Ultra-Reliable Low-Latency Communications: Unmanned Aerial Vehicles Assisted Systems
Abstract
:1. Introduction
- 1
- Introducing the main requirements and challenges associated with the uRLLC of the 5G/6G network.
- 2
- Providing AR/VR as a use case of the uRLL applications.
- 3
- Using UAVs to assist uRLL 5G/6G applications.
- 4
- Integrating SDN and MEC with UAVs to support uRLLC.
- 5
- Providing the current state-of-the-art and future directions of UAV-based networks for uRLLC.
2. uRLL 5G/6G Applications
- 1
- Smart Factories: The use of devices and precision are controlled in real time for rapid production and facilitating the recycling process in factories. The presence of many production lines represents a great challenge in terms of latency and reliability. Therefore, most services require very low latency, up to 5 milliseconds. Such application has great interest with the announcement of the industry 4.0 paradigm [25,26].
- 2
- Intelligent Transportation Systems: Autonomous driving and traffic facilitation require a scalable infrastructure, highly reliable communication with very low latency, and special stations to achieve road safety. The maximum permissible latency for most of the vehicular applications is 5 milliseconds [27,28].
- 3
- Robots and remote control: As an example of robots and remote control, the remote surgical operation in places affected by natural and industrial disasters protects the human element in the shortest possible time [29]. It is used to discover mines and dismantle explosive devices to reduce the loss of life. Many recently introduced teleoperations require a communication network with ultra-low latency communications.
- 4
- Virtual Reality (VR): Many applications requiring very high data processing sensitivity and accuracy, such as remote surgery, need VR technology. VR simulates with a common tactile structure in a very low time. Supporting these services requires a very low response time [30].
- 5
- Augmented Reality (AR): AR technology has made its way into several applications, including distance education, medical services, gaming, smart cities, and the training of firefighters to face fires without human losses [31]. Such applications require an end-to-end latency of 5 milliseconds at maximum [32]. This is to achieve the required quality of experience (QoE).
- 6
- Healthcare: This includes remote surgery, remote diagnosis and performing dangerous operations using human-assisted robot systems. Such applications are based on real-time communications that should be achieved at a very low latency [33]. This is to transfer the human sense to haptic-based robots with maximum experience. Such applications require an end-to-end latency between 1 and 5 milliseconds [34].
- 7
- Smart grids: Smart grids have important requirements in terms of reliability and latency, so it requires a very low latency to keep pace with these requirements and the applications in which smart grids are used [35].
- 8
- Tactile Internet: It represents the fourth wave of the traditional internet that enables the transfer of human sense and actuation in real time. The main application that the Tactile Internet will support is haptic communications that require an end-to-end latency of one millisecond at maximum [36]. Such latency challenge is due to the physical parameters associated with the human senses as introduced in [37].
3. Augmented and Virtual Reality (AR/VR)
3.1. Main Use Cases of AR Technology
- Educational applications: Some countries and organizations have been forced to use modern technologies, such as AR and VR, to teach and motivate students through educational content to combine facts with the virtual. Such organizations address traditional methods accompanied by boredom in accepting ancient and modern cultural information [45,46]. AR technology greatly contributes to the educational aspect in a way that helps both the student and the teacher. The students have become greatly involved in interactive learning and improved perception and understanding [46]. With the recent progress in smartphone and smart device manufacturing, new technologies support the augmented reality feature, such as the barometer and accelerometer, facilitating the use of new tools and technologies in education [47].Cultural and civilizational heritage is one of the most common educational branches that use AR as a main technology [48]. Using human senses, such as hearing, touch, and others, improves facts and provides users with information about cultural and historical heritage [49]. AR is used to improve the education process in studies of the ancient cultural and civilizational heritage of a particular country by transferring generations to simulate the ancient world; the knowledge of the ancient historical customs, traditions, and ancient civilizational buildings now become more developed, less expensive and increase the student’s concentration more than virtual reality technology. The use of some devices, such as screens installed on the head, smartphones, also special lenses and glasses that support the augmented reality feature, in showing the ancient civilizations by displaying ancient warriors to the real world as well as adding buildings, historical museums, architectural artifacts and verifying their structure is an example [50].
- Industrial applications: AR can be used to automate industrial processes and develop modern technologies to increase the production and the sales process. Using AR, buyers can make the purchase decision more wisely and helps the company to modify or add the product before buying. It helps companies to customize the products and the needs required by the customers and reduces the time to deliver products to the customer [51]. AR can also reduce operating hours, increase product lines’ flexibility, and improve product development and quality [52].AR is used in maintenance, quality and production lines enhancement for users. It reduces cost and time, as it does not require the presence of experts on the site by means of augmented reality technology assistance [51]. It is also used to improve the safety of the user in the use of robots while they are in dangerous places and places of accidents that are difficult for humans to reach and deal with, providing a three-dimensional image of the situation through robots in real time for the occurrence of risks [53].AR technology has helped many industries, including architecture, utilities, construction, energy, logistics and many other industries, and played an important role in their production and the installation of modern technology in their production lines [54]. Augmented reality technology helps some devices, including head-mounted screens, e.g., helmets and smartphones.
- Tracking applications: AR technology assisted the tracking process, increased the use of natural feature tracking (NFT) techniques in real-time virtual image detection, and facilitated the process of optimizing methods and locations [55]. It can assist with simultaneous localization and mapping (SLAM) guides, robots moving for the first time, and reducing delays in responding and executing things in real time [56].
- Military applications: AR has been used extensively in many areas that integrate real, virtual environments and real-time implementation, such as army exercises, where field equipment is trained and repaired, and soldiers are warned of the risks that may occur during battle. It enables virtual maps to help confront the enemy and simulate real reality, reducing the cost and time used in training [57,58].
- Entertainment and gaming applications: AR has many applications in 3D weather prediction. It is also used in concerts and cinemas at large scales [59]. Recently, AR was used to assist in broadcasting football matches and other sporting events [60]. Another common application of AR technology is online gaming, which represents a promising application. It gained much interest with the advances in the haptic devices used in online gaming [61].
- Healthcare applications: AR enables doctors to provide medical assistance during dangerous surgeries. Using AR, doctors can be trained to visualize critical emergencies during surgeries and treat them before they occur without causing loss of life when an unexpected problem occurs [62]. Moreover, AR can be used to provide medications remotely and provides the necessary data for medications [63].
3.2. Main Use Cases of VR
- Educational applications: The emergence of VR technology played a very important role in the education process, which became complex with the emergence of many modern curricula. Most countries turned to use modern technologies that depend on technological development in education to keep pace with the modern education process. However, this is no longer sufficient to facilitate understanding, except for the role of virtual reality in developing the education process in engineering, medicine and many other fields. Teaching methods became interesting and attractive to the learner and increased their acquisition of knowledge, skills and values that help to understand life and work [64].VR provides an interactive virtual environment using the computer that transfers the learner to a virtual environment that simulates reality to help them understand most fields such as medicine, psychology and cultural history [65]. Using VR to provide knowledge in certain areas, such as science and history, and to support students in acquiring knowledge of practical facts and theories that are difficult to assimilate in the old ways has gained great attention in recent years. Moreover, VR can be used in the education of history by simulating historical events, places, and their behavior in training to visualize the occurrence of people in emergencies, such as fighting fires, floods, volcanoes, road accidents, and many others [66].VR technology has many applications in simulation processes for learning applied sciences, engineering disciplines, and medical studies. The emergence of VR helped engineers choose the best design methods early, allowing them to decide before creating them [67] in order to reduce cost and change customer requirements before implementation, which helps reduce time, and also develop training processes for engineering disciplines, such as mechatronics and others [68].Medical virtual reality has become very important in our world. It helps doctors and students to practice the medical field on a daily basis, which increases the quality of medical skills. Doctors have developed early predictions of dangerous diseases by simulating virtual things with real-life scenarios. It enabled them to understand the complexity of the heart system. Moreover, doctors have trained on how to recover and save the lives of accident patients in a very fast way. VR has been used in training to perform critical surgeries that require intense concentration, such as the eye, heart, and others that seriously affect the patient’s life [69,70].
- Space applications: The emergence of virtual reality technology helped astronomers explain natural phenomena, simulate reality and understand the solar system by creating a three-dimensional model. It helped astronomers with the ability at any time and under any conditions to travel to outer space in a virtual world without cost and create an experience to train learners and their knowledge of the universe [71].
- Medical applications: The presence of virtual reality technology has helped the field of medical diagnosis to the highest levels, as the doctors were relieved of pressure during critical surgeries. The patient was visualized in virtual reality and diagnosed at the highest level; sudden changes were simulated during the patient’s aid, as well as good planning for surgery and reducing pain during surgery and diagnosis. It is great in the treatment of dangerous and widespread modern diseases, such as breast cancer, colon cancer, Alzheimer’s disease and many other different diseases, using video imaging through modern technologies and artificial intelligence devices, such as devices attached to the head and other sensors, such as lenses and others.For breast cancer, virtual reality has been introduced to reduce or limit the use of traditional methods, such as chemotherapy and radiation, to treat breast cancer or surgery that causes severe pain to the patient and increase anxiety as a result of harmful radiation to which they are exposed. Virtual reality solved the problem by providing a virtual headset to the patient that displays videos that help the patient to acclimate to situations that cause them anxiety, tension and pain, and providing information about their condition that they can easily understand. Finally, the physicists helped improve the drug dramatically by testing the drug with malignant cells before using it [72,73].Colon cancer is considered one of the most dangerous diseases currently in the world for women and men. The traditional treatment methods become more difficult and cause pain and anxiety for the patient. It has become difficult to assess the situation efficiently during the live broadcast. Therefore, they forced researchers and doctors to use virtual reality via virtual simulators. They have the ability to report information about the patient’s condition, such as the visible mucous membrane, the detection rate of polyps, and others. Virtual colonoscopy has become an ideal solution instead to optical colonoscopy, which uses computed tomography, which is considered a blurring image for diagnosis [74,75].Alzheimer’s disease is a disease of the age that causes disturbances in the brain, causing damage to the memory system. Virtual reality trains the patient to target things by default and improves the patient’s driving skills significantly. In addition, it helps them to perceive things at home, in their daily life and in the early detection of Alzheimer’s disease using the virtual reality maze test by testing specific cells of the brain to detect the disease early and test the strength of memory [76].The benefit of virtual reality in medical diagnosis and cognitive rehabilitation is to avoid sudden illnesses, such as stroke. It is used in physical therapy by visualizing the patient’s movements in a virtual game instead of treating them in difficult gyms. It also gives doctors the freedom to perform surgeries in a virtual environment to simulate errors that could immediately be resolved by a computer [77]. It simulates real errors during the patient’s diagnosis and works to increase the patient’s physical and psychological comfort, reducing costs and providing health care. The use of virtual reality provides the interaction between reality (existence), virtual environments and the user’s senses.
4. Specifications and Main Requirements of AR/VR Systems
5. Challenges with AR/VR Systems
6. Unmanned Aerial Vehicles for uRLLC
6.1. UAVs for uRLLC Applications
- Industrial Internet of things (IIoT): UAVs can be used to increase production, monitor industrial areas, and control production processes in dangerous places. IoT-based industrial systems, e.g., industry 4.0, can use UAVs to support the communication network by providing the required coverage and latency [95].
- Augmented reality and virtual reality (AR/VR): Deploying UAVs for AR/VR systems, users can see real video from high altitudes with very good quality. The use of unmanned aerial vehicles in the market helped virtual reality technology in the purchase decision process by offering the best product to the buyer [96].
- Real-Time Monitoring: UAVs are used to monitor road traffic, regulate traffic, and reduce road density by sending directions to control towers and traffic lights by collecting road traffic information and sending it to act. UAVs are used in monitoring railways and highways to facilitate road management and achieve a high level of safety [97].
- Lifeline applications: Unmanned aerial vehicles can be used as an air station to receive data in hard-to-reach places and places of volcanoes and earthquakes. It is able to provide real-time communications in such hard situations. It monitors and forecasts areas affected by natural disasters. It works to preserve protected areas and forests. It monitors borders and arrests terrorists and outlaws. It also works in search-and-rescue operations against destructive activities affecting the state [98].
6.2. UAVs for AR/VR Systems
6.3. UAVs-Based Framework to Assist uRLL Applications
7. Distributed Edge Computing for uRLLC
8. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Popovski, P.; Stefanović, Č.; Nielsen, J.J.; De Carvalho, E.; Angjelichinoski, M.; Trillingsgaard, K.F.; Bana, A.S. Wireless access in ultra-reliable low-latency communication (URLLC). IEEE Trans. Commun. 2019, 67, 5783–5801. [Google Scholar] [CrossRef]
- Bhat, J.R.; Alqahtani, S.A. 6G ecosystem: Current status and future perspective. IEEE Access 2021, 9, 43134–43167. [Google Scholar] [CrossRef]
- Salah, I.; Mabrook, M.M.; Hussein, A.I.; Rahouma, K.H. Comparative study of efficiency enhancement technologies in 5G networks-A survey. Procedia Comput. Sci. 2021, 182, 150–158. [Google Scholar] [CrossRef]
- Ateya, A.A.; Muthanna, A.; Makolkina, M.; Koucheryavy, A. Study of 5G services standardization: Specifications and requirements. In Proceedings of the 2018 10th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), Moscow, Russia, 5–9 November 2018; pp. 1–6. [Google Scholar]
- Park, J.H.; Rathore, S.; Singh, S.K.; Salim, M.M.; Azzaoui, A.; Kim, T.W.; Pan, Y.; Park, J.H. A comprehensive survey on core technologies and services for 5G security: Taxonomies, issues, and solutions. Hum.-Centric Comput. Inf. Sci 2021, 11, 3. [Google Scholar] [CrossRef]
- Ali, R.; Zikria, Y.B.; Bashir, A.K.; Garg, S.; Kim, H.S. URLLC for 5G and beyond: Requirements, enabling incumbent technologies and network intelligence. IEEE Access 2021, 9, 67064–67095. [Google Scholar] [CrossRef]
- Park, J.; Samarakoon, S.; Shiri, H.; Abdel-Aziz, M.K.; Nishio, T.; Elgabli, A.; Bennis, M. Extreme ultra-reliable and low-latency communication. Nat. Electron. 2022, 5, 133–141. [Google Scholar] [CrossRef]
- Ye, S. Support of ultra-reliable and low-latency communications (URLLC) in NR. In 5G and Beyond; Springer: Berlin/Heidelberg, Germany, 2021; pp. 373–400. [Google Scholar]
- Feng, D.; Lai, L.; Luo, J.; Zhong, Y.; Zheng, C.; Ying, K. Ultra-reliable and low-latency communications: Applications, opportunities and challenges. Sci. China Inf. Sci. 2021, 64, 120301. [Google Scholar] [CrossRef]
- Bermejo, C.; Hui, P. A survey on haptic technologies for mobile augmented reality. ACM Comput. Surv. (CSUR) 2021, 54, 1–35. [Google Scholar] [CrossRef]
- Shahraki, A.; Abbasi, M.; Piran, M.; Taherkordi, A. A comprehensive survey on 6G networks: Applications, core services, enabling technologies, and future challenges. arXiv 2021, arXiv:2101.12475. [Google Scholar]
- Alraih, S.; Shayea, I.; Behjati, M.; Nordin, R.; Abdullah, N.F.; Abu-Samah, A.; Nandi, D. Revolution or evolution? Technical requirements and considerations towards 6G mobile communications. Sensors 2022, 22, 762. [Google Scholar] [CrossRef]
- Ray, P.P. A review on 6G for space-air-ground integrated network: Key enablers, open challenges, and future direction. J. King Saud Univ. Comput. Inf. Sci. 2021, in press. [CrossRef]
- Hakeem, S.A.A.; Hussein, H.H.; Kim, H. Vision and research directions of 6G technologies and applications. J. King Saud Univ. Comput. Inf. Sci. 2022, 34, 2419–2442. [Google Scholar]
- Kilpi, J.; Kokkoniemi-Tarkkanen, H.; Uusitalo, M.A. Efficient method to validate high reliability of 5G URLLC. In Proceedings of the 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring), Virtual Event, 25–28 April 2021; pp. 1–6. [Google Scholar]
- Khan, J.; Jacob, L. Efficient resource allocation in 5G URLLC with packet duplication based macro-diversity. Comput. Commun. 2022, 191, 459–466. [Google Scholar] [CrossRef]
- Li, X.; Savkin, A.V. Networked unmanned aerial vehicles for surveillance and monitoring: A survey. Future Internet 2021, 13, 174. [Google Scholar] [CrossRef]
- Zhang, Y.; Cui, L.; Wang, W.; Zhang, Y. A survey on software defined networking with multiple controllers. J. Netw. Comput. Appl. 2018, 103, 101–118. [Google Scholar] [CrossRef]
- Pham, Q.V.; Fang, F.; Ha, V.N.; Piran, M.J.; Le, M.; Le, L.B.; Hwang, W.J.; Ding, Z. A survey of multi-access edge computing in 5G and beyond: Fundamentals, technology integration, and state-of-the-art. IEEE Access 2020, 8, 116974–117017. [Google Scholar] [CrossRef]
- Shah, S.D.A.; Gregory, M.A.; Li, S.; Fontes, R.D.R. SDN enhanced multi-access edge computing (MEC) for E2E mobility and QoS management. IEEE Access 2020, 8, 77459–77469. [Google Scholar] [CrossRef]
- Ranjha, A.; Kaddoum, G. URLLC facilitated by mobile UAV relay and RIS: A joint design of passive beamforming, blocklength, and UAV positioning. IEEE Internet Things J. 2020, 8, 4618–4627. [Google Scholar] [CrossRef]
- Liu, Y.; Deng, Y.; Elkashlan, M.; Nallanathan, A.; Karagiannidis, G.K. Analyzing grant-free access for URLLC service. IEEE J. Sel. Areas Commun. 2020, 39, 741–755. [Google Scholar] [CrossRef]
- Xie, Y.; Ren, P. Reliability Analysis of Grant-Free Uplink Data Transmission for URLLC. In Proceedings of the 2021 IEEE Global Communications Conference (GLOBECOM), Madrid, Spain, 7–11 December 2021; pp. 1–5. [Google Scholar]
- Li, Z.; Uusitalo, M.A.; Shariatmadari, H.; Singh, B. 5G URLLC: Design challenges and system concepts. In Proceedings of the 2018 15th international symposium on wireless communication systems (ISWCS), Lisbon, Portugal, 28–31 August 2018; pp. 1–6. [Google Scholar]
- Osterrieder, P.; Budde, L.; Friedli, T. The smart factory as a key construct of industry 4.0: A systematic literature review. Int. J. Prod. Econ. 2020, 221, 107476. [Google Scholar] [CrossRef]
- Mourtzis, D.; Angelopoulos, J.; Panopoulos, N. Smart Manufacturing and Tactile Internet Based on 5G in Industry 4.0: Challenges, Applications and New Trends. Electronics 2021, 10, 3175. [Google Scholar] [CrossRef]
- Arena, F.; Pau, G.; Severino, A. A review on IEEE 802.11 p for intelligent transportation systems. J. Sens. Actuator Netw. 2020, 9, 22. [Google Scholar] [CrossRef]
- Guevara, L.; Auat Cheein, F. The role of 5G technologies: Challenges in smart cities and intelligent transportation systems. Sustainability 2020, 12, 6469. [Google Scholar] [CrossRef]
- Romeo, L.; Petitti, A.; Marani, R.; Milella, A. Internet of robotic things in smart domains: Applications and challenges. Sensors 2020, 20, 3355. [Google Scholar] [CrossRef]
- Greengard, S. Virtual Reality; MIT Press: Cambridge, MA, USA, 2019. [Google Scholar]
- Chen, Y.; Wang, Q.; Chen, H.; Song, X.; Tang, H.; Tian, M. An overview of augmented reality technology. Proc. J. Phys. Conf. Ser. 2019, 1237, 022082. [Google Scholar] [CrossRef]
- Chen, K.; Li, T.; Kim, H.S.; Culler, D.E.; Katz, R.H. Marvel: Enabling mobile augmented reality with low energy and low latency. In Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems, Shenzhen, China, 4–7 November 2018; pp. 292–304. [Google Scholar]
- Vergutz, A.; Noubir, G.; Nogueira, M. Reliability for smart healthcare: A network slicing perspective. IEEE Netw. 2020, 34, 91–97. [Google Scholar] [CrossRef]
- Liou, E.C.; Cheng, S.C. A qos benchmark system for telemedicine communication over 5g urllc and mmtc scenarios. In Proceedings of the 2020 IEEE 2nd Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS), Tainan, Taiwan, 29–31 May 2020; pp. 24–26. [Google Scholar]
- Maksimović, M.; Forcan, M.; Bošković, M.Č.; Šekara, T.B.; Lutovac, B. On the role of 5G Ultra-Reliable Low-Latency Communications (URLLC) in applications extending Smart Grid (SG) capabilities. In Proceedings of the 2022 11th Mediterranean Conference on Embedded Computing (MECO), Budva, Montenegro, 7–10 June 2022; pp. 1–4. [Google Scholar]
- Sharma, S.K.; Woungang, I.; Anpalagan, A.; Chatzinotas, S. Toward tactile internet in beyond 5G era: Recent advances, current issues, and future directions. IEEE Access 2020, 8, 56948–56991. [Google Scholar] [CrossRef]
- Ateya, A.A.; Muthanna, A.; Vybornova, A.; Gudkova, I.; Gaidamaka, Y.; Abuarqoub, A.; Algarni, A.D.; Koucheryavy, A. Model mediation to overcome light limitations—Toward a secure tactile Internet system. J. Sens. Actuator Netw. 2019, 8, 6. [Google Scholar] [CrossRef]
- Bellalouna, F. The augmented reality technology as enabler for the digitization of industrial business processes: Case studies. Procedia CIRP 2021, 98, 400–405. [Google Scholar] [CrossRef]
- Cools, R.; Han, J.; Simeone, A.L. SelectVisAR: Selective Visualisation of Virtual Environments in Augmented Reality. In Proceedings of the Designing Interactive Systems Conference 2021, Xiamen, China, 20–22 December 2021; pp. 275–282. [Google Scholar]
- Akyildiz, I.F.; Guo, H. Wireless Extended Reality (XR): Challenges and New Research Directions. ITU J. Future Evol. Technol. 2022, 3, 1–15. [Google Scholar]
- Rebbani, Z.; Azougagh, D.; Bahatti, L.; Bouattane, O. Definitions and applications of augmented/virtual reality: A survey. Int. J. Emerg. Trends Eng. Res. 2021, 9, 279–285. [Google Scholar]
- Lv, Z. Virtual reality in the context of Internet of Things. Neural Comput. Appl. 2020, 32, 9593–9602. [Google Scholar] [CrossRef]
- Xie, B.; Liu, H.; Alghofaili, R.; Zhang, Y.; Jiang, Y.; Lobo, F.D.; Li, C.; Li, W.; Huang, H.; Akdere, M.; et al. A review on virtual reality skill training applications. Front. Virtual Real. 2021, 2, 645153. [Google Scholar] [CrossRef]
- Schäfer, A.; Reis, G.; Stricker, D. A Survey on Synchronous Augmented, Virtual and Mixed Reality Remote Collaboration Systems. ACM Comput. Surv. (CSUR) 2021. [Google Scholar] [CrossRef]
- Turan, Z.; Atila, G. Augmented reality technology in science education for students with specific learning difficulties: Its effect on students’ learning and views. Res. Sci. Technol. Educ. 2021, 39, 506–524. [Google Scholar] [CrossRef]
- Roopa, D.; Prabha, R.; Senthil, G. Revolutionizing education system with interactive augmented reality for quality education. Mater. Today Proc. 2021, 46, 3860–3863. [Google Scholar] [CrossRef]
- Gurevych, R.; Silveistr, A.; Mokliuk, M.; Shaposhnikova, I.; Gordiichuk, G.; Saiapina, S. Using Augmented Reality Technology in Higher Education Institutions. Postmod. Openings Deschid. Postmoderne 2021, 12, 109–132. [Google Scholar] [CrossRef]
- Muthanna, A.; Ateya, A.A.; Amelyanovich, A.; Shpakov, M.; Darya, P.; Makolkina, M. AR enabled system for cultural heritage monitoring and preservation. In Internet of Things, Smart Spaces, and Next Generation Networks and Systems; Springer: Berlin/Heidelberg, Germany, 2018; pp. 560–571. [Google Scholar]
- Hincapié, M.; Díaz, C.; Zapata-Cárdenas, M.I.; Rios, H.d.J.T.; Valencia, D.; Güemes-Castorena, D. Augmented reality mobile apps for cultural heritage reactivation. Comput. Electr. Eng. 2021, 93, 107281. [Google Scholar] [CrossRef]
- Aliprantis, J.; Caridakis, G. A survey of augmented reality applications in cultural heritage. Int. J. Comput. Methods Herit. Sci. (IJCMHS) 2019, 3, 118–147. [Google Scholar] [CrossRef]
- Rejeb, A.; Rejeb, K.; Treiblmaier, H. How augmented reality impacts retail marketing: A state-of-the-art review from a consumer perspective. J. Strateg. Mark. 2021, 1–31. [Google Scholar] [CrossRef]
- Yoo, J. The effects of perceived quality of augmented reality in mobile commerce—An application of the information systems success model. Informatics 2020, 7, 14. [Google Scholar] [CrossRef]
- Marino, E.; Barbieri, L.; Colacino, B.; Fleri, A.K.; Bruno, F. An Augmented Reality inspection tool to support workers in Industry 4.0 environments. Comput. Ind. 2021, 127, 103412. [Google Scholar] [CrossRef]
- Szajna, A.; Stryjski, R.; Woźniak, W.; Chamier-Gliszczyński, N.; Królikowski, T. The production quality control process, enhanced with augmented reality glasses and the new generation computing support system. Procedia Comput. Sci. 2020, 176, 3618–3625. [Google Scholar] [CrossRef]
- Manuri, F.; Sanna, A. A survey on applications of augmented reality. ACSIJ Adv. Comput. Sci. Int. J. 2016, 5, 18–27. [Google Scholar]
- Tsai, T.H.; Chiang, Y.W. Research study on applying SLAM-Based Augmented Reality technology for gamification history guided tour. In Proceedings of the 2019 IEEE International Conference on Architecture, Construction, Environment and Hydraulics (ICACEH), Xiamen, China, 20–22 December 2019; pp. 116–119. [Google Scholar]
- Mao, C.C.; Chen, C.H. Augmented reality of 3D content application in common operational picture training system for army. Int. J. Hum. Comput. Interact. 2021, 37, 1899–1915. [Google Scholar] [CrossRef]
- Zaman, F.; Drake, W.; Intriligator, J.; Gardony, A.; Natick, M.; Rife, J. Investigating a Virtual Reality Based Subterranean Scenario Examining Augmented Reality Implications for Military Operators. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting; SAGE Publications Sage CA: Los Angeles, CA, USA, 2021; Volume 65, pp. 1129–1133. [Google Scholar]
- Aggarwal, R.; Singhal, A. Augmented Reality and its effect on our life. In Proceedings of the 2019 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence), Uttar Pradesh, India, 10–11 January 2019; pp. 510–515. [Google Scholar]
- Mahmood, Z.; Ali, T.; Muhammad, N.; Bibi, N.; Shahzad, I.; Azmat, S. EAR: Enhanced augmented reality system for sports entertainment applications. KSII Trans. Internet Inf. Syst. (TIIS) 2017, 11, 6069–6091. [Google Scholar]
- Yang, T.H.; Kim, J.R.; Jin, H.; Gil, H.; Koo, J.H.; Kim, H.J. Recent advances and opportunities of active materials for haptic technologies in virtual and augmented reality. Adv. Funct. Mater. 2021, 31, 2008831. [Google Scholar] [CrossRef]
- Ferrari, V.; Klinker, G.; Cutolo, F. Augmented reality in healthcare. J. Healthc. Eng. 2019, 2019, 9321535. [Google Scholar] [CrossRef]
- Berciu, A.G.; Dulf, E.H.; Stefan, I.A. Flexible Augmented Reality-Based Health Solution for Medication Weight Establishment. Processes 2022, 10, 219. [Google Scholar] [CrossRef]
- Akhunova, N.K.K. Possibilities of using virtual reality technologies in education. Asian J. Multidimens. Res. (AJMR) 2021, 10, 549–555. [Google Scholar] [CrossRef]
- Behmadi, S.; Asadi, F.; Okhovati, M.; Sarabi, R.E. Virtual reality-based medical education versus lecture-based method in teaching start triage lessons in emergency medical students: Virtual reality in medical education. J. Adv. Med Educ. Prof. 2022, 10, 48. [Google Scholar]
- Hutson, J.; Olsen, T. Digital humanities and virtual reality: A review of theories and best practices for art history. Int. J. Technol. Educ. (IJTE) 2021, 4, 491–500. [Google Scholar] [CrossRef]
- Soliman, M.; Pesyridis, A.; Dalaymani-Zad, D.; Gronfula, M.; Kourmpetis, M. The application of virtual reality in engineering education. Appl. Sci. 2021, 11, 2879. [Google Scholar] [CrossRef]
- Huang, W.; Roscoe, R.D. Head-mounted display-based virtual reality systems in engineering education: A review of recent research. Comput. Appl. Eng. Educ. 2021, 29, 1420–1435. [Google Scholar] [CrossRef]
- Hasan, L.K.; Haratian, A.; Kim, M.; Bolia, I.K.; Weber, A.E.; Petrigliano, F.A. Virtual reality in orthopedic surgery training. Adv. Med. Educ. Pract. 2021, 12, 1295. [Google Scholar] [CrossRef]
- Chheang, V.; Saalfeld, P.; Joeres, F.; Boedecker, C.; Huber, T.; Huettl, F.; Lang, H.; Preim, B.; Hansen, C. A collaborative virtual reality environment for liver surgery planning. Comput. Graph. 2021, 99, 234–246. [Google Scholar] [CrossRef]
- Salamon, N.; Grimm, J.M.; Horack, J.M.; Newton, E.K. Application of virtual reality for crew mental health in extended-duration space missions. Acta Astronaut. 2018, 146, 117–122. [Google Scholar] [CrossRef]
- Ang, S.P.; Montuori, M.; Trimba, Y.; Maldari, N.; Patel, D.; Chen, Q.C. Recent applications of virtual reality for the management of pain in burn and pediatric patients. Curr. Pain Headache Rep. 2021, 25, 1–8. [Google Scholar] [CrossRef]
- Venkatesan, M.; Mohan, H.; Ryan, J.R.; Schürch, C.M.; Nolan, G.P.; Frakes, D.H.; Coskun, A.F. Virtual and augmented reality for biomedical applications. Cell Rep. Med. 2021, 2, 100348. [Google Scholar] [CrossRef]
- Găină, M.A.; Szalontay, A.S.; Ștefănescu, G.; Bălan, G.G.; Ghiciuc, C.M.; Boloș, A.; Găină, A.M.; Ștefănescu, C. State-of-the-Art Review on Immersive Virtual Reality Interventions for Colonoscopy-Induced Anxiety and Pain. J. Clin. Med. 2022, 11, 1670. [Google Scholar] [CrossRef]
- Cassidy, D.J.; Coe, T.M.; Jogerst, K.M.; McKinley, S.K.; Sell, N.M.; Sampson, M.; Park, Y.S.; Petrusa, E.; Goldstone, R.N.; Hashimoto, D.A.; et al. Transfer of virtual reality endoscopy training to live animal colonoscopy: A randomized control trial of proficiency vs. repetition-based training. Surg. Endosc. 2022, 36, 1–10. [Google Scholar] [CrossRef]
- Oliveira, J.; Gamito, P.; Souto, T.; Conde, R.; Ferreira, M.; Corotnean, T.; Fernandes, A.; Silva, H.; Neto, T. Virtual Reality-Based Cognitive Stimulation on People with Mild to Moderate Dementia due to Alzheimer’s Disease: A Pilot Randomized Controlled Trial. Int. J. Environ. Res. Public Health 2021, 18, 5290. [Google Scholar] [CrossRef]
- Hemphill, S.; Nguyen, A.; Kwong, J.; Rodriguez, S.T.; Wang, E.; Caruso, T.J. Virtual reality facilitates engagement in physical therapy in the pediatric CVICU. Pediatr. Phys. Ther. 2021, 33, E7–E9. [Google Scholar] [CrossRef]
- Zhan, T.; Yin, K.; Xiong, J.; He, Z.; Wu, S.T. Augmented reality and virtual reality displays: Perspectives and challenges. iScience 2020, 23, 101397. [Google Scholar] [CrossRef]
- Ateya, A.; Al-Bahri, M.; Muthanna, A.; Koucheryavy, A. End-to-end system structure for latency sensitive applications of 5G. Elektrosvyaz 2018, 6, 56–61. [Google Scholar]
- Muthanna, M.S.A.; Wang, P.; Wei, M.; Ateya, A.A.; Muthanna, A. Toward an ultra-low latency and energy efficient LoRaWAN. In Internet of Things, Smart Spaces, and Next Generation Networks and Systems; Springer: Cham, Switzerland, 2019; pp. 233–242. [Google Scholar]
- Giaretta, A. Security and Privacy in Virtual Reality–A Literature Survey. arXiv 2022, arXiv:2205.00208. [Google Scholar]
- Rossi, S.; Viola, I.; Toni, L.; Cesar, P. From 3-DoF to 6-DoF: New Metrics to Analyse Users Behaviour in Immersive Applications. arXiv 2021, arXiv:2112.09402. [Google Scholar]
- Cheng, Q.; Shan, H.; Zhuang, W.; Yu, L.; Zhang, Z.; Quek, T.Q. Design and Analysis of MEC-and Proactive Caching-Based 360∘ Mobile VR Video Streaming. IEEE Trans. Multimed. 2021, 24, 1529–1544. [Google Scholar] [CrossRef]
- Vlahovic, S.; Suznjevic, M.; Skorin-Kapov, L. A survey of challenges and methods for Quality of Experience assessment of interactive VR applications. J. Multimodal User Interfaces 2022, 16, 1–35. [Google Scholar] [CrossRef]
- Dills, P.; Gabardi, K.; Zinn, M. Stability and Rendering Limitations of High-Performance Admittance Based Haptic Interfaces. In Proceedings of the 2022 IEEE Haptics Symposium (HAPTICS), Santa Barbara, CA, USA, 21–24 March 2022; pp. 1–8. [Google Scholar]
- Sahu, C.K.; Young, C.; Rai, R. Artificial intelligence (AI) in augmented reality (AR)-assisted manufacturing applications: A review. Int. J. Prod. Res. 2021, 59, 4903–4959. [Google Scholar] [CrossRef]
- Muthanna, A.; Ateya, A.A.; Al Balushi, M.; Kirichek, R. D2D enabled communication system structure based on software defined networking for 5G network. In Proceedings of the 2018 International Symposium on Consumer Technologies (ISCT), St-Petersburg, Russia, 11–12 May 2018; pp. 41–44. [Google Scholar]
- Zhang, L.; Chakareski, J. UAV-Assisted Edge Computing and Streaming for Wireless Virtual Reality: Analysis, Algorithm Design, and Performance Guarantees. IEEE Trans. Veh. Technol. 2022, 71, 3267–3275. [Google Scholar] [CrossRef]
- Wang, Y.; Yu, T.; Sakaguchi, K. Context-Based MEC Platform for Augmented-Reality Services in 5G Networks. In Proceedings of the 2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall), Online, 27 September–28 October 2021; pp. 1–5. [Google Scholar]
- Ravuri, H.K.; Vega, M.T.; Wauters, T.; Da, B.; Clemm, A.; De Turck, F. An experimental evaluation of flow setup latency in distributed software defined networks. In Proceedings of the 2019 IEEE Conference on Network Softwarization (NetSoft), Paris, France, 24–28 June 2019; pp. 432–437. [Google Scholar]
- Ge, X.; Pan, L.; Li, Q.; Mao, G.; Tu, S. Multipath cooperative communications networks for augmented and virtual reality transmission. IEEE Trans. Multimed. 2017, 19, 2345–2358. [Google Scholar] [CrossRef]
- Devagiri, J.S.; Paheding, S.; Niyaz, Q.; Yang, X.; Smith, S. Augmented Reality and Artificial Intelligence in industry: Trends, tools, and future challenges. Expert Syst. Appl. 2022, 207, 118002. [Google Scholar] [CrossRef]
- Mohsan, S.A.H.; Khan, M.A.; Noor, F.; Ullah, I.; Alsharif, M.H. Towards the Unmanned Aerial Vehicles (UAVs): A Comprehensive Review. Drones 2022, 6, 147. [Google Scholar] [CrossRef]
- Li, Y.; Huynh, D.V.; Do-Duy, T.; Garcia-Palacios, E.; Duong, T.Q. Unmanned aerial vehicle-aided edge networks with ultra-reliable low-latency communications: A digital twin approach. IET Signal Process. 2022. [Google Scholar] [CrossRef]
- Su, Z.; Feng, W.; Tang, J.; Chen, Z.; Fu, Y.; Zhao, N.; Wong, K.K. Energy efficiency optimization for D2D communications underlaying UAV-assisted industrial iot networks with SWIPT. IEEE Internet Things J. 2022. [Google Scholar] [CrossRef]
- Rachmawati, T.S.N.; Kim, S. Unmanned Aerial Vehicles (UAV) Integration with Digital Technologies toward Construction 4.0: A Systematic Literature Review. Sustainability 2022, 14, 5708. [Google Scholar] [CrossRef]
- Liao, Y.H.; Juang, J.G. Real-Time UAV Trash Monitoring System. Appl. Sci. 2022, 12, 1838. [Google Scholar] [CrossRef]
- Nguyen, L.M.D.; Vo, V.N.; So-In, C.; Dang, V.H. Throughput analysis and optimization for NOMA Multi-UAV assisted disaster communication using CMA-ES. Wirel. Netw. 2021, 27, 4889–4902. [Google Scholar] [CrossRef]
- Mohan, M.; Richardson, G.; Gopan, G.; Aghai, M.M.; Bajaj, S.; Galgamuwa, G.P.; Vastaranta, M.; Arachchige, P.S.P.; Amorós, L.; Corte, A.P.D.; et al. UAV-supported forest regeneration: Current trends, challenges and implications. Remote. Sens. 2021, 13, 2596. [Google Scholar] [CrossRef]
- Shang, Y.; Liu, B.; Tian, Y.; Wang, X.; Cai, Z. Virtual Reality Oriented Modeling and Simulation of Amphibious Aircraft Forest Fire Extinguishing Mission Scene. In Proceedings of the 2021 5th International Conference on Artificial Intelligence and Virtual Reality (AIVR), Kumamoto, Japan, 23–25 July 2021; pp. 9–14. [Google Scholar]
- Filkin, T.; Sliusar, N.; Ritzkowski, M.; Huber-Humer, M. Unmanned Aerial Vehicles for Operational Monitoring of Landfills. Drones 2021, 5, 125. [Google Scholar] [CrossRef]
- Gargalakos, M. The role of unmanned aerial vehicles in military communications: Application scenarios, current trends, and beyond. J. Def. Model. Simul. 2021. [Google Scholar] [CrossRef]
- Tang, Y.; Dananjayan, S.; Hou, C.; Guo, Q.; Luo, S.; He, Y. A survey on the 5G network and its impact on agriculture: Challenges and opportunities. Comput. Electron. Agric. 2021, 180, 105895. [Google Scholar] [CrossRef]
- Hayat, S.; Yanmaz, E.; Muzaffar, R. Survey on unmanned aerial vehicle networks for civil applications: A communications viewpoint. IEEE Commun. Surv. Tutor. 2016, 18, 2624–2661. [Google Scholar] [CrossRef]
- Ai, Z.; Livingston, M.A.; Moskowitz, I.S. Real-time unmanned aerial vehicle 3D environment exploration in a mixed reality environment. In Proceedings of the 2016 International Conference on Unmanned Aircraft Systems (ICUAS), Arlington, VA, USA, 7–10 June 2016; pp. 664–670. [Google Scholar]
- Mozaffari, M.; Saad, W.; Bennis, M.; Nam, Y.H.; Debbah, M. A tutorial on UAVs for wireless networks: Applications, challenges, and open problems. IEEE Commun. Surv. Tutor. 2019, 21, 2334–2360. [Google Scholar] [CrossRef]
- Khalaf, A.S.; Pianpak, P.; Alharthi, S.A.; NaminiMianji, Z.; Torres, R.; Tran, S.; Dolgov, I.; Toups, Z.O. An architecture for simulating drones in mixed reality games to explore future search and rescue scenarios. In Proceedings of the International ISCRAM Conference, Rochester, NY, USA, 20–23 May 2018. [Google Scholar]
- Sestras, P.; Roșca, S.; Bilașco, Ș.; Naș, S.; Buru, S.M.; Kovacs, L.; Spalević, V.; Sestras, A.F. Feasibility assessments using unmanned aerial vehicle technology in heritage buildings: Rehabilitation-restoration, spatial analysis and tourism potential analysis. Sensors 2020, 20, 2054. [Google Scholar] [CrossRef]
- Panou, C.; Ragia, L.; Dimelli, D.; Mania, K. An architecture for mobile outdoors augmented reality for cultural heritage. ISPRS Int. J. Geo-Inf. 2018, 7, 463. [Google Scholar] [CrossRef]
- Roldán-Gómez, J.J.; González-Gironda, E.; Barrientos, A. A survey on robotic technologies for forest firefighting: Applying drone swarms to improve firefighters’ efficiency and safety. Appl. Sci. 2021, 11, 363. [Google Scholar] [CrossRef]
- Halik, Ł; Smaczyński, M. Geovisualisation of relief in a virtual reality system on the basis of low-level aerial imagery. Pure Appl. Geophys. 2018, 175, 3209–3221. [Google Scholar] [CrossRef]
- Kim, S.J.; Jeong, Y.; Park, S.; Ryu, K.; Oh, G. A survey of drone use for entertainment and AVR (augmented and virtual reality). In Augmented Reality and Virtual Reality; Springer: Cham, Switzerland, 2018; pp. 339–352. [Google Scholar]
- Sakib, M.N.; Chaspari, T.; Behzadan, A.H. Physiological data models to understand the effectiveness of drone operation training in immersive virtual reality. J. Comput. Civ. Eng. 2021, 35, 04020053. [Google Scholar] [CrossRef]
- Templin, T.; Popielarczyk, D. The use of low-cost unmanned aerial vehicles in the process of building models for cultural tourism, 3D web and augmented/mixed reality applications. Sensors 2020, 20, 5457. [Google Scholar] [CrossRef] [PubMed]
- Unal, M.; Bostanci, E.; Sertalp, E. Distant augmented reality: Bringing a new dimension to user experience using drones. Digit. Appl. Archaeol. Cult. Herit. 2020, 17, e00140. [Google Scholar] [CrossRef]
- Sutton, G.J.; Zeng, J.; Liu, R.P.; Ni, W.; Nguyen, D.N.; Jayawickrama, B.A.; Huang, X.; Abolhasan, M.; Zhang, Z.; Dutkiewicz, E.; et al. Enabling technologies for ultra-reliable and low latency communications: From PHY and MAC layer perspectives. IEEE Commun. Surv. Tutor. 2019, 21, 2488–2524. [Google Scholar] [CrossRef]
- Carvalho, G.; Cabral, B.; Pereira, V.; Bernardino, J. Edge computing: Current trends, research challenges and future directions. Computing 2021, 103, 993–1023. [Google Scholar] [CrossRef]
- Islam, A.; Debnath, A.; Ghose, M.; Chakraborty, S. A survey on task offloading in multi-access edge computing. J. Syst. Archit. 2021, 118, 102225. [Google Scholar] [CrossRef]
- Singh, J.; Singh, P.; Gill, S.S. Fog computing: A taxonomy, systematic review, current trends and research challenges. J. Parallel Distrib. Comput. 2021, 157, 56–85. [Google Scholar] [CrossRef]
- Mansouri, Y.; Babar, M.A. A review of edge computing: Features and resource virtualization. J. Parallel Distrib. Comput. 2021, 150, 155–183. [Google Scholar] [CrossRef]
- Gao, B.; Zhou, Z.; Liu, F.; Xu, F.; Li, B. An online framework for joint network selection and service placement in mobile edge computing. IEEE Trans. Mob. Comput. 2021. [Google Scholar] [CrossRef]
- Mao, Y.; You, C.; Zhang, J.; Huang, K.; Letaief, K.B. A survey on mobile edge computing: The communication perspective. IEEE Commun. Surv. Tutor. 2017, 19, 2322–2358. [Google Scholar] [CrossRef]
- Qiu, H.; Zhu, K.; Luong, N.C.; Yi, C.; Niyato, D.; Kim, D.I. Applications of auction and mechanism design in edge computing: A survey. IEEE Trans. Cogn. Commun. Netw. 2022, 8, 1034–1058. [Google Scholar] [CrossRef]
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Osama, M.; Ateya, A.A.; Ahmed Elsaid, S.; Muthanna, A. Ultra-Reliable Low-Latency Communications: Unmanned Aerial Vehicles Assisted Systems. Information 2022, 13, 430. https://doi.org/10.3390/info13090430
Osama M, Ateya AA, Ahmed Elsaid S, Muthanna A. Ultra-Reliable Low-Latency Communications: Unmanned Aerial Vehicles Assisted Systems. Information. 2022; 13(9):430. https://doi.org/10.3390/info13090430
Chicago/Turabian StyleOsama, Mohamed, Abdelhamied A. Ateya, Shaimaa Ahmed Elsaid, and Ammar Muthanna. 2022. "Ultra-Reliable Low-Latency Communications: Unmanned Aerial Vehicles Assisted Systems" Information 13, no. 9: 430. https://doi.org/10.3390/info13090430
APA StyleOsama, M., Ateya, A. A., Ahmed Elsaid, S., & Muthanna, A. (2022). Ultra-Reliable Low-Latency Communications: Unmanned Aerial Vehicles Assisted Systems. Information, 13(9), 430. https://doi.org/10.3390/info13090430