues in which ML can be applied to solve the different challenges of flocks, and we suggest means of using ML methods for this purpose. This comprehensive review may be useful for both researchers and developers in providing a wide view of various aspects of state-of-the-art ML technologies that are applicable to flock management.

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5G smart antenna for IoT application: A review

Kishore

Senapati

2022

Int J Communication

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Summary The fifth generation of mobile technology is referred to as “5G.” 5G refers to the next significant phase of mobile communications standards after the upcoming 4G standards. With 5G technology, the bulk of high‐bandwidth consumers would be able to use their phones in innovative ways. When 5G is pushed over a VOIP‐enabled device, individuals encounter record levels of call volume and data transmission. In this paper, we reviewed smart antenna 5G for Internet of Things (IoT) application. Beamforming is a 5G active antenna technique that uses directional radio links to concurrently and selectively supply high bandwidth to certain mobile devices. Multi‐antenna systems are required when using larger frequency ranges. The better the propagation conditions for electromagnetic waves, the higher the frequency. To some extent, multi‐antenna arrays and beamforming can assist mitigate this. Radio signals can be transmitted and received in a spatially targeted manner due to beamforming. The better the beamforming works, the more dipoles (antenna elements) are available. In contrast to earlier eras on wireless networking, such as Global System For Mobile Communication (GSM), Universal Mobile Telecommunication System (UMTS), also 4G/LTE, 5G would not require major technological advances. Additional systems and equipment are added to the existing LTE technology to increase data capacity and reduce latency. The 5G NR infrastructure depends heavily on active antenna arrays, which enable multi‐user multiple‐in multiple‐out (MIMO) technologies. For targeted radio contact with the receiver, these antenna modules use beamforming.

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UAVs joint optimization problems and machine learning to improve the 5G and Beyond communication

Cited by 39 publications

References 43 publications

Development of Technological Capabilities through the Internet of Things (IoT): Survey of Opportunities and Barriers for IoT Implementation in Portugal’s Agro-Industry

Development of Technological Capabilities through the Internet of Things (IoT): Survey of Opportunities and Barriers for IoT Implementation in Portugal’s Agro-Industry

Machine Learning Methods for UAV Flocks Management-A Survey

5G smart antenna for IoT application: A review

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