Showing items 21 - 38 of 38

Deep deterministic learning for pattern recognition of different cardiac diseases through the internet of medical things

- Iqbal, Uzair, Wah, Teh, Habib ur Rehman, Muhammad, Mujtaba, Ghulam, Imran, Muhammad, Shoaib, Muhammad

  • Authors: Iqbal, Uzair , Wah, Teh , Habib ur Rehman, Muhammad , Mujtaba, Ghulam , Imran, Muhammad , Shoaib, Muhammad
  • Date: 2018
  • Type: Text , Journal article
  • Relation: Journal of Medical Systems Vol. 42, no. 12 (2018), p.
  • Full Text: false
  • Reviewed:
  • Description: Electrocardiography (ECG) sensors play a vital role in the Internet of Medical Things, and these sensors help in monitoring the electrical activity of the heart. ECG signal analysis can improve human life in many ways, from diagnosing diseases among cardiac patients to managing the lifestyles of diabetic patients. Abnormalities in heart activities lead to different cardiac diseases and arrhythmia. However, some cardiac diseases, such as myocardial infarction (MI) and atrial fibrillation (Af), require special attention due to their direct impact on human life. The classification of flattened T wave cases of MI in ECG signals and how much of these cases are similar to ST-T changes in MI remain an open issue for researchers. This article presents a novel contribution to classify MI and Af. To this end, we propose a new approach called deep deterministic learning (DDL), which works by combining predefined heart activities with fused datasets. In this research, we used two datasets. The first dataset, Massachusetts Institute of Technology–Beth Israel Hospital, is publicly available, and we exclusively obtained the second dataset from the University of Malaya Medical Center, Kuala Lumpur Malaysia. We first initiated predefined activities on each individual dataset to recognize patterns between the ST-T change and flattened T wave cases and then used the data fusion approach to merge both datasets in a manner that delivers the most accurate pattern recognition results. The proposed DDL approach is a systematic stage-wise methodology that relies on accurate detection of R peaks in ECG signals, time domain features of ECG signals, and fine tune-up of artificial neural networks. The empirical evaluation shows high accuracy (i.e., ≤99.97%) in pattern matching ST-T changes and flattened T waves using the proposed DDL approach. The proposed pattern recognition approach is a significant contribution to the diagnosis of special cases of MI. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.

Deep learning-based approach for detecting trajectory modifications of cassini-huygens spacecraft

- Aldabbas, Ashraf, Gal, Zoltan, Ghori, Khawaja, Imran, Muhammad, Shoaib, Muhammad

  • Authors: Aldabbas, Ashraf , Gal, Zoltan , Ghori, Khawaja , Imran, Muhammad , Shoaib, Muhammad
  • Date: 2021
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 9, no. (2021), p. 39111-39125
  • Full Text:
  • Reviewed:
  • Description: There were necessary trajectory modifications of Cassini spacecraft during its last 14 years movement cycle of the interplanetary research project. In the scale 1.3 hour of signal propagation time and 1.4-billion-kilometer size of Earth-Cassini channel, complex event detection in the orbit modifications requires special investigation and analysis of the collected big data. The technologies for space exploration warrant a high standard of nuanced and detailed research. The Cassini mission has accumulated quite huge volumes of science records. This generated a curiosity derives mainly from a need to use machine learning to analyze deep space missions. For energy saving considerations, the communication between the Earth and Cassini was executed in non-periodic mode. This paper provides a sophisticated in-depth learning approach for detecting Cassini spacecraft trajectory modifications in post-processing mode. The proposed model utilizes the ability of Long Short Term Memory (LSTM) neural networks for drawing out useful data and learning the time series inner data pattern, along with the forcefulness of LSTM layers for distinguishing dependencies among the long-short term. Our research study exploited the statistical rates, Matthews correlation coefficient, and F1 score to evaluate our models. We carried out multiple tests and evaluated the provided approach against several advanced models. The preparatory analysis showed that exploiting the LSTM layer provides a notable boost in rising the detection process performance. The proposed model achieved a number of 232 trajectory modification detections with 99.98% accuracy among the last 13.35 years of the Cassini spacecraft life. © 2013 IEEE.

Efficient data gathering in 3D linear underwater wireless sensor networks using sink mobility

- Akbar, Mariam, Javaid, Nadeem, Khan, Ayesha, Imran, Muhammad, Shoaib, Muhammad, Vasilakos, Athanasios

  • Authors: Akbar, Mariam , Javaid, Nadeem , Khan, Ayesha , Imran, Muhammad , Shoaib, Muhammad , Vasilakos, Athanasios
  • Date: 2016
  • Type: Text , Journal article
  • Relation: Sensors (Switzerland) Vol. 16, no. 3 (2016), p.
  • Full Text:
  • Reviewed:
  • Description: Due to the unpleasant and unpredictable underwater environment, designing an energy-efficient routing protocol for underwater wireless sensor networks (UWSNs) demands more accuracy and extra computations. In the proposed scheme, we introduce a mobile sink (MS), i.e., an autonomous underwater vehicle (AUV), and also courier nodes (CNs), to minimize the energy consumption of nodes. MS and CNs stop at specific stops for data gathering; later on, CNs forward the received data to the MS for further transmission. By the mobility of CNs and MS, the overall energy consumption of nodes is minimized. We perform simulations to investigate the performance of the proposed scheme and compare it to preexisting techniques. Simulation results are compared in terms of network lifetime, throughput, path loss, transmission loss and packet drop ratio. The results show that the proposed technique performs better in terms of network lifetime, throughput, path loss and scalability. © 2016 by the authors; licensee MDPI, Basel, Switzerland.

Electric Load Forecasting using EEMD and machine learning techniques

- Naz, Aqdas, Javaid, Nadeem, Khalid, Adia, Shoaib, Muhammad, Imran, Muhammad

Electricity theft detection using pipeline in machine learning

- Anwar, Mubbashra, Javaid, Nadeem, Khalid, Adia, Imran, Muhammad, Shoaib, Muhammad

  • Authors: Anwar, Mubbashra , Javaid, Nadeem , Khalid, Adia , Imran, Muhammad , Shoaib, Muhammad
  • Date: 2020
  • Type: Text , Conference paper
  • Relation: 16th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2020, Limassol, Cyprus, 15 to 19 June 2020, 2020 International Wireless Communications and Mobile Computing, IWCMC 2020 p. 2138-2142
  • Full Text: false
  • Reviewed:
  • Description: Electricity theft is the primary cause of electrical power loss that significantly affects the revenue loss and the quality of electrical power. Nevertheless, the existing methods for the detection of this criminal behavior of theft are diversified and complicated since the imbalanced nature of the dataset, and high dimensionality of time-series data make it challenging to extract meaningful information. This paper addresses these problems by developing a novel electricity theft detection model, integrating three algorithms in a pipeline. The proposed method first applies the synthetic minority oversampling technique (SMOTE) for balancing the dataset, secondly integration of kernel function and principal component analysis (KPCA) for the feature extraction from high dimensional time-series data, and support vector machine (SVM) for the classification. Besides, the performance of the proposed pipeline is measured using a comprehensive list of performance metrics. Extensive experiments are performed by using real electricity consumption data, and results show that the proposed method outperforms other methods in terms of theft detection. © 2020 IEEE.

Have you been a victim of COVID-19-related cyber incidents? Survey, taxonomy, and mitigation strategies

- Hakak, Saqib, Khan, Wazir, Imran, Muhammad, Choo, Kim-Kwang, Shoaib, Muhammad

  • Authors: Hakak, Saqib , Khan, Wazir , Imran, Muhammad , Choo, Kim-Kwang , Shoaib, Muhammad
  • Date: 2020
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 8, no. (2020), p. 124134-124144
  • Full Text:
  • Reviewed:
  • Description: Cybercriminals are constantly on the lookout for new attack vectors, and the recent COVID-19 pandemic is no exception. For example, social distancing measures have resulted in travel bans, lockdowns, and stay-at-home orders, consequently increasing the reliance on information and communications technologies, such as Zoom. Cybercriminals have also attempted to exploit the pandemic to facilitate a broad range of malicious activities, such as attempting to take over videoconferencing platforms used in online meetings/educational activities, information theft, and other fraudulent activities. This study briefly reviews some of the malicious cyber activities associated with COVID-19 and the potential mitigation solutions. We also propose an attack taxonomy, which (optimistically) will help guide future risk management and mitigation responses. © 2013 IEEE.

Impact of node deployment and routing for protection of critical infrastructures

- Subhan, Fazli, Noreen, Madiha, Imran, Muhammad, Tariq, Moeenuddin, Khan, Asfandyar, Shoaib, Muhammad

  • Authors: Subhan, Fazli , Noreen, Madiha , Imran, Muhammad , Tariq, Moeenuddin , Khan, Asfandyar , Shoaib, Muhammad
  • Date: 2019
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 7, no. (2019), p. 11502-11514
  • Full Text:
  • Reviewed:
  • Description: Recently, linear wireless sensor networks (LWSNs) have been eliciting increasing attention because of their suitability for applications such as the protection of critical infrastructures. Most of these applications require LWSN to remain operational for a longer period. However, the non-replenishable limited battery power of sensor nodes does not allow them to meet these expectations. Therefore, a shorter network lifetime is one of the most prominent barriers in large-scale deployment of LWSN. Unlike most existing studies, in this paper, we analyze the impact of node placement and clustering on LWSN network lifetime. First, we categorize and classify existing node placement and clustering schemes for LWSN and introduce various topologies for disparate applications. Then, we highlight the peculiarities of LWSN applications and discuss their unique characteristics. Several application domains of LWSN are described. We present three node placement strategies (i.e., linear sequential, linear parallel, and grid) and various deployment methods such as random, uniform, decreasing distance, and triangular. Extensive simulation experiments are conducted to analyze the performance of the three state-of-the-art routing protocols in the context of node deployment strategies and methods. The experimental results demonstrate that the node deployment strategies and methods significantly affect LWSN lifetime. © 2013 IEEE.

Link and stability-aware adaptive cooperative routing with restricted packets transmission and void-avoidance for underwater acoustic wireless sensor networks

- Khan, Anwar, Imran, Muhammad, Shoaib, Muhammad, Rahman, Atiq, Sama, Najmus

  • Authors: Khan, Anwar , Imran, Muhammad , Shoaib, Muhammad , Rahman, Atiq , Sama, Najmus
  • Date: 2022
  • Type: Text , Journal article
  • Relation: Computer Communications Vol. 181, no. (2022), p. 428-437
  • Full Text: false
  • Reviewed:
  • Description: In underwater acoustic wireless sensor networks (UAWSNs), the conventional routing protocols continuously transmit data packets containing the same information when a source node detects an event of interest. This approach, however, leads to high energy consumption, high interference and challenges the stability of the network due to heavy data load on the nodes close to water surface. To overcome these challenges, this article proposes two routing protocols for UAWSNs. They are, SRRPV: stability-aware routing with restricted packets transmission and void-avoidance and LS-ACRPV: link and stability-aware adaptive cooperative routing with restricted packets transmission and void-avoidance. In SRRPV, a source node detects the event of interest, generates and routes packets. Subsequent packets routing is performed only when a change in intensity of the event is detected. Due to restricted packets transmission, three-hop connected paths with suitable neighbors are chosen to overcome the existence of a void (non-availability of a suitable forwarder) and, therefore, control packets loss. Moreover, the defined packet holding time ensures that nodes with the highest available energy transfer the most packets by holding the packets for the shortest interval of time. This strategy, in combination with restricted packets transmission, achieves network stability. Since limited number of packets are routed, the LS-ACRPV protocol is designed that adds reliability to the SRRPV protocol by selecting a routing link with the highest probability of successfully delivering packets to the destination or using adaptive cooperative routing to combat severe link conditions. Unlike the conventional protocols, the proposed protocols do not require the geographical position coordinates of nodes, which is challenging in underwater environment as nodes change their positions with sea tides and currents. Extensive simulation results reveal promising performance of the proposed schemes in terms of energy expenditure, delay and network stability at the expense of low packets delivery due to restricted packets transmission. © 2021 Elsevier B.V.

Mobile crowd sensing – taxonomy, applications, challenges, and solutions

- Boubiche, Djallel, Imran, Muhammad, Maqsood, Aneela, Shoaib, Muhammad

  • Authors: Boubiche, Djallel , Imran, Muhammad , Maqsood, Aneela , Shoaib, Muhammad
  • Date: 2019
  • Type: Text , Journal article
  • Relation: Computers in Human Behavior Vol. 101, no. (2019), p. 352-370
  • Full Text: false
  • Reviewed:
  • Description: Recently, mobile crowd sensing (MCS) is captivating growing attention because of their suitability for enormous range of new types of context-aware applications and services. This is attributed to the fact that modern smartphones are equipped with unprecedented sensing, computing, and communication capabilities that allow them to perform more complex tasks besides their inherent calling features. Despite a number of merits, MCS confronts new challenges due to network dynamics, the huge volume of data, sensing task coordination, and the user privacy problems. In this paper, a comprehensive review of MCS is presented. First, we highlight the distinguishing features and potential advantages of MCS compared to conventional sensor networks. Then, a taxonomy of MCS is devised based on sensing scale, level of user involvement and responsiveness, sampling rate, and underlying network infrastructure. Afterward, we categorize and classify prominent applications of MCS in environmental, infrastructure, social, and behavioral domains. The core architecture of MCS is also described. Finally, we describe the potential advantages, determine and reiterate the open research challenges of MCS and illustrate possible solutions. © 2018 Elsevier Ltd

Novel one time signatures (NOTS) : a compact post-quantum digital signature scheme

- Shahid, Furqan, Ahmad, Iftikhar, Imran, Muhammad, Shoaib, Muhammad

  • Authors: Shahid, Furqan , Ahmad, Iftikhar , Imran, Muhammad , Shoaib, Muhammad
  • Date: 2020
  • Type: Text , Journal article
  • Relation: IEEE access Vol. 8, no. (2020), p. 15895-15906
  • Full Text:
  • Reviewed:
  • Description: The future of the hash based digital signature schemes appears to be very bright in the upcoming quantum era because of the quantum threats to the number theory based digital signature schemes. The Shor's algorithm is available to allow a sufficiently powerful quantum computer to break the building blocks of the number theory based signature schemes in a polynomial time. The hash based signature schemes being quite efficient and provably secure can fill in the gap effectively. However, a draw back of the hash based signature schemes is the larger key and signature sizes which can prove a barrier in their adoption by the space critical applications, like the blockchain. A hash based signature scheme is constructed using a one time signature (OTS) scheme. The underlying OTS scheme plays an important role in determining key and signature sizes of a hash based signature scheme. In this article, we have proposed a novel OTS scheme with minimized key and signature sizes as compared to all of the existing OTS schemes. Our proposed OTS scheme offers an 88% reduction in both key and signature sizes as compared to the popular Winternitz OTS scheme. Furthermore, our proposed OTS scheme offers an 84% and an 86% reductions in the signature and the key sizes respectively as compared to an existing compact variant of the WOTS scheme, i.e. WOTS + .

Protection of records and data authentication based on secret shares and watermarking

- Ali, Zulfiqar, Imran, Muhammad, McClean, Sally, Khan, Naveed, Shoaib, Muhammad

  • Authors: Ali, Zulfiqar , Imran, Muhammad , McClean, Sally , Khan, Naveed , Shoaib, Muhammad
  • Date: 2019
  • Type: Text , Journal article
  • Relation: Future Generation Computer Systems Vol. 98, no. (2019), p. 331-341
  • Full Text:
  • Reviewed:
  • Description: The rapid growth in communication technology facilitates the health industry in many aspects from transmission of sensor's data to real-time diagnosis using cloud-based frameworks. However, the secure transmission of data and its authenticity become a challenging task, especially, for health-related applications. The medical information must be accessible to only the relevant healthcare staff to avoid any unfortunate circumstances for the patient as well as for the healthcare providers. Therefore, a method to protect the identity of a patient and authentication of transmitted data is proposed in this study. The proposed method provides dual protection. First, it encrypts the identity using Shamir's secret sharing scheme without the increase in dimension of the original identity. Second, the identity is watermarked using zero-watermarking to avoid any distortion into the host signal. The experimental results show that the proposed method encrypts, embeds and extracts identities reliably. Moreover, in case of malicious attack, the method distorts the embedded identity which provides a clear indication of fabrication. An automatic disorder detection system using Mel-frequency cepstral coefficients and Gaussian mixture model is also implemented which concludes that malicious attacks greatly impact on the accurate diagnosis of disorders. © 2019 Elsevier B.V.

Resource optimization‐based software risk reduction model for large‐scale application development

- Shahzad, Basit, Amin, Fazal-e, Abro, Ahsanullah, Imran, Muhammad, Shoaib, Muhammad

  • Authors: Shahzad, Basit , Amin, Fazal-e , Abro, Ahsanullah , Imran, Muhammad , Shoaib, Muhammad
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Sustainability (Switzerland) Vol. 13, no. 5 (2021), p. 1-17
  • Full Text:
  • Reviewed:
  • Description: Software risks are a common phenomenon in the software development lifecycle, and risks emerge into larger problems if they are not dealt with on time. Software risk management is a strategy that focuses on the identification, management, and mitigation of the risk factors in the software development lifecycle. The management itself depends on the nature, size, and skill of the project under consideration. This paper proposes a model that deals with identifying and dealing with the risk factors by introducing different observatory and participatory project factors. It is as-sumed that most of the risk factors can be dealt with by doing effective business processing that in response deals with the orientation of risks and elimination or reduction of those risk factors that emerge over time. The model proposes different combinations of resource allocation that can help us conclude a software project with an extended amount of acceptability. This paper presents a Risk Reduction Model, which effectively handles the application development risks. The model can syn-chronize its working with medium to large‐scale software projects. The reduction in software failures positively affects the software development environment, and the software failures shall re-duce consequently. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Self-aware autonomous city : from sensing to planning

- Chen, Bo-Wei, Imran, Muhammad, Nasser, Nidal, Shoaib, Muhammad

  • Authors: Chen, Bo-Wei , Imran, Muhammad , Nasser, Nidal , Shoaib, Muhammad
  • Date: 2019
  • Type: Text , Journal article
  • Relation: IEEE Communications Magazine Vol. 57, no. 4 (2019), p. 33-39
  • Full Text: false
  • Reviewed:
  • Description: This article presents a knowledge mining model, where a city can plan its development based on existing knowledge during city expansion, for example, telecommunication resource allocation and crowd forecasts in a new region. Unlike most works that focused on Internet-of-Things (IoT) sensing, this study is aimed at urban planning by using harvested data, from the perspective of city architects. For large-scale metropolitan areas, a massive amount of data is generated every day, either from static surveys or dynamic IoT sensing. For urban planners, data collection is not their primary concern. How to transfer harvested knowledge from exiting parts of the city to suburban/rural/untapped areas is a new challenge. This is because those areas still lack sufficient statistics, and the density of IoT deployment is low. Therefore, development is risky and uncertain. To exploit new regions requires knowledge inference. Such a transition needs data interpretation from historical city dynamics, involving sensor deployment, human activities, and resource allocation in the vicinity. With the proposed model, a city can estimate the requirement for resources when the peripheral areas on the outskirts of a city develop. The same model can be applied to enterprises for resource deployment, and applications are not merely limited to governments. © 1979-2012 IEEE.

Simultaneous wireless information and power transfer for buffer-aided cooperative relaying systems

- Nasir, Hina, Javaid, Nadeem, Imran, Muhammad, Shoaib, Muhammad, Anwar, Mehmoon

  • Authors: Nasir, Hina , Javaid, Nadeem , Imran, Muhammad , Shoaib, Muhammad , Anwar, Mehmoon
  • Date: 2018
  • Type: Text , Conference paper
  • Relation: 14th International Wireless Communications and Mobile Computing Conference, IWCMC 2018, Limassol, 25-28 June 2018 p. 845-849
  • Full Text: false
  • Reviewed:
  • Description: This paper explored cooperative relaying in the presence of energy constrained relays with data storage facility. The relays depend only on the source signal to harvest energy and forward signal to the destination. The relay is selected according to the instantaneous strength of the wireless link. The strongest link among all links on both sides i.e., source-relay and relaydestination links is selected for relay to receive or transmit data, respectively. Two protocols are used for energy harvesting and information transfer namely: 'power splitting based relaying' and 'time switching based relaying'. We evaluate the outage probability performance of the presented scheme using Monte Carlo simulations. The results show that TSR performs better than PSR protocol. © 2018 IEEE.

Smart dynamic traffic monitoring and enforcement system

- El-Hansali, Youssef, Outay, Fatma, Yasar, Ansar, Farrag, Siham, Shoaib, Muhammad, Imran, Muhammad, Awan, Hammad

  • Authors: El-Hansali, Youssef , Outay, Fatma , Yasar, Ansar , Farrag, Siham , Shoaib, Muhammad , Imran, Muhammad , Awan, Hammad
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Computers, Materials and Continua Vol. 67, no. 3 (2021), p. 2797-2806
  • Full Text:
  • Reviewed:
  • Description: Enforcement of traffic rules and regulations involves a wide range of complex tasks, many of which demand the use of modern technologies. variable speed limits (VSL) control is to change the current speed limit according to the current traffic situation based on the observed traffic conditions. The aim of this study is to provide a simulation-based methodological framework to evaluate (VSL) as an effective Intelligent Transportation System (ITS) enforcement system. The focus of the study is on measuring the effectiveness of the dynamic traffic control strategy on traffic performance and safety considering various performance indicators such as total travel time, average delay, and average number of stops. United Arab Emirates (UAE) was selected as a case study to evaluate the effectiveness of this strategy. A micro simulation software package VISSIM with add-on module VisVAP is used to evaluate the impacts of VSL. It has been observed that VSL control strategy reduced the average delay time per vehicle to around 7%, travel time by 3.2%, and number of stops by 48.5%. Dynamic traffic control strategies also alleviated congestion by increasing the capacity of the bottleneck section and improving safety. Results of this study would act as a guidance for engineers and decision makers to new traffic control system implementation. © 2021 Tech Science Press. All rights reserved.

Technology-assisted decision support system for efficient water utilization : a real-time testbed for irrigation using wireless sensor networks

- Khan, Rahim, Ali, Ihsan, Zakarya, Muhammad, Ahmad, Mushtaq, Imran, Muhammad, Shoaib, Muhammad

  • Authors: Khan, Rahim , Ali, Ihsan , Zakarya, Muhammad , Ahmad, Mushtaq , Imran, Muhammad , Shoaib, Muhammad
  • Date: 2018
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 6, no. (2018), p. 25686-25697
  • Full Text:
  • Reviewed:
  • Description: Scientific organizations and researchers are eager to apply recent technological advancements, such as sensors and actuators, in different application areas, including environmental monitoring, creation of intelligent buildings, and precision agriculture. Technology-assisted irrigation for agriculture is a major research innovation which eases the work of farmers and prevents water wastage. Wireless sensor networks (WSNs) are used as sensor nodes that directly interact with the physical environment and provide real-time data that are useful in identifying regions in need, particularly in agricultural fields. This paper presents an efficient methodology that employs WSN as a data collection tool and a decision support system (DSS). The proposed DSS can assist farmers in their manual irrigation procedures or automate irrigation activities. Water-deficient sites in both scenarios are identified by using soil moisture and environmental data sensors. However, the proposed system's accuracy is directly proportional to the accuracy of dynamic data generated by the deployed WSN. A simplified outlier-detection algorithm is thus presented and integrated with the proposed DSS to fine-tune the collected data prior to processing. The complexity of the algorithm is O(1) for dynamic datasets generated by sensor nodes and O(n) for static datasets. Different issues in technology-assisted irrigation management and their solutions are also addressed. © 2013 IEEE.

Towards a low complexity scheme for medical images in scalable video coding

- Shoaib, Muhammad, Imran, Muhammad, Subhan, Fazli, Ahmad, Iftikhar

  • Authors: Shoaib, Muhammad , Imran, Muhammad , Subhan, Fazli , Ahmad, Iftikhar
  • Date: 2020
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 8, no. (2020), p. 41439-41451
  • Full Text:
  • Reviewed:
  • Description: Medical imaging has become of vital importance for diagnosing diseases and conducting noninvasive procedures. Advances in eHealth applications are challenged by the fact that Digital Imaging and Communications in Medicine (DICOM) requires high-resolution images, thereby increasing their size and the associated computational complexity, particularly when these images are communicated over IP and wireless networks. Therefore, medical research requires an efficient coding technique to achieve high-quality and low-complexity images with error-resilient features. In this study, we propose an improved coding scheme that exploits the content features of encoded videos with low complexity combined with flexible macroblock ordering for error resilience. We identify the homogeneous region in which the search for optimal macroblock modes is early terminated. For non-homogeneous regions, the integration of smaller blocks is employed only if the vector difference is less than the threshold. Results confirm that the proposed technique achieves a considerable performance improvement compared with existing schemes in terms of reducing the computational complexity without compromising the bit-rate and peak signal-to-noise ratio. © 2013 IEEE.

UAV-enabled data acquisition scheme with directional wireless energy transfer for Internet of Things

- Liu, Yalin, Dai, Hong-Ning, Wang, Hao, Imran, Muhammad, Wang, Xiaofen, Shoaib, Muhammad

  • Authors: Liu, Yalin , Dai, Hong-Ning , Wang, Hao , Imran, Muhammad , Wang, Xiaofen , Shoaib, Muhammad
  • Date: 2020
  • Type: Text , Journal article
  • Relation: Computer Communications Vol. 155, no. (2020), p. 184-196
  • Full Text: false
  • Reviewed:
  • Description: Low power Internet of Things (IoT) is suffering from two limitations: battery-power limitation of IoT nodes and inflexibility of infrastructure-node deployment. In this paper, we propose an Unmanned Aerial Vehicle (UAV)-enabled data acquisition scheme with directional wireless energy transfer (WET) to overcome the limitations of low power IoT. The main idea of the proposed scheme is to employ a UAV to serve as both a data collector and an energy supplier. The UAV first transfers directional wireless energy to an IoT node which then sends back the data packets to the UAV by using the harvested energy. Meanwhile, we minimize the overall energy consumption under conditions of balanced energy supply and limited overall time. Moreover, we derive the optimal values of WET time and data transmission power. After analysing the feasibility of the optimal WET time and data transmission, we design an allocation scheme based on the feasible ranges of data size level and channel-fading degree. The numerical results show the feasibility and adaptability of our allocation scheme against the varied values of multiple system parameters. We further extend our scheme to the multi-node scenario by re-designing energy beamforming and adopting multi-access mechanisms. Moreover, we also analyse the mobility of UAVs in the proposed scheme. © 2020 Elsevier B.V.