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Prof. Dr. Jaime Lloret
Universitat Politecnica de Valencia, Spain

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0 Multimedia
0 Streaming Media
0 Telematics
0 Wireless and underwater sensor networks
0 Wireless Ad hoc Networks

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Short Biography

Prof. Jaime Lloret received his B.Sc. and M.Sc. in Physics in 1997, his B.Sc.and M.Sc. in Electronic Engineering in 2003 and his Ph.D. in telecommunication engineering (Dr. Ing.) in 2006. He is currently an Associate Professor at the Polytechnic University of Valencia. He has been the Chair of the Integrated Management Coastal Research Institute since January 2017. He has been Internet Technical Committee chair for the term 2013-2015. He has authored 14 books and has more than 600 research papers published. He is EiC of the “Ad Hoc and Sensor Wireless Networks” and the international journal "Networks Protocols and Algorithms". Since 2016, he has been the Spanish researcher with highest h-index in the TELECOMMUNICATIONS journal list according to the Clarivate Analytics Ranking. He is included in the world’s top 2% of scientists according to the Stanford University List. He has been general chair of 65 international workshops and conferences. He is an IEEE Senior, ACM Senior and IARIA Fellow.

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Journal article
Published: 18 August 2021 in Drones
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The use of drones in agriculture is becoming a valuable tool for crop monitoring. There are some critical moments for crop success; the establishment is one of those. In this paper, we present an initial approximation of a methodology that uses RGB images gathered from drones to evaluate the establishment success in legumes based on matrixes operations. Our aim is to provide a method that can be implemented in low-cost nodes with relatively low computational capacity. An index (B1/B2) is used for estimating the percentage of green biomass to evaluate the establishment success. In the study, we include three zones with different establishment success (high, regular, and low) and two species (chickpea and lentils). We evaluate data usability after applying aggregation techniques, which reduces the picture’s size to improve long-term storage. We test cell sizes from 1 to 10 pixels. This technique is tested with images gathered in production fields with intercropping at 4, 8, and 12 m relative height to find the optimal aggregation for each flying height. Our results indicate that images captured at 4 m with a cell size of 5, at 8 m with a cell size of 3, and 12 m without aggregation can be used to determine the establishment success. Comparing the storage requirements, the combination that minimises the data size while maintaining its usability is the image at 8 m with a cell size of 3. Finally, we show the use of generated information with an artificial neural network to classify the data. The dataset was split into a training dataset and a verification dataset. The classification of the verification dataset offered 83% of the cases as well classified. The proposed tool can be used in the future to compare the establishment success of different legume varieties or species.

ACS Style

Lorena Parra; David Mostaza-Colado; Salima Yousfi; Jose F. Marin; Pedro V. Mauri; Jaime Lloret. Drone RGB Images as a Reliable Information Source to Determine Legumes Establishment Success. Drones 2021, 5, 79 .

AMA Style

Lorena Parra, David Mostaza-Colado, Salima Yousfi, Jose F. Marin, Pedro V. Mauri, Jaime Lloret. Drone RGB Images as a Reliable Information Source to Determine Legumes Establishment Success. Drones. 2021; 5 (3):79.

Chicago/Turabian Style

Lorena Parra; David Mostaza-Colado; Salima Yousfi; Jose F. Marin; Pedro V. Mauri; Jaime Lloret. 2021. "Drone RGB Images as a Reliable Information Source to Determine Legumes Establishment Success." Drones 5, no. 3: 79.

Journal article
Published: 16 August 2021 in Healthcare
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The COVID-19 pandemic has been a worldwide catastrophe. Its impact, not only economically, but also socially and in terms of human lives, was unexpected. Each of the many mechanisms to fight the contagiousness of the illness has been proven to be extremely important. One of the most important mechanisms is the use of facemasks. However, the wearing the facemasks incorrectly makes this prevention method useless. Artificial Intelligence (AI) and especially facial recognition techniques can be used to detect misuses and reduce virus transmission, especially indoors. In this paper, we present an intelligent method to automatically detect when facemasks are being worn incorrectly in real-time scenarios. Our proposal uses Convolutional Neural Networks (CNN) with transfer learning to detect not only if a mask is used or not, but also other errors that are usually not taken into account but that may contribute to the virus spreading. The main problem that we have detected is that there is currently no training set for this task. It is for this reason that we have requested the participation of citizens by taking different selfies through an app and placing the mask in different positions. Thus, we have been able to solve this problem. The results show that the accuracy achieved with transfer learning slightly improves the accuracy achieved with convolutional neural networks. Finally, we have also developed an Android-app demo that validates the proposal in real scenarios.

ACS Style

Jesús Tomás; Albert Rego; Sandra Viciano-Tudela; Jaime Lloret. Incorrect Facemask-Wearing Detection Using Convolutional Neural Networks with Transfer Learning. Healthcare 2021, 9, 1050 .

AMA Style

Jesús Tomás, Albert Rego, Sandra Viciano-Tudela, Jaime Lloret. Incorrect Facemask-Wearing Detection Using Convolutional Neural Networks with Transfer Learning. Healthcare. 2021; 9 (8):1050.

Chicago/Turabian Style

Jesús Tomás; Albert Rego; Sandra Viciano-Tudela; Jaime Lloret. 2021. "Incorrect Facemask-Wearing Detection Using Convolutional Neural Networks with Transfer Learning." Healthcare 9, no. 8: 1050.

Journal article
Published: 13 August 2021 in Sustainability
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The Internet of Things (IoT) is an emerging technology and provides connectivity among physical objects with the support of 5G communication. In recent decades, there have been a lot of applications based on IoT technology for the sustainability of smart cities, such as farming, e-healthcare, education, smart homes, weather monitoring, etc. These applications communicate in a collaborative manner between embedded IoT devices and systematize daily routine tasks. In the literature, many solutions facilitate remote users to gather the observed data by accessing the stored information on the cloud network and lead to smart systems. However, most of the solutions raise significant research challenges regarding information sharing in mobile IoT networks and must be able to stabilize the performance of smart operations in terms of security and intelligence. Many solutions are based on 5G communication to support high user mobility and increase the connectivity among a huge number of IoT devices. However, such approaches lack user and data privacy against anonymous threats and incur resource costs. In this paper, we present a mobility support 5G architecture with real-time routing for sustainable smart cities that aims to decrease the loss of data against network disconnectivity and increase the reliability for 5G-based public healthcare networks. The proposed architecture firstly establishes a mutual relationship among the nodes and mobile sink with shared secret information and lightweight processing. Secondly, multi-secured levels are proposed to protect the interaction with smart transmission systems by increasing the trust threshold over the insecure channels. The conducted experiments are analyzed, and it is concluded that their performance significantly increases the information sustainability for mobile networks in terms of security and routing.

ACS Style

Amjad Rehman; Khalid Haseeb; Tanzila Saba; Jaime Lloret; Zara Ahmed. Mobility Support 5G Architecture with Real-Time Routing for Sustainable Smart Cities. Sustainability 2021, 13, 9092 .

AMA Style

Amjad Rehman, Khalid Haseeb, Tanzila Saba, Jaime Lloret, Zara Ahmed. Mobility Support 5G Architecture with Real-Time Routing for Sustainable Smart Cities. Sustainability. 2021; 13 (16):9092.

Chicago/Turabian Style

Amjad Rehman; Khalid Haseeb; Tanzila Saba; Jaime Lloret; Zara Ahmed. 2021. "Mobility Support 5G Architecture with Real-Time Routing for Sustainable Smart Cities." Sustainability 13, no. 16: 9092.

Journal article
Published: 12 August 2021 in Sensors
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Uncontrolled dumping linked to agricultural vehicles causes an increase in the incorporation of oils into the irrigation system. In this paper, we propose a system based on an optical sensor to monitor oil concentration in the irrigation ditches. Our prototype is based on the absorption and dispersion of light. As a light source, we use Light Emitting Diodes (LEDs) with different colours (white, yellow, blue, green, and red) and a photodetector as a sensing element. To test the sensor’s performance, we incorporate industrial oils used by a diesel or gasoline engine, with a concentration from 0 to 0.20 mLoil/cm2. The experiment was carried out at different water column heights, 0 to 20 cm. According to our results, the sensor can differentiate between the presence or absence of diesel engine oil with any LED. For gasoline engine oil, the sensor quantifies its concentration using the red light source; concentrations greater than 0.1 mLoil/cm2 cannot be distinguished. The data gathered using the red LED has an average absolute error of 0.003 mLoil/cm2 (relative error of 15.8%) for the worst case, 15 cm. Finally, the blue LED generates different signals in the photodetector according to the type of oil. We developed an algorithm that combines (i) the white LED, to monitor the presence of oil; (ii) the blue LED, to identify if the oil comes from a gasoline or diesel engine; and (iii) the red LED, to monitor the concentration of oil used by a gasoline engine.

ACS Style

Daniel A. Basterrechea; Javier Rocher; Lorena Parra; Jaime Lloret. Low-Cost System Based on Optical Sensor to Monitor Discharge of Industrial Oil in Irrigation Ditches. Sensors 2021, 21, 5449 .

AMA Style

Daniel A. Basterrechea, Javier Rocher, Lorena Parra, Jaime Lloret. Low-Cost System Based on Optical Sensor to Monitor Discharge of Industrial Oil in Irrigation Ditches. Sensors. 2021; 21 (16):5449.

Chicago/Turabian Style

Daniel A. Basterrechea; Javier Rocher; Lorena Parra; Jaime Lloret. 2021. "Low-Cost System Based on Optical Sensor to Monitor Discharge of Industrial Oil in Irrigation Ditches." Sensors 21, no. 16: 5449.

Research article
Published: 06 July 2021 in Wireless Communications and Mobile Computing
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Spontaneous networks lack an a priori communication infrastructure, the neighbors are unknown right after the deployment, and they are used during a period of time and in a certain location. In this paper, we present a new randomized creation model of a spontaneous wireless ad hoc network based on trusted neighbors. The idea is to manage the neighbor discovery with the exchange of identity cards, and the checking of a signature establishes a relationship based on trust of the neighbors. To asses the performance of our randomized trusted network proposal and compare it against an existing deterministic protocol used as reference, we relied on Castalia 3.2 simulator, regarding 4 metrics: time, energy consumption, throughput, and number of discoveries vs packet sent ratio. We found that our proposal outperforms the reference protocol in terms of time, energy, and discoveries vs packet sent ratio in a one-hop setting, while it outperforms the reference protocol regarding all 4 metrics in multihop environments. We also evaluated our proposal through simulations varying the transmission probability and proved that it does not require to know the number of nodes if a fixed transmission probability is set, providing reasonable results. Moreover, our proposal is based on collision detection, it knows when to terminate the process, it does not require a transmission schedule, and it follows more realistic assumptions. In addition, a qualitative comparison is carried out, comparing our proposal against existing protocols from the literature.

ACS Style

Jose Vicente Sorribes; Lourdes Peñalver; Jaime Lloret. A Spontaneous Wireless Ad Hoc Trusted Neighbor Network Creation Protocol. Wireless Communications and Mobile Computing 2021, 2021, 1 -20.

AMA Style

Jose Vicente Sorribes, Lourdes Peñalver, Jaime Lloret. A Spontaneous Wireless Ad Hoc Trusted Neighbor Network Creation Protocol. Wireless Communications and Mobile Computing. 2021; 2021 ():1-20.

Chicago/Turabian Style

Jose Vicente Sorribes; Lourdes Peñalver; Jaime Lloret. 2021. "A Spontaneous Wireless Ad Hoc Trusted Neighbor Network Creation Protocol." Wireless Communications and Mobile Computing 2021, no. : 1-20.

Journal article
Published: 06 July 2021 in Cluster Computing
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Internet of Things (IoT) has introduced new applications and environments. Smart Home provides new ways of communication and service consumption. In addition, Artificial Intelligence (AI) and deep learning have improved different services and tasks by automatizing them. In this field, reinforcement learning (RL) provides an unsupervised way to learn from the environment. In this paper, a new intelligent system based on RL and deep learning is proposed for Smart Home environments to guarantee good levels of QoE, focused on multimedia services. This system is aimed to reduce the impact on user experience when the classifying system achieves a low accuracy. The experiments performed show that the deep learning model proposed achieves better accuracy than the KNN algorithm and that the RL system increases the QoE of the user up to 3.8 on a scale of 10.

ACS Style

Albert Rego; Pedro Luis González Ramírez; Jose M. Jimenez; Jaime Lloret. Artificial intelligent system for multimedia services in smart home environments. Cluster Computing 2021, 1 .

AMA Style

Albert Rego, Pedro Luis González Ramírez, Jose M. Jimenez, Jaime Lloret. Artificial intelligent system for multimedia services in smart home environments. Cluster Computing. 2021; ():1.

Chicago/Turabian Style

Albert Rego; Pedro Luis González Ramírez; Jose M. Jimenez; Jaime Lloret. 2021. "Artificial intelligent system for multimedia services in smart home environments." Cluster Computing , no. : 1.

Conference paper
Published: 02 July 2021 in Sustainable Smart Cities and Territories
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Wireless ad hoc networks are characterized by a lack of a communications infrastructure after their deployment, and the nodes have limited range radio transceivers to carry out communications. Therefore, neighbor discovery techniques are necessary so that the nodes get to know their one-hop neighbors, that is, the nodes within transmission range. In this article, we proceed to present a new randomized leader-based neighbor discovery protocol for static one-hop networks, which manages to discover all the neighbors with probability 1, know when to terminate the process, following more realistic assumptions. To evaluate the performance of the protocol presented, we rely on Castalia 3.2 simulator, and we also compare the proposal with the Hello protocol chosen from the literature and an existing deterministic leader-based protocol. We found that the proposal presents better results than the Hello protocol regarding four metrics (Neighbor Discovery Time, Number of Discovered Neighbors, Energy consumption and Throughput). In addition, our proposal presents reasonable results in comparison to the deterministic leader-based protocol regarding time, energy and throughput results, and it also allows its use in an asynchronous way.

ACS Style

Jose Vicente Sorribes; Lourdes Peñalver; Jaime Lloret. An Asynchronous Leader-Based Neighbor Discovery Protocol in Static Wireless Ad Hoc Networks. Sustainable Smart Cities and Territories 2021, 145 -161.

AMA Style

Jose Vicente Sorribes, Lourdes Peñalver, Jaime Lloret. An Asynchronous Leader-Based Neighbor Discovery Protocol in Static Wireless Ad Hoc Networks. Sustainable Smart Cities and Territories. 2021; ():145-161.

Chicago/Turabian Style

Jose Vicente Sorribes; Lourdes Peñalver; Jaime Lloret. 2021. "An Asynchronous Leader-Based Neighbor Discovery Protocol in Static Wireless Ad Hoc Networks." Sustainable Smart Cities and Territories , no. : 145-161.

Journal article
Published: 25 June 2021 in Future Generation Computer Systems
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Over the last few years, Software Defined Networking (SDN) paradigm has become an emerging architecture to design future networks and to meet new application demands. SDN provides resources for improving network control and management by separating control and data plane, and the logical control is centralized in a controller. However, the centralized control logic can be an ideal target for malicious attacks, mainly Distributed Denial of Service (DDoS) attacks. Recently, Deep Learning has become a powerful technique applied in cybersecurity, and many Network Intrusion Detection (NIDS) have been proposed in recent researches. Some studies have indicated that deep neural networks are sensitive in detecting adversarial attacks. Adversarial attacks are instances with certain perturbations that cause deep neural networks to misclassify. In this paper, we proposed a detection and defense system based on Adversarial training in SDN , which uses Generative Adversarial Network (GAN) framework for detecting DDoS attacks and applies adversarial training to make the system less sensitive to adversarial attacks. The proposed system includes well-defined modules that enable continuous traffic monitoring using IP flow analysis, enabling the anomaly detection system to act in near-real-time. We conducted the experiments on two distinct scenarios, with emulated data and the public dataset CICDDoS 2019. Experimental results demonstrated that the system efficiently detected up-to-date common types of DDoS attacks compared to other approaches.

ACS Style

Matheus P. Novaes; Luiz F. Carvalho; Jaime Lloret; Mario Lemes Proença. Adversarial Deep Learning approach detection and defense against DDoS attacks in SDN environments. Future Generation Computer Systems 2021, 125, 156 -167.

AMA Style

Matheus P. Novaes, Luiz F. Carvalho, Jaime Lloret, Mario Lemes Proença. Adversarial Deep Learning approach detection and defense against DDoS attacks in SDN environments. Future Generation Computer Systems. 2021; 125 ():156-167.

Chicago/Turabian Style

Matheus P. Novaes; Luiz F. Carvalho; Jaime Lloret; Mario Lemes Proença. 2021. "Adversarial Deep Learning approach detection and defense against DDoS attacks in SDN environments." Future Generation Computer Systems 125, no. : 156-167.

Journal article
Published: 08 June 2021 in Sensors
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Recently, green computing has received significant attention for Internet of Things (IoT) environments due to the growing computing demands under tiny sensor enabled smart services. The related literature on green computing majorly focuses on a cover set approach that works efficiently for target coverage, but it is not applicable in case of area coverage. In this paper, we present a new variant of a cover set approach called a grouping and sponsoring aware IoT framework (GS-IoT) that is suitable for area coverage. We achieve non-overlapping coverage for an entire sensing region employing sectorial sensing. Non-overlapping coverage not only guarantees a sufficiently good coverage in case of large number of sensors deployed randomly, but also maximizes the life span of the whole network with appropriate scheduling of sensors. A deployment model for distribution of sensors is developed to ensure a minimum threshold density of sensors in the sensing region. In particular, a fast converging grouping (FCG) algorithm is developed to group sensors in order to ensure minimal overlapping. A sponsoring aware sectorial coverage (SSC) algorithm is developed to set off redundant sensors and to balance the overall network energy consumption. GS-IoT framework effectively combines both the algorithms for smart services. The simulation experimental results attest to the benefit of the proposed framework as compared to the state-of-the-art techniques in terms of various metrics for smart IoT environments including rate of overlapping, response time, coverage, active sensors, and life span of the overall network.

ACS Style

Vinod Kumar; Sushil Kumar; Rabah AlShboul; Geetika Aggarwal; OmPrakash Kaiwartya; Ahmad Khasawneh; Jaime Lloret; Mahmoud Al-Khasawneh. Grouping and Sponsoring Centric Green Coverage Model for Internet of Things. Sensors 2021, 21, 3948 .

AMA Style

Vinod Kumar, Sushil Kumar, Rabah AlShboul, Geetika Aggarwal, OmPrakash Kaiwartya, Ahmad Khasawneh, Jaime Lloret, Mahmoud Al-Khasawneh. Grouping and Sponsoring Centric Green Coverage Model for Internet of Things. Sensors. 2021; 21 (12):3948.

Chicago/Turabian Style

Vinod Kumar; Sushil Kumar; Rabah AlShboul; Geetika Aggarwal; OmPrakash Kaiwartya; Ahmad Khasawneh; Jaime Lloret; Mahmoud Al-Khasawneh. 2021. "Grouping and Sponsoring Centric Green Coverage Model for Internet of Things." Sensors 21, no. 12: 3948.

Journal article
Published: 31 May 2021 in IEEE Transactions on Intelligent Transportation Systems
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Internet of Vehicles (IoV) is a large interactive network composed of information such as vehicle location, speed and route. Vehicles can collect their own environment and state information through GPS, RFID, sensors, camera image processing, and other devices. They can transmit their various information to the central processing unit through Internet technology. These large amounts of vehicle information can be analyzed and processed through computer technology to calculate the optimal route for different vehicles, and report road conditions in time and schedule signal light cycles. Internet of Vehicles (IoV) is a large-scale system network for wireless communication and information exchange between vehicles and people, vehicles and roads, vehicles and the Internet, which is based on intra-vehicle network, inter-vehicle network and vehicle mobile Internet, in accordance with the agreed communication protocols and data interaction standards. The system realizes the integrated network of intelligent traffic management, intelligent dynamic information service, and intelligent vehicle control by “filtering and cleaning” massive data and processing data on the platform. Internet of Vehicles (IoV) system utilizes advanced IoT technology, cloud computing, and big data to make the system fully aware of roads and traffic. It enables all vehicles to collect information through their own environment and state, and upload all kinds of information to the Internet big data platform. The central processing unit collects, analyzes, and processes a large amount of uploaded information. The system will control every vehicle involved in the traffic and control every road in real time to provide users with traffic efficiency and safety.

ACS Style

ZhiHan Lv; Jaime Lloret; Houbing Song. Guest Editorial Software Defined Internet of Vehicles. IEEE Transactions on Intelligent Transportation Systems 2021, 22, 3504 -3510.

AMA Style

ZhiHan Lv, Jaime Lloret, Houbing Song. Guest Editorial Software Defined Internet of Vehicles. IEEE Transactions on Intelligent Transportation Systems. 2021; 22 (6):3504-3510.

Chicago/Turabian Style

ZhiHan Lv; Jaime Lloret; Houbing Song. 2021. "Guest Editorial Software Defined Internet of Vehicles." IEEE Transactions on Intelligent Transportation Systems 22, no. 6: 3504-3510.

Journal article
Published: 27 May 2021 in Electronics
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The Internet of Medical Things (IoMT) has shown incredible development with the growth of medical systems using wireless information technologies. Medical devices are biosensors that can integrate with physical things to make smarter healthcare applications that are collaborated on the Internet. In recent decades, many applications have been designed to monitor the physical health of patients and support expert teams for appropriate treatment. The medical devices are attached to patients’ bodies and connected with a cloud computing system for obtaining and analyzing healthcare data. However, such medical devices operate on battery powered sensors with limiting constraints in terms of memory, transmission, and processing resources. Many healthcare solutions are helping the community with the efficient monitoring of patients’ conditions using cloud computing, however, mostly incur latency in data collection and storage. Therefore, this paper presents a model for the Secured Big Data analytics using Edge–Cloud architecture (SBD-EC), which aims to provide distributed and timely computation of a decision-oriented medical system. Moreover, the mobile edges cooperate with the cloud level to present a secure algorithm, achieving reliable availability of medical data with privacy and security against malicious actions. The performance of the proposed model is evaluated in simulations and the results obtained demonstrate significant improvement over other solutions.

ACS Style

Amjad Rehman; Khalid Haseeb; Tanzila Saba; Jaime Lloret; Usman Tariq. Secured Big Data Analytics for Decision-Oriented Medical System Using Internet of Things. Electronics 2021, 10, 1273 .

AMA Style

Amjad Rehman, Khalid Haseeb, Tanzila Saba, Jaime Lloret, Usman Tariq. Secured Big Data Analytics for Decision-Oriented Medical System Using Internet of Things. Electronics. 2021; 10 (11):1273.

Chicago/Turabian Style

Amjad Rehman; Khalid Haseeb; Tanzila Saba; Jaime Lloret; Usman Tariq. 2021. "Secured Big Data Analytics for Decision-Oriented Medical System Using Internet of Things." Electronics 10, no. 11: 1273.

Article
Published: 10 May 2021 in Multimedia Tools and Applications
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Nowadays, heterogeneous devices are widely utilizing Hypertext Transfer Protocol (HTTP) to transfer the data. Furthermore, HTTP adaptive video streaming (HAS) technology transmits the video data over wired and wireless networks. In adaptive technology services, a client’s application receives a streaming video through the adaptation of its quality to the network condition. However, such a technology has increased the demand for Quality of Experience (QoE) in terms of prediction and assessment. It can also cause a challenging behavior regarding subjective and objective QoE evaluations of HTTP adaptive video over time since each Quality of Service (QoS) parameter affects the QoE of end-users separately. This paper introduces a methodology design for the evaluation of subjective QoE in adaptive video streaming over wireless networks. Besides, some parameters are considered such as video characteristics, segment length, initial delay, switch strategy, stalls, as well as QoS parameters. The experiment’s evaluation demonstrated that objective metrics can be mapped to the most significant subjective parameters for user’s experience. The automated model could function to demonstrate the importance of correlation for network behaviors’ parameters. Consequently, it directly influences the satisfaction of the end-user’s perceptual quality. In comparison with other recent related works, the model provided a positive Pearson Correlation value. Simulated results give a better performance between objective Structural Similarity (SSIM) and subjective Mean Opinion Score (MOS) evaluation metrics for all video test samples.

ACS Style

Miran Taha; Aree Ali; Jaime Lloret; Paulo R. L. Gondim; Alejandro Canovas. An automated model for the assessment of QoE of adaptive video streaming over wireless networks. Multimedia Tools and Applications 2021, 1 -22.

AMA Style

Miran Taha, Aree Ali, Jaime Lloret, Paulo R. L. Gondim, Alejandro Canovas. An automated model for the assessment of QoE of adaptive video streaming over wireless networks. Multimedia Tools and Applications. 2021; ():1-22.

Chicago/Turabian Style

Miran Taha; Aree Ali; Jaime Lloret; Paulo R. L. Gondim; Alejandro Canovas. 2021. "An automated model for the assessment of QoE of adaptive video streaming over wireless networks." Multimedia Tools and Applications , no. : 1-22.

Journal article
Published: 04 May 2021 in IEEE Transactions on Wireless Communications
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The hardware realization of Universal Filtered Multi Carrier (UFMC) architecture has attracted significant attention in fifth generation (5G) and beyond. In addition to the flexibility in fast Fourier transform (FFT)-length, a flexible prototype filter in combination with multiplicative complex spectrum shifting co-efficients is required for realizing flexible UFMC architecture. The existing architectures of UFMC transmitter commonly adopted fixed-size FFT-length, number of subbands, subband size, and filter-length. Moreover, the lack of flexible prototype filter and spectrum localization of filter co-efficients to individual subbands limits the flexible UFMC system design. In this paper, we propose VLSI architecture for a flexible length prototype filter that can generate spectrally shifted filter co-efficients to individual subbands in tune with the changing value of FFT-length, number of subbands, subband size, and filter-length. For 16-bit word size architecture, our proposed design produces filter co-efficients and spectrum shifting co-efficients upto length, 215. Thus, any desired combination of FFT-length, number of subbands, subband size and filter-length is selected to generate the filter co-efficients for the individual subbands. Moreover, complex multiplication and addition operations are reduced in proposed architecture, quantitatively, about 58.81% reduction in filtering unit is achieved over the state-of-the-art architecture. Finally, hardware implementation output and XILINX post route simulation result matches perfectly with MATLAB simulations.

ACS Style

Vikas Kumar; Mithun Mukherjee; Jaime Lloret; Zhenwen Ren; Mamta Kumari. A Joint Filter and Spectrum Shifting Architecture for Low Complexity Flexible UFMC in 5G. IEEE Transactions on Wireless Communications 2021, PP, 1 -1.

AMA Style

Vikas Kumar, Mithun Mukherjee, Jaime Lloret, Zhenwen Ren, Mamta Kumari. A Joint Filter and Spectrum Shifting Architecture for Low Complexity Flexible UFMC in 5G. IEEE Transactions on Wireless Communications. 2021; PP (99):1-1.

Chicago/Turabian Style

Vikas Kumar; Mithun Mukherjee; Jaime Lloret; Zhenwen Ren; Mamta Kumari. 2021. "A Joint Filter and Spectrum Shifting Architecture for Low Complexity Flexible UFMC in 5G." IEEE Transactions on Wireless Communications PP, no. 99: 1-1.

Journal article
Published: 18 April 2021 in Applied Sciences
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Water quality may be affected by aspects such as pollution from industries, agricultural fertilizers and pesticides, and waste produced by humans. This contamination can affect the produce of the fields irrigated by untreated water. Therefore, it is necessary to add a treatment process in irrigation systems. In this paper, an architecture, communication protocol, and a data analysis algorithm for a wastewater treatment system intended for irrigation are presented. Our system includes a smart group-based wireless sensor network that is able to detect high salinity levels and pollution stains, such as oil spills. When contamination is detected, the water is led into auxiliary canals that perform the biosorption process to treat the water and dump it back into the main canal. Simulations were performed to assess the amount of data stored on the secure digital (SD) card, the consumed bandwidth, and the energy consumption of our proposal. The results show the system has a low bandwidth consumption with a maximum of 2.58 kbps for the setting of two daily data transmissions of the node in the last auxiliary canal. Furthermore, it can sustain the energy consumption in adverse conditions, where the node with the highest energy consumption reaches the lowest energy value of 12,320 mW/h.

ACS Style

Jose Jimenez; Lorena Parra; Laura García; Jaime Lloret; Pedro Mauri; Pascal Lorenz. New Protocol and Architecture for a Wastewater Treatment System Intended for Irrigation. Applied Sciences 2021, 11, 3648 .

AMA Style

Jose Jimenez, Lorena Parra, Laura García, Jaime Lloret, Pedro Mauri, Pascal Lorenz. New Protocol and Architecture for a Wastewater Treatment System Intended for Irrigation. Applied Sciences. 2021; 11 (8):3648.

Chicago/Turabian Style

Jose Jimenez; Lorena Parra; Laura García; Jaime Lloret; Pedro Mauri; Pascal Lorenz. 2021. "New Protocol and Architecture for a Wastewater Treatment System Intended for Irrigation." Applied Sciences 11, no. 8: 3648.

Article
Published: 27 March 2021 in Telecommunication Systems
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Neighbor discovery represents a first step after the deployment of wireless ad hoc networks, since the nodes that form them are equipped with limited-range radio transceivers, and they typically do not know their neighbors. In this paper two randomized neighbor discovery approaches, called CDH and CDPRR, based on collision detection for static multi-hop wireless ad hoc networks, are presented. Castalia 3.2 simulator has been used to compare our proposed protocols against two protocols chosen from the literature and used as reference: the PRR, and the Hello protocol. For the experiments, we chose five metrics: the neighbor discovery time, the number of discovered neighbors, the energy consumption, the throughput and the number of discovered neighbors versus packets sent ratio. According to the results obtained through simulation, we can conclude that our randomized proposals outperform both Hello and PRR protocols in the presence of collisions regarding all five metrics, for both one-hop and multi-hop scenarios. As novelty compared to the reference protocols, both proposals allow nodes to discover all their neighbors with probability 1, they are based on collision detection and know when to terminate the neighbor discovery process. Furthermore, qualitative comparisons of the existing protocols and the proposals are available in this paper. Moreover, CDPRR presents better results in terms of time, energy consumption and number of discovered neighbors versus packets sent ratio. We found that both proposals achieve to operate under more realistic assumptions. Furthermore, CDH does not need to know the number of nodes in the network.

ACS Style

Jose Vicente Sorribes; Lourdes Peñalver; Carlos Tavares Calafate; Jaime Lloret. Randomized neighbor discovery protocols with collision detection for static multi-hop wireless ad hoc networks. Telecommunication Systems 2021, 77, 577 -596.

AMA Style

Jose Vicente Sorribes, Lourdes Peñalver, Carlos Tavares Calafate, Jaime Lloret. Randomized neighbor discovery protocols with collision detection for static multi-hop wireless ad hoc networks. Telecommunication Systems. 2021; 77 (3):577-596.

Chicago/Turabian Style

Jose Vicente Sorribes; Lourdes Peñalver; Carlos Tavares Calafate; Jaime Lloret. 2021. "Randomized neighbor discovery protocols with collision detection for static multi-hop wireless ad hoc networks." Telecommunication Systems 77, no. 3: 577-596.

Guest editorial
Published: 23 March 2021 in Journal of Real-Time Image Processing
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In the last few years, remarkable progress has been made in mobile consumer devices. Modern smartphones and tablet computers offer multi-core processors and graphics processing units, which have opened up new application possibilities such as augmented reality, virtual reality, and 3D reconstruction. Augmented Reality (AR) is a key technology that is going to facilitate a paradigm shift in the way users interact with data and has only just recently been recognized as a viable solution for solving many critical needs.

ACS Style

ZhiHan Lv; Jaime Lloret; Houbing Song. Real-time image processing for augmented reality on mobile devices. Journal of Real-Time Image Processing 2021, 18, 245 -248.

AMA Style

ZhiHan Lv, Jaime Lloret, Houbing Song. Real-time image processing for augmented reality on mobile devices. Journal of Real-Time Image Processing. 2021; 18 (2):245-248.

Chicago/Turabian Style

ZhiHan Lv; Jaime Lloret; Houbing Song. 2021. "Real-time image processing for augmented reality on mobile devices." Journal of Real-Time Image Processing 18, no. 2: 245-248.

Journal article
Published: 23 March 2021 in Sensors
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The irrigation of green areas in cities should be managed appropriately to ensure its sustainability. In large cities, not all green areas might be monitored simultaneously, and the data acquisition time can skew the gathered value. Our purpose is to evaluate which parameter has a lower hourly variation. We included soil parameters (soil temperature and moisture) and plant parameters (canopy temperature and vegetation indexes). Data were gathered at 5 different hours in 11 different experimental plots with variable irrigation and with different grass composition. The results indicate that soil moisture and Normalized Difference Vegetation Index are the sole parameters not affected by the data acquisition time. For soil moisture, the maximum difference was in experimental plot 4, with values of 21% at 10:45 AM and 27% at 8:45 AM. On the other hand, canopy temperature is the most affected parameter with a mean variation of 15 °C in the morning. The maximum variation was in experimental plot 8 with a 19 °C at 8:45 AM and 39 °C at 12:45 PM. Data acquisition time affected the correlation between soil moisture and canopy temperature. We can affirm that data acquisition time has to be included as a variability source. Finally, our conclusion indicates that it is vital to consider data acquisition time to ensure water distribution for irrigation in cities.

ACS Style

Pedro Mauri; Lorena Parra; Salima Yousfi; Jaime Lloret; Jose Marin. Evaluating the Effects of Environmental Conditions on Sensed Parameters for Green Areas Monitoring and Smart Irrigation Systems. Sensors 2021, 21, 2255 .

AMA Style

Pedro Mauri, Lorena Parra, Salima Yousfi, Jaime Lloret, Jose Marin. Evaluating the Effects of Environmental Conditions on Sensed Parameters for Green Areas Monitoring and Smart Irrigation Systems. Sensors. 2021; 21 (6):2255.

Chicago/Turabian Style

Pedro Mauri; Lorena Parra; Salima Yousfi; Jaime Lloret; Jose Marin. 2021. "Evaluating the Effects of Environmental Conditions on Sensed Parameters for Green Areas Monitoring and Smart Irrigation Systems." Sensors 21, no. 6: 2255.

Journal article
Published: 18 March 2021 in Agronomy
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The excessive use of chemical fertilizers can lead to severe environmental damages. In recent decades, the application of biostimulants to improve soil composition and stimulate plant growth has contributed significantly to environmental preservation. In this paper, we studied the effect of a rhizogenic biostimulant, obtained from fulvic acids, probiotics, and prebiotics, on the fertility of two types of soils, sandy and sandy loam soils, in which turfgrass was growing. Soil samples from plots treated with biostimulant and controls (untreated plots) were collected. The analyzed parameters from the soil include organic matter, microbial activity, soil chemical composition, catalase, dehydrogenase, and phosphatase enzyme activities. Moreover, root lengths was examined and compared in turfgrass species. The biostimulant application improved microbial activity, organic matter, and enzymatic activity in both types of soils. The soil calcium, potassium, magnesium, and phosphorus content increased with the biostimulant application, whereas pH and electrical conductivity decreased. The most relevant improvement was a 77% increase of calcium for sandy loam soil and 38% increase in potassium for sandy soil. Biostimulant application led to a significant increase in turf root length. This increase was greater for sandy soil than in sandy loam soil with an increment of 43% and 34% respectively, compared to control.

ACS Style

Salima Yousfi; José Marín; Lorena Parra; Jaime Lloret; Pedro Mauri. A Rhizogenic Biostimulant Effect on Soil Fertility and Roots Growth of Turfgrass. Agronomy 2021, 11, 573 .

AMA Style

Salima Yousfi, José Marín, Lorena Parra, Jaime Lloret, Pedro Mauri. A Rhizogenic Biostimulant Effect on Soil Fertility and Roots Growth of Turfgrass. Agronomy. 2021; 11 (3):573.

Chicago/Turabian Style

Salima Yousfi; José Marín; Lorena Parra; Jaime Lloret; Pedro Mauri. 2021. "A Rhizogenic Biostimulant Effect on Soil Fertility and Roots Growth of Turfgrass." Agronomy 11, no. 3: 573.

Research article
Published: 17 March 2021 in Wireless Communications and Mobile Computing
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The last decade has witnessed a steep growth in multimedia traffic due to real-time content delivery such as in online games and video conferencing. In some contexts, MANETs play a key role in the hyperconnectivity of everything in multimedia services. In this context, this work proposes a new scheduling approach based on context-aware mobile nodes for their connectivity. The contribution relies on reporting not only the locations of devices in the network but also their movement identified by sensors. In order to illustrate this approach, we have developed a novel agent-based simulator called MASEMUL for illustrating the proposed approach. The results show that a movement-aware scheduling strategy defined with the proposed approach has decreased the ratio of channel interruptions over another common strategy in mobile networks.

ACS Style

Moustafa M. Nasralla; Iván García-Magariño; Jaime Lloret. MASEMUL: A Simulation Tool for Movement-Aware MANET Scheduling Strategies for Multimedia Communications. Wireless Communications and Mobile Computing 2021, 2021, 1 -12.

AMA Style

Moustafa M. Nasralla, Iván García-Magariño, Jaime Lloret. MASEMUL: A Simulation Tool for Movement-Aware MANET Scheduling Strategies for Multimedia Communications. Wireless Communications and Mobile Computing. 2021; 2021 ():1-12.

Chicago/Turabian Style

Moustafa M. Nasralla; Iván García-Magariño; Jaime Lloret. 2021. "MASEMUL: A Simulation Tool for Movement-Aware MANET Scheduling Strategies for Multimedia Communications." Wireless Communications and Mobile Computing 2021, no. : 1-12.

Conference paper
Published: 11 March 2021 in Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Water is a natural resource necessary for life that must be taken care of. In coastal areas with near agricultural activity, it is very common to detect spills of chemical products that affect water quality of rivers and beaches. This water usually reaches the sea with bad consequences for nature and, therefore, it is important to detect where possible spills are taking place and water does not have enough quality to be used. This paper presents the development of a LoRa (Long Range) based wireless sensor network to create an observatory of water quality in coastal areas. This network consists of wireless nodes endowed with several sensors that allow measuring physical parameters of water quality, such as turbidity, temperature, etc. The data collected by the sensors will be sent to a gateway that will redirect them to a database. The database creates an observatory that will allow monitoring the environment where the network is deployed in real time. Finally, the developed system will be tested in a real environment for its correct start-up. Two different tests will be performed. The first one will check the correct operation of sensors and network architecture; the second test will check the network coverage of the commercial devices.

ACS Style

Sandra Sendra; Marta Botella-Campos; Jaime Lloret; Jose Miguel Jimenez. Wireless Sensor Network to Create a Water Quality Observatory in Coastal Areas. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2021, 100 -118.

AMA Style

Sandra Sendra, Marta Botella-Campos, Jaime Lloret, Jose Miguel Jimenez. Wireless Sensor Network to Create a Water Quality Observatory in Coastal Areas. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. 2021; ():100-118.

Chicago/Turabian Style

Sandra Sendra; Marta Botella-Campos; Jaime Lloret; Jose Miguel Jimenez. 2021. "Wireless Sensor Network to Create a Water Quality Observatory in Coastal Areas." Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering , no. : 100-118.