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Dr., Yusuf Perwej, and Akhtar Nikhat. "An Empirical Study on the Current State of Internet of Multimedia Things (IoMT)." International Journal of Engineering Research in Computer Science and Engineering (IJERCSE), ISSN (Online) 2394-2320 Volume 8, Issue 3 (2021): Pages 25–42. https://doi.org/10.1617/vol8/iss3/pid85026.
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As the Internet continues to expand, immense people around the globe join the Internet. The Internet of Things (IoT) can be defined as the interconnection of peerless identifiable embedded computing devices within the current Internet infrastructure. This paradigm encompasses an infrastructure of software, hardware, and services that link tangible objects called things to the Internet. In Internet of Things technology, multimedia big data which is said to be the huge amount of data from multimedia devices will be generated with the swiftly rise of the multimedia gadgets and devices. The multimedia devices need higher processing and memory resources to process the obtained multimedia information. The Internet of Things systems are fiasco in realizing the multimedia devices connectivity unless they are able in processing multimedia gadgets and devices at a moment. In this paper, we are introduces a new concept of Internet of Multimedia Things (IoMT) for multimedia communications in Internet of Things (IoT). Internet of Multimedia Things (IoMT) communications play a vital role in Internet of Things (IoT) applications such as traffic control and handling, environmental monitoring, healthcare sector, observation & surveillance, event recognition and house monitoring and automation. In this paper, we present a comprehensive survey of IoMT and future research directions. The Internet of Multimedia Things (IoMT) applications such as real-time multimedia based security and monitoring in smart house, Smart Agriculture, multispecialty hospitals, metropolitan area, and smart transportation handling systems are of the most difficult systems to deploy.
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Zikria, Yousaf Bin, Muhammad Khalil Afzal, and Sung Won Kim. "Internet of Multimedia Things (IoMT): Opportunities, Challenges and Solutions." Sensors 20, no. 8 (2020): 2334. http://dx.doi.org/10.3390/s20082334.
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With the immersive growth of the Internet of Things (IoT) and real-time adaptability, quality of life for people is improving. IoT applications are diverse in nature and one crucial aspect of it is multimedia sensors and devices. These IoT multimedia devices form the Internet of Multimedia Things (IoMT). It generates a massive volume of data with different characteristics and requirements than the IoT. The real-time deployment scenarios vary from smart traffic monitoring to smart hospitals. Hence, Timely delivery of IoMT data and decision making is critical as it directly involves the safety of human beings. In this paper, we present a brief overview of IoMT and future research directions. Afterward, we provide an overview of the accepted articles in our special issue on the IoMT: Opportunities, Challenges, and Solutions.
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Yu, Jinao, Hanyu Xue, Bo Liu, Yu Wang, Shibing Zhu, and Ming Ding. "GAN-Based Differential Private Image Privacy Protection Framework for the Internet of Multimedia Things." Sensors 21, no. 1 (2020): 58. http://dx.doi.org/10.3390/s21010058.
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With the development of the Internet of Multimedia Things (IoMT), an increasing amount of image data is collected by various multimedia devices, such as smartphones, cameras, and drones. This massive number of images are widely used in each field of IoMT, which presents substantial challenges for privacy preservation. In this paper, we propose a new image privacy protection framework in an effort to protect the sensitive personal information contained in images collected by IoMT devices. We aim to use deep neural network techniques to identify the privacy-sensitive content in images, and then protect it with the synthetic content generated by generative adversarial networks (GANs) with differential privacy (DP). Our experiment results show that the proposed framework can effectively protect users’ privacy while maintaining image utility.
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Balan, Titus, Dan Robu, and Florin Sandu. "Multihoming for Mobile Internet of Multimedia Things." Mobile Information Systems 2017 (2017): 1–16. http://dx.doi.org/10.1155/2017/6965028.
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Mobility, redundancy, and bandwidth requirements are transforming the communication models used for IoT, mainly in case of Critical Communications and multimedia streaming (“IoMT, Internet of Multimedia Things”), as wireless video traffic is expected to be 60–75% of the global mobile traffic by 2020. One of the characteristics of 5G networks will be the proliferation of different/heterogeneous radio networks (virtualized radio access networks, RAN, new energy-efficient radios, femtocells, and offloading capabilities) and the possibility for IoT objects to connect and load-balance between dual and multiple RANs. This paper focuses on the possibility of using LISP (Locator Identifier Separation Protocol) for multihoming and load-balancing purposes and presents an illustrative scenario for the case of mobile IoT (e.g., the “things” part of vehicular or public transportation systems, PTS) that are also intensive bandwidth consumers, like the case of connected multimedia “things.” We have implemented and tested a demonstrator of a mobile LISP IoT gateway that is also integrated with Cloud-based video analytics.
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Liu, Meiping, Cheng Yang, Hao Li, and Yana Zhang. "An Efficient Attribute-Based Access Control (ABAC) Policy Retrieval Method Based on Attribute and Value Levels in Multimedia Networks." Sensors 20, no. 6 (2020): 1741. http://dx.doi.org/10.3390/s20061741.
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Internet of Multimedia Things (IoMT) brings convenient and intelligent services while also bringing huge challenges to multimedia data security and privacy. Access control is used to protect the confidentiality and integrity of restricted resources. Attribute-Based Access Control (ABAC) implements fine-grained control of resources in an open heterogeneous IoMT environment. However, due to numerous users and policies in ABAC, access control policy evaluation is inefficient, which affects the quality of multimedia application services in the Internet of Things (IoT). This paper proposed an efficient policy retrieval method to improve the performance of access control policy evaluation in multimedia networks. First, retrieve policies that satisfy the request at the attribute level by computing based on the binary identifier. Then, at the attribute value level, the depth index was introduced to reconstruct the policy decision tree, thereby improving policy retrieval efficiency. This study carried out simulation experiments in terms of the different number of policies and different policy complexity situation. The results showed that the proposed method was three to five times more efficient in access control policy evaluation and had stronger scalability.
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Tanseer, Iffrah, Nadia Kanwal, Mamoona Naveed Asghar, Ayesha Iqbal, Faryal Tanseer, and Martin Fleury. "Real-Time, Content-Based Communication Load Reduction in the Internet of Multimedia Things." Applied Sciences 10, no. 3 (2020): 1152. http://dx.doi.org/10.3390/app10031152.
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There is an increasing number of devices available for the Internet of Multimedia Things (IoMT). The demands these ever-more complex devices make are also increasing in terms of energy efficiency, reliability, quality-of-service guarantees, higher data transfer rates, and general security. The IoMT itself faces challenges when processing and storing massive amounts of data, transmitting it over low bandwidths, bringing constrained resources to bear and keeping power consumption under check. This paper’s research focuses on an efficient video compression technique to reduce that communication load, potentially generated by diverse camera sensors, and also improve bit-rates, while ensuring accuracy of representation and completeness of video data. The proposed method applies a video content-based solution, which, depending on the motion present between consecutive frames, decides on whether to send only motion information or no frame information at all. The method is efficient in terms of limiting the data transmitted, potentially conserving device energy, and reducing latencies by means of negotiable processing overheads. Data are also encrypted in the interests of confidentiality. Video quality measurements, along with a good number of Quality-of-Service measurements demonstrated the value of the load reduction, as is also apparent from a comparison with other related methods.
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Soudani, Adel, Manal Alsabhan, and Manan Almusallam. "A Study on Energy Efficiency of a Distributed Processing Scheme for Image-Based Target Recognition for Internet of Multimedia Things." Computers 12, no. 5 (2023): 99. http://dx.doi.org/10.3390/computers12050099.
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A growing number of services and applications are developed using multimedia sensing low-cost wireless devices, thus creating the Internet of Multimedia Things (IoMT). Nevertheless, energy efficiency and resource availability are two of the most challenging issues to overcome when developing image-based sensing applications. In depth, image-based sensing and transmission in IoMT significantly drain the sensor energy and overwhelm the network with redundant data. Event-based sensing schemes can be used to provide efficient data transmission and an extended network lifetime. This paper proposes a novel approach for distributed event-based sensing achieved by a cluster of processing nodes. The proposed scheme aims to balance the processing load across the nodes in the cluster. This study demonstrates the adequacy of distributed processing to extend the lifetime of the IoMT platform and compares the efficiency of Haar wavelet decomposition and general Fourier descriptors (GFDs) as a feature extraction module in a distributed features-based target recognition system. The results show that the distributed processing of the scheme based on the Haar wavelet transform of the image outperforms the scheme based on a general Fourier shape descriptor in recognition accuracy of the target as well as the energy consumption. In contrast to a GFD-based scheme, the recognition accuracy of a Haar-based scheme was increased by 26%, and the number of sensing cycles was increased from 40 to 70 cycles, which attests to the adequacy of the proposed distributed Haar-based processing scheme for deployment in IoMT devices.
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Rani, Shalli, Syed Hassan Ahmed, Rajneesh Talwar, Jyoteesh Malhotra, and Houbing Song. "IoMT: A Reliable Cross Layer Protocol for Internet of Multimedia Things." IEEE Internet of Things Journal 4, no. 3 (2017): 832–39. http://dx.doi.org/10.1109/jiot.2017.2671460.
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Silvestre-Blanes, Javier, Víctor Sempere-Payá, and Teresa Albero-Albero. "Smart Sensor Architectures for Multimedia Sensing in IoMT." Sensors 20, no. 5 (2020): 1400. http://dx.doi.org/10.3390/s20051400.
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Today, a wide range of developments and paradigms require the use of embedded systems characterized by restrictions on their computing capacity, consumption, cost, and network connection. The evolution of the Internet of Things (IoT) towards Industrial IoT (IIoT) or the Internet of Multimedia Things (IoMT), its impact within the 4.0 industry, the evolution of cloud computing towards edge or fog computing, also called near-sensor computing, or the increase in the use of embedded vision, are current examples of this trend. One of the most common methods of reducing energy consumption is the use of processor frequency scaling, based on a particular policy. The algorithms to define this policy are intended to obtain good responses to the workloads that occur in smarthphones. There has been no study that allows a correct definition of these algorithms for workloads such as those expected in the above scenarios. This paper presents a method to determine the operating parameters of the dynamic governor algorithm called Interactive, which offers significant improvements in power consumption, without reducing the performance of the application. These improvements depend on the load that the system has to support, so the results are evaluated against three different loads, from higher to lower, showing improvements ranging from 62% to 26%.
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Shashidhar, P. K., Thanuja T. C. Dr., and Kunabeva Rajashekar. "Modified IOT-RTP Routing Protocol For Transmission Of Multi-Modal Biomedical Data." Webology Volume 18,, No. 6 (2022): 4500–4512. https://doi.org/10.5281/zenodo.6643328.
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With multimodal biomedical signals constituting complex multimedia messages to be transmitted from WBAN over WSN with IoT in e-health monitoring applications there is need for novel routing protocols. Transmission of medical signals and images over Internet of Multimedia Things (IoMT) predominantly face the challenges in ensuring quality sensory data. In this paper energy-efficient routing mechanism based on modified IoT versions of Real time Transport Protocol (RTP) and Real Time Control Protocol (RTCP). The proposed protocol achieves improvement in energy efficiency of 3.02%, reduction in end-end delay of 4ms and Packet loss of 19% respectively.
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Luo, Wanli, and Lei Zhang. "Question Text Classification Method of Tourism Based on Deep Learning Model." Wireless Communications and Mobile Computing 2022 (January 5, 2022): 1–9. http://dx.doi.org/10.1155/2022/4330701.
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The Internet of Things applications are diverse in nature, and a key aspect of it is multimedia sensors and devices. These IoT multimedia devices form the Internet of Multimedia Things (IoMT). Compared with the Internet of Things, it generates a large amount of text data with different characteristics and requirements. Aiming at the problems that machine learning and single structure deep learning model cannot effectively grasp the text emotional information in text processing, resulting in poor classification effect, this paper proposes a text classification method of tourism questions based on deep learning model. First, the corpus is trained with word2vec tool based on continuous word bag model to obtain the text word vector representation. Then, the attention mechanism is introduced into the long-short term network (LSTM), and the attention-based LSTM model is constructed for text feature extraction, which highlights the impact of different words in the input text on the text emotion category. Finally, the text features are input into the Softmax classifier to obtain the probability distribution of text categories, and the model is trained combined with the cross entropy loss function. The experimental results show that the average accuracy, recall, and F value are 0.943, 0.867, and 0.903, respectively, which has better classification effect than other methods.
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Aslam, Asra, and Edward Curry. "Investigating response time and accuracy in online classifier learning for multimedia publish-subscribe systems." Multimedia Tools and Applications 80, no. 9 (2021): 13021–57. http://dx.doi.org/10.1007/s11042-020-10277-x.
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AbstractThe enormous growth of multimedia content in the field of the Internet of Things (IoT) leads to the challenge of processing multimedia streams in real-time. Event-based systems are constructed to process event streams. They cannot natively consume multimedia event types produced by the Internet of Multimedia Things (IoMT) generated data to answer multimedia-based user subscriptions. Machine learning-based techniques have enabled rapid progress in solving real-world problems and need to be optimised for the low response time of the multimedia event processing paradigm. In this paper, we describe a classifier construction approach for the training of online classifiers, that can handle dynamic subscriptions with low response time and provide reasonable accuracy for the multimedia event processing. We find that the current object detection methods can be configured dynamically for the construction of classifiers in real-time, by tuning hyperparameters even when training from scratch. Our experiments demonstrate that deep neural network-based object detection models, with hyperparameter tuning, can improve the performance within less training time for the answering of previously unknown user subscriptions. The results from this study show that the proposed online classifier training based model can achieve accuracy of 79.00% with 15-min of training and 84.28% with 1-hour training from scratch on a single GPU for the processing of multimedia events.
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Wu, Shaohua, Tiantian Zhang, Jian Jiao, Jingran Yang, and Qinyu Zhang. "Statistical Prior Aided Separate Compressed Image Sensing for Green Internet of Multimedia Things." Mobile Information Systems 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/2314062.
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In this paper, we aim to propose an image compression and reconstruction strategy under the compressed sensing (CS) framework to enable the green computation and communication for the Internet of Multimedia Things (IoMT). The core idea is to explore the statistics of image representations in the wavelet domain to aid the reconstruction method design. Specifically, the energy distribution of natural images in the wavelet domain is well characterized by an exponential decay model and then used in the two-step separate image reconstruction method, by which the row-wise (or column-wise) intermediates and column-wise (or row-wise) final results are reconstructed sequentially. Both the intermediates and the final results are constrained to conform with the statistical prior by using a weight matrix. Two recovery strategies with different levels of complexity, namely, the direct recovery with fixed weight matrix (DR-FM) and the iterative recovery with refined weight matrix (IR-RM), are designed to obtain different quality of recovery. Extensive simulations show that both DR-FM and IR-RM can achieve much better image reconstruction quality with much faster recovery speed than traditional methods.
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Lalithambigai, B., and S. Chitra. "Segment Based Compressive Sensing (SBCS) of Color Images for Internet of Multimedia Things Applications." Journal of Medical Imaging and Health Informatics 12, no. 1 (2022): 1–6. http://dx.doi.org/10.1166/jmihi.2022.3848.
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Telemedicine is one of the IoMT applications transmitting medical images from hospital to remote medical centers for diagnosis and treatment. To share this multimedia content across internet, storage and transmission become a challenge because of its huge volume. New compression techniques are being continuously introduced to circumvent this issue. Compressive sensing (CS) is a new paradigm in signal compression. Block based compressive sensing (BCS) is a standard and commonly used technique in color image compression. However, BCS suffers from block artifacts and during transmission, mistakes can be introduced to affect the BCS coefficients, degrading the reconstructed image’s quality. The performance of BCS at low compression ratios is also poor. To overcome these limitations, without dividing the image into blocks, the image matrix is considered as a whole and compressively sensed by segment based compressive sensing (SBCS). This is a novel strategy that is offered in this article, for efficient compression of digital color images at low compression ratios. Metrics of performance The peak signal to noise ratio (PSNR), the mean structural similarity index (MSSIM), and the colour perception metric delta E are computed and compared to those obtained using block-based compressive sensing (BBCS). The results show that SBCS performs better than BBCS.
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Takabayashi, Kento, Hirokazu Tanaka, and Katsumi Sakakibara. "Toward an Advanced Human Monitoring System Based on a Smart Body Area Network for Industry Use." Electronics 10, no. 6 (2021): 688. http://dx.doi.org/10.3390/electronics10060688.
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This research provides a study on a smart body area network (SmartBAN) physical layer (PHY), as an of the Internet of medical things (IoMT) technology, for an advanced human monitoring system in industrial use. The SmartBAN provides a new PHY and a medium access control (MAC) layer, improving its performance and providing very low-latency emergency information transmission with low energy consumption compared with other wireless body area network (WBAN) standards. On the other hand, IoMT applications are expected to become more advanced with smarter wearable devices, such as augmented reality-based human monitoring and work support in a factory. Therefore, it is possible to develop more advanced human monitoring systems for industrial use by combining the SmartBAN with multimedia devices. However, the SmartBAN PHY is not designed to transmit multimedia information such as audio and video. To address this issue, multilevel phase shift keying (PSK) modulation is applied to the SmartBAN PHY, and the symbol rate is improved by setting the roll-off rate appropriately to realize the system. The numerical results show that a sufficient link budget, receiver sensitivity and fade margin were obtained even when those approaches were applied to the SmartBAN PHY. The results indicate that these techniques are required for high-quality audio or video transmission, as well as vital sign data transmission, in a SmartBAN.
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Sherly, P. Steffy, and P. Velvizhy. "IoT-enabled image captioning with deep learning for healthcare domain." Journal of Autonomous Intelligence 7, no. 5 (2024): 1542. http://dx.doi.org/10.32629/jai.v7i5.1542.
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<p>The ever-increasing volume of medical images greatly strains clinicians who are in the process of reviewing it and writing reports. It would be more efficient and cost-effective if an image captioning model could automatically create report drafts from matching photos, thereby relieving physicians from this tedious work. The Internet of things (IoT) has switched its emphasis from its initial binary concept to that of the Internet of multimedia things (IoMT) because of the explosive rise of multilingual-on-demand data in various sound, footage, picture forms. This work proposed a deep learning-based image caption network (DL-ICN) for healthcare domain. The work originality is shown using DL to identify various class labels of the patient X-ray and ECG images. With the help of bilateral encoder representations from transformers (BERT) method for captioning pictures, a detailed written summary of a person’s medical picture may be generated automatically. Results of simulations showed that the proposed model achieved good compression performance, good quality reconstruction and good classification results for image captioning.</p>
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Nikhat Akhtar and Yusuf Perwej. "The internet of nano things (IoNT) existing state and future Prospects." GSC Advanced Research and Reviews 5, no. 2 (2020): 131–50. http://dx.doi.org/10.30574/gscarr.2020.5.2.0110.
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The increase of intelligent environments suggests the interconnectivity of applications and the use of the Internet. For this reason, arise what is known as the Internet of Things (IoT). The expansion of the IoT concept gives access to the Internet of Nano Things (IoNT). A new communication networks paradigm based on nano technology and IoT, in other words, a paradigm with the capacity to interconnect nano-scale devices through existing networks. From the interconnection of these nano machines with the Internet emerged the concept of Internet of Nano Things (IoNT). The Internet of Nano-Things (IoNT) is a system of nano connected devices, objects, or organisms that have unique identifiers to transfer data over a computer or cellular network wirelessly to the Cloud. The data delivery, caching, and energy consumption are among the most significant topics in the IoNT nowadays. The nano-networks paradigm can empower the consumers to make a difference to their well-being by connecting data to personalized analysis within timely insights. The real-time data can be used in a diversification of nano-applications in the Internet of Nano-Things (IoNT), from preventive treatment to diagnostics and rehabilitation. In this paper intelligibly explains the Internet of Nano Things (IoNT), its architecture, challenges, explains the role of IoNT in global market, IoNT applications in various domains. Internet of things has provided countless new opportunity to create a powerful industrialized structure and many more. The key applications for IoNT communication including healthcare, transportation and logistics, defense and aerospace, media and entertainment, manufacturing, oil and gas, high speed data transfer & cellular, multimedia, immune system support and others services. In the end, since security is considered to be one of the main issues of the IoNT system, we provide an in-depth discussion on security, communication network and Internet of Nano Things (IoNT) market trends.
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Nikhat, Akhtar, and Perwej Yusuf. "The internet of nano things (IoNT) existing state and future Prospects." GSC Advanced Research and Reviews 5, no. 2 (2020): 131–50. https://doi.org/10.5281/zenodo.4319652.
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The increase of intelligent environments suggests the interconnectivity of applications and the use of the Internet. For this reason, arise what is known as the Internet of Things (IoT). The expansion of the IoT concept gives access to the Internet of Nano Things (IoNT). A new communication networks paradigm based on nano technology and IoT, in other words, a paradigm with the capacity to interconnect nano-scale devices through existing networks. From the interconnection of these nano machines with the Internet emerged the concept of Internet of Nano Things (IoNT). The Internet of Nano-Things (IoNT) is a system of nano connected devices, objects, or organisms that have unique identifiers to transfer data over a computer or cellular network wirelessly to the Cloud. The data delivery, caching, and energy consumption are among the most significant topics in the IoNT nowadays. The nano-networks paradigm can empower the consumers to make a difference to their well-being by connecting data to personalized analysis within timely insights. The real-time data can be used in a diversification of nano-applications in the Internet of Nano-Things (IoNT), from preventive treatment to diagnostics and rehabilitation. In this paper intelligibly explains the Internet of Nano Things (IoNT), its architecture, challenges, explains the role of IoNT in global market, IoNT applications in various domains. Internet of things has provided countless new opportunity to create a powerful industrialized structure and many more. The key applications for IoNT communication including healthcare, transportation and logistics, defense and aerospace, media and entertainment, manufacturing, oil and gas, high speed data transfer & cellular, multimedia, immune system support and others services. In the end, since security is considered to be one of the main issues of the IoNT system, we provide an in-depth discussion on security, communication network and Internet of Nano Things (IoNT) market trends.
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Xu, Xiaolong, Qihe Huang, Yiwen Zhang, Shancang Li, Lianyong Qi, and Wanchun Dou. "An LSH-based Offloading Method for IoMT Services in Integrated Cloud-Edge Environment." ACM Transactions on Multimedia Computing, Communications, and Applications 16, no. 3s (2021): 1–19. http://dx.doi.org/10.1145/3408319.
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Benefiting from the massive available data provided by Internet of multimedia things (IoMT), enormous intelligent services requiring information of various types to make decisions are emerging. Generally, the IoMT devices are equipped with limited computing power, interfering with the process of computation-intensive services. Currently, to satisfy a wide range of service requirements, the novel computing paradigms, i.e., cloud computing and edge computing, can potentially be integrated for service accommodation. Nevertheless, the private information (i.e., location, service type, etc.) in the services is prone to spilling out during service offloading in the cloud-edge computing. To avoid privacy leakage while improving service utility, including the service response time and energy consumption for service executions, a <underline>L</underline>ocality-sensitive-hash (LSH)-based <underline>o</underline>ffloading <underline>m</underline>ethod, named LOM, is devised. Specifically, LSH is leveraged to encrypt the feature information for the services offloaded to the edge servers with the intention of privacy preservation. Eventually, comparative experiments are conducted to verify the effectiveness of LOM with respect to promoting service utility.
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Wang, Xiaonan, and Xingwei Wang. "Multimedia data delivery based on IoT clouds." Communications of the ACM 64, no. 8 (2021): 80–86. http://dx.doi.org/10.1145/3474089.
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Yang, Lihong, and Yu Shi. "The Cultivation of Political Identity Literacy in Ideological and Political Classroom Based on IOT and Knowledge Map." Wireless Communications and Mobile Computing 2022 (April 5, 2022): 1–6. http://dx.doi.org/10.1155/2022/9904314.
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The learning depth and training temperature of citizen research course are realized through preclass preview and exploration of life situation and strengthen emotional noncognitive learning by guiding students through preschool preview, life situation exploration, hot topic dialogue and questions, experience transfer and application, and creating practical activities. In order to achieve the purpose of critical understanding and real problem-solving, I integrated and refined the learning content, from emotion to internal political identity and realized the organic combination of in-depth learning and classroom training. Combined with the development of Multimedia Internet of Things in the classroom, a new software is developed to solve the problem of multimedia network management that connects to other central media control devices and auxiliary devices through the Internet of Things. This paper introduces the design idea and overall structure of the system and discusses the changes brought by the network structure to the multimedia network. The network architecture of multimedia classroom based on SDN and Internet of Things helps to solve the practical problems in the use of existing multimedia classroom, improve the intelligence of multimedia classroom, and better serve teachers and students.
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Zilani, Tanjila Akter, Fadi Al-Turjman, Muhammad Bilal Khan, Nan Zhao, and Xiaodong Yang. "Monitoring Movements of Ataxia Patient by Using UWB Technology." Sensors 20, no. 3 (2020): 931. http://dx.doi.org/10.3390/s20030931.
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Internet of multimedia things (IoMT) driving innovative product development in health care applications. IoMT requires delay-sensitive and higher bandwidth devices. Ultra-wideband (UWB) technology is a promising solution to improve communication between devices, tracking and monitoring of patients. In the future, this technology has the capability to expand the IoMT world with new capabilities and more devices can be integrated. At the present time, some people face different types of physiological problems because of the damage in different areas of the central nervous system. Thus, they lose their balance coordination. One of these types of coordination problems is named Ataxia, in which patients are unable to control their body movements. This kind of coordination disorder needs a proper supervision system for the caretaker. Previous Ataxia assessment methods are cumbersome and cannot handle regular monitoring and tracking of patients. One of the most challenging tasks is to detect different walking abnormalities of Ataxia patients. In our paper, we present a technique for monitoring and tracking of a patient with the help of UWB technology. This method expands the real-time location systems (RTLS) in the indoor environment by placing wearable receiving tags on the body of Ataxia patients. The location and four different walking movement data are collected by UWB transceiver for the classification and prediction in the two-dimensional path. For accurate classification, we use a support vector machine (SVM) algorithm to clarify the movement variations. Our proposed examined result successfully achieved and the accuracy is above 95%.
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Mustamin, Syaiful Bachri, Muhammad Atnang, Sahriani, Nur Hikmah, and Samsidar. "Transparansi dan Auditabilitas Data Pribadi dalam Layanan Berbasis Cloud Pada Proyek PACE: Studi Literatur." Jurnal Teknologi dan Sains Modern 1, no. 1 (2024): 1–8. https://doi.org/10.69930/jtsm.v1i1.57.
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Ulasan komprehensif ini mengeksplorasi pendekatan-pendekatan beragam dalam meningkatkan privasi dan keamanan dalam manajemen data di berbagai bidang. Studi pertama menyajikan kerangka konseptual yang bertujuan untuk memperkuat privasi dan keamanan dalam manajemen data kota cerdas dengan mengintegrasikan kecerdasan buatan dan pemodelan big data. Meskipun analisis data empiris absen, kerangka konseptual tersebut memberikan wawasan penting tentang kemungkinan kemajuan. Studi kedua menelusuri proyek Privacy-Aware Cloud Ecosystems (PACE), berfokus pada teknologi blockchain untuk meningkatkan transparansi dan auditabilitas dalam pemrosesan data pribadi berbasis awan. Meskipun secara utama berorientasi pada masa depan, teknologi yang dikembangkan menjanjikan peningkatan privasi dan keamanan data dalam komputasi awan. Tinjauan literatur dalam studi ketiga mengevaluasi tren dan tantangan dalam menerapkan keamanan dan blockchain dalam Internet of Multimedia Things (IoMT), memberikan wawasan berharga meskipun tanpa temuan empiris langsung. Terakhir, sebuah studi eksperimental memperkenalkan sistem pengolahan data berbasis blockchain dan differential privacy untuk komputasi perkotaan, melaporkan kinerja sistem dan peningkatan keamanannya. Meskipun metodologi beragam, setiap studi memberikan kontribusi pada diskusi yang lebih luas tentang privasi dan keamanan data, menawarkan wawasan, kerangka kerja, dan inovasi teknologi untuk penelitian dan implementasi praktis di masa depan.
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Eliviani, Rosa, and Yoanes Bandung. "WSN-IoT Forecast: Wireless Sensor Network Throughput Prediction Framework in Multimedia Internet of Things." Journal of ICT Research and Applications 17, no. 3 (2023): 336–55. http://dx.doi.org/10.5614/itbj.ict.res.appl.2023.17.3.4.
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Accurate throughput predictions can significantly improve the quality of experience (QoE), where QoE denotes a network’s capacity to provide satisfactory service. By increasing the results of good throughput predictions, the best strategy can be planned for managing data transmission networks with the aim of better and faster data transmission, thereby increasing QoE. Consequently, this paper investigates how to predict the throughput of wireless sensor networks utilizing multimedia data. First, we conducted a comparative analysis of relevant prior research on the topic of throughput prediction in Multimedia Internet of Things (Multimedia IoT). We developed a throughput prediction framework for wireless sensor networks based on what we learned from these studies using machine learning. The Throughput Prediction Framework identifies historical throughput data and employs these traits to predict throughput. In the final phase, multiple camera nodes and local servers are utilized to test a framework for throughput prediction. Our analysis demonstrates that WSN-IoT predictions are quite precise. For a 1-second time breakdown, the average absolute percentage error for all investigated scenarios ranges from 1 to 8 percent.
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Zhao, Gui Xin, and Bei Qi. "Application of the IOT Technology in the Intelligent Management of University Multimedia Classrooms." Applied Mechanics and Materials 513-517 (February 2014): 2050–53. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.2050.
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The internet of things technology is applies to the management of universities multimedia classroom in an effort to reach the network, information technology and intelligent management. The radio frequency identification technology and sensor technology are used in the management of university multimedia classrooms, and explains the information stored in the teacher RFID, student RFID card and the property staff RFID card, finally make a detail analysis of the implementation of Access management multimedia device management and the control of electric and heating in the application of the IOT technology in the intelligent management of university multimedia classrooms.
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Akbar, Junaidi, Jacob Febryadi Nithanel Dethan, Rudy ., Rudy Arijanto, Benny Daniawan, and Andi Leo. "Implementasi Internet of Things (IoT) dalam Pelatihan Siswa Multimedia SMK Setia Bhakti." Jurnal Abdimas Berdaya : Jurnal Pembelajaran, Pemberdayaan dan Pengabdian Masyarakat 7, no. 1 (2024): 55. http://dx.doi.org/10.30736/jab.v7i1.608.
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Islam, Naveed, Majid Altamimi, Khalid Haseeb, and Mohammad Siraj. "Secure and Sustainable Predictive Framework for IoT-Based Multimedia Services Using Machine Learning." Sustainability 13, no. 23 (2021): 13128. http://dx.doi.org/10.3390/su132313128.
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In modern years, the Internet of Things (IoT) has gained tremendous growth and development in various sectors because of its scalability, self-configuring, and heterogeneous factors. It performs a vital role in improving multimedia communication and reducing production costs. The multimedia data consist of various types and formats (text, audio, videos, etc.), which are forwarded in the form of blocks of bits in the network layer of TCP/IP. Due to limited resources available to IoT-built devices, most of the Multimedia Internet of Things (MIoT)-based applications are delay constraints, especially for big data content. Similarly, multimedia-based applications are more vulnerable to security burdens and lower the trust of data processing. In this paper, we present a secure and sustainable prediction framework for MIoT data transmission using machine learning, which aims to offer intelligent behavior of the system with information protection. Firstly, the network edges exploit a regression analysis for a real-time multimedia routing scheme and achieve precise delivery towards the media servers. Secondly, an efficient and low-processing asymmetric process is proposed to provide secure data transmission between the IoT devices, edges, and data servers. Extensive experiments are performed over the OMNET++ network simulator, and its significance is achieved by an average for energy consumption by 71%, throughput by 30.5%, latency by 22%, bandwidth by 34.5%, packets overheads by 38.5%, computation time by 12.5%, and packet drop ratio by 35% in the comparison of existing schemes.
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G. RAMA, SUBBA REDDY, KUMAR M. AJAY, and KUMAR N. V. KISHORE. "A TAXONOMY OF ISSUES, CHALLENGES AND APPLICATIONS IN INTERNET OF MULTIMEDIA THINGS (IoMMT)." i-manager’s Journal on Cloud Computing 6, no. 1 (2019): 1. http://dx.doi.org/10.26634/jcc.6.1.16178.
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Sathya, M., M. Jeyaselvi, Lalitha Krishnasamy, et al. "A Novel, Efficient, and Secure Anomaly Detection Technique Using DWU-ODBN for IoT-Enabled Multimedia Communication Systems." Wireless Communications and Mobile Computing 2021 (December 14, 2021): 1–12. http://dx.doi.org/10.1155/2021/4989410.
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The Internet of Things (IoT) is enhancing our lives in a variety of structures, which consists of smarter cities, agribusiness, and e-healthcare, among others. Even though the Internet of Things has many features with the consumer Internet of Things, the open nature of smart devices and their worldwide connection make IoT networks vulnerable to a variety of assaults. Several approaches focused on attack detection in Internet of Things devices, which has the longest calculation times and the lowest accuracy issues. It is proposed in this paper that an attack detection framework for Internet of Things devices, based on the DWU-ODBN method, be developed to alleviate the existing problems. At the end of the process, the proposed method is used to identify the source of the assault. It comprises steps such as preprocessing, feature extraction, feature selection, and classification to identify the source of the attack. A random oversampler is used to preprocess the input data by dealing with NaN values, categorical features, missing values, and unbalanced datasets before being used to deal with the imbalanced dataset. When the data has been preprocessed, it is then sent to the MAD Median-KS test method, which is used to extract features from the dataset. To categorize the data into attack and nonattack categories, the features are classified using the dual weight updation-based optimal deep belief network (DWU-ODBN) classification technique, which is explained in more detail below. According to the results of the experimental assessment, the proposed approach outperforms existing methods in terms of detecting intrusions and assaults. The proposed work achieves 77 seconds to achieve the attack detection with an accuracy rate of 98.1%.
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Babar, Muhammad, Mohammad Dahman Alshehri, Muhammad Usman Tariq, et al. "IoT-Enabled Big Data Analytics Architecture for Multimedia Data Communications." Wireless Communications and Mobile Computing 2021 (December 17, 2021): 1–9. http://dx.doi.org/10.1155/2021/5283309.
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The present spreading out of the Internet of Things (IoT) originated the realization of millions of IoT devices connected to the Internet. With the increase of allied devices, the gigantic multimedia big data (MMBD) vision is also gaining eminence and has been broadly acknowledged. MMBD management offers computation, exploration, storage, and control to resolve the QoS issues for multimedia data communications. However, it becomes challenging for multimedia systems to tackle the diverse multimedia-enabled IoT settings including healthcare, traffic videos, automation, society parking images, and surveillance that produce a massive amount of big multimedia data to be processed and analyzed efficiently. There are several challenges in the existing structural design of the IoT-enabled data management systems to handle MMBD including high-volume storage and processing of data, data heterogeneity due to various multimedia sources, and intelligent decision-making. In this article, an architecture is proposed to process and store MMBD efficiently in an IoT-enabled environment. The proposed architecture is a layered architecture integrated with a parallel and distributed module to accomplish big data analytics for multimedia data. A preprocessing module is also integrated with the proposed architecture to prepare the MMBD and speed up the processing mechanism. The proposed system is realized and experimentally tested using real-time multimedia big data sets from athentic sources that discloses the effectiveness of the proposed architecture.
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Triadi Antara, Komang. "Pengaruh IoT pada Transformasi Jaringan Multimedia: Literatur Review." Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) 7, no. 1 (2024): 173–81. http://dx.doi.org/10.55338/jikomsi.v7i1.2736.
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Pengaruh Internet of Things (IoT) pada Transformasi Jaringan Multimedia menjadi fokus kajian dalam literatur ini. Tinjauan literatur menyeluruh menggambarkan perubahan signifikan yang terjadi dalam paradigma jaringan multimedia seiring dengan integrasi IoT. Perkembangan ini bukan hanya mengenai kemajuan teknologi, melainkan juga melibatkan transformasi mendasar dalam arsitektur, kapabilitas, dan keamanan jaringan multimedia. Literatur memberikan penekanan pada peningkatan konektivitas antar perangkat multimedia yang dipacu oleh IoT, menciptakan lingkungan yang lebih dinamis dan responsif. Namun, tantangan terkait keamanan dan privasi data juga diperinci, menyoroti perlunya perlindungan data yang efektif dalam lingkungan yang semakin terhubung. Kajian literatur ini juga menegaskan pentingnya pemahaman mendalam terhadap konsep, perkembangan, dan tantangan yang dihadapi oleh jaringan multimedia dalam mengadopsi IoT. Dengan mempertimbangkan berbagai perspektif dari literatur, abstrak ini merangkum bahwa transformasi jaringan multimedia oleh IoT tidak hanya merupakan revolusi teknologi, tetapi juga memerlukan pendekatan holistik untuk mengoptimalkan dampak positifnya dan mengatasi tantangan yang muncul. Kesimpulannya, integrasi IoT dalam jaringan multimedia bukan hanya evolusi teknologi, melainkan transformasi yang mengubah paradigma interaksi antarperangkat dan mendefinisikan ulang landscape multimedia di era digital.
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Benaka, Santhosha S., and Kiran N. Chitra. "A Systematic Review of Existing Data Mining Approaches Envisioned for Knowledge Discovery from Multimedia." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 2 (2018): 908–16. https://doi.org/10.11591/ijece.v8i2.pp908-916.
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The extensive use of multimedia technologies extended the applicability of information technology to a large extent which results enormous generation of complex multimedia contents over the internet. Therefore the number of multimedia contents available to the user is also exponentially increasing. In this digital era of the cloud-enabled Internet of Things (IoT), analysis of complex video and image data plays a crucial role.It aims to extract meaningful information as the distributed storages and processing elements within a bandwidth constraint network seek optimal solutions to increase the throughput along with an optimal trade-off between computational complexity and power consumption. However, due to complex characteristics of visual patterns and variations in video frames, it is not a trivial task to discover meaningful information and correlation. Hence, data mining has emerged as a field which has diverse aspects presently in extracting meaningful hidden patterns from the complex image and video data considering different pattern classification approach. The study mostly investigates the existing data-mining tools and their performance metric for the purpose of reviewing this research track.It also highlights the relationship between frequent patterns and discriminativefeatures associated with a video object. Finally, the study addresses the existing research issues to strengthen up the future direction of research towards video analytics and pattern recognition.
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Chang, Victor, Gang Sun, and Jin Li. "Guest Editorial: Security and Privacy for Multimedia in the Internet of Things (IoT)." Multimedia Tools and Applications 77, no. 14 (2018): 18201–2. http://dx.doi.org/10.1007/s11042-018-5963-z.
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Maphathe, Bokang Francis, Prabhat Thakur, Ghanshyam Singh, and Hashimu E. Iddi. "The Terahertz Channel Modeling in Internet of Multimedia Design In-Body Antenna." International Journal of E-Health and Medical Communications 13, no. 4 (2022): 1–17. http://dx.doi.org/10.4018/ijehmc.309437.
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In this paper, the authors have emphasized on the perspectives of the Terahertz channel modeling in Internet of multimedia nano things (IoMNT) networks. A modulation technique targeting body-centric network is discussed. An analogy of a real Terahertz antenna is developed within a terahertz multi-layer modelling channel for a human skin tissue. As a result, the investigation of how signals at THz frequency band interact and transmit within the skin biomaterial. The human skin model used to collect data was selected to have four layers: epidermis, dermis, blood, and hypodermis, with the depth of the layers varying between normal human body values. It is revealed from the literature that the frequency and content have a substantial impact on path failure. The estimated path loss could thus differ considerably, but for a human skin model with depths of 0.21 mm, 1.23 mm, 1.38 mm, and 3.76 mm, the frequencies of 0.5-1.5 THz at the end distance resulted in a path loss estimated about 250-350 dB.
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Wang, Dongkui, and Zuolian Bai. "Piano Intelligent Teaching Evaluation with IoT and Multimedia Technology." Mobile Information Systems 2022 (July 4, 2022): 1–10. http://dx.doi.org/10.1155/2022/7636458.
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With deepening of the economic development process, the overall spiritual and cultural needs of the people have increased, and quality education has received more and more attention. Piano education is an important part of quality education. Nowadays, piano education has also been able to move forward continuously. As the king of musical instruments, the piano is widely used in music learning. Learning the piano can exercise willpower, develop intelligence, and cultivate sentiment. With development of computer software as well as hardware, Internet of Things technology and multimedia technology provide the material basis and preconditions for intelligent piano teaching. Therefore, how to evaluate the impact of the IoT and multimedia technology on intelligent teaching of piano has become a very important topic. Based on this, this work combines BP network with artificial fish swarm algorithm (AFS) and proposes network model (IAFS-BP) for evaluating the quality of piano intelligent teaching in the context of Internet of Things and multimedia. The specific contents of this work are as follows: (1) Aiming at the shortcomings of AFS, an IAFS with mutation operator, dynamic vision, and step size is proposed. (2) In view of shortcomings for BP network, IAFS is used in BP network. By using the IAFS algorithm in the training of the weights as well as thresholds, the training speed and training accuracy of the network are improved. (3) This work has carried out a comprehensive and systematic experiment to verify effectiveness and feasibility of IAFS-BP applied to quality assessment of piano intelligent teaching in the context of the IoT and multimedia.
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Dong, Pengfei. "Design and Practice of The Fire IoT Big Data Application Platform." Journal of Industry and Engineering Management 2, no. 1 (2024): 93–98. http://dx.doi.org/10.62517/jiem.202403114.
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The Fire IoT Big Data Application Platform is built in accordance with relevant national regulations and standards. Its main functions combine the characteristics of fire control supervision and maintenance, and are designed with Internet of Things technology, big data, mobile Internet and other multimedia technologies according to the current technical status of the fire alarm platform. It is mainly used to solve problems such as the integration of firefighting e-government, normalization of firefighting facility maintenance, and automation of fire fault alarm.
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Debauche, Olivier, Saïd Mahmoudi, and Adriano Guttadauria. "A New Edge Computing Architecture for IoT and Multimedia Data Management." Information 13, no. 2 (2022): 89. http://dx.doi.org/10.3390/info13020089.
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The Internet of Things and multimedia devices generate a tremendous amount of data. The transfer of this data to the cloud is a challenging problem because of the congestion at the network level, and therefore processing time could be too long when we use a pure cloud computing strategy. On the other hand, new applications requiring the processing of large amounts of data in real time have gradually emerged, such as virtual reality and augmented reality. These new applications have gradually won over users and developed a demand for near real-time interaction of their applications, which has completely called into question the way we process and store data. To address these two problems of congestion and computing time, edge architecture has emerged with the goal of processing data as close as possible to users, and to ensure privacy protection and responsiveness in real-time. With the continuous increase in computing power, amounts of memory and data storage at the level of smartphone and connected objects, it is now possible to process data as close as possible to sensors or directly on users devices. The coupling of these two types of processing as close as possible to the data and to the user opens up new perspectives in terms of services. In this paper, we present a new distributed edge architecture aiming to process and store Internet of Things and multimedia data close to the data producer, offering fast response time (closer to real time) in order to meet the demands of modern applications. To do this, the processing at the level of the producers of data collaborate with the processing ready for the users, establishing a new paradigm of short supply circuit for data transmission inspired of short supply chains in agriculture. The removing of unnecessary intermediaries between the producer and the consumer of the data improves efficiency. We named this new paradigm the Short Supply Circuit Internet of Things (SSCIoT).
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Said, Omar, Yasser Albagory, Mostafa Nofal, and Fahad Al Raddady. "IoT-RTP and IoT-RTCP: Adaptive Protocols for Multimedia Transmission over Internet of Things Environments." IEEE Access 5 (2017): 16757–73. http://dx.doi.org/10.1109/access.2017.2726902.
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Chen, Chi-Yuan, Han-Chieh Chao, Tin-Yu Wu, et al. "IoT-IMS Communication Platform for Future Internet." International Journal of Adaptive, Resilient and Autonomic Systems 2, no. 4 (2011): 74–94. http://dx.doi.org/10.4018/jaras.2011100105.
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In recent years, Internet of Things (IoT) and Cloud Computing are the hottest issues of Future Internet. However, there is a lack of common fabric for integrating IoT and Cloud. In telecommunications, the IMS (IP Multimedia Subsystem), based on the All-IP and Open Services Architecture, has been regarded as the trend for Next Generation Network (NGN). The IMS communication platform is the most suitable fabric for integrating IoT and Cloud. This paper focuses on different aspects including Cloud Service Framework, Data Sensing and Communication Technology, Collaborative Authentication and Privacy Protection Mechanism, Operation, Administration, and Maintenance (OA&M), Mobility and Energy-Saving Management, and Application Services. This paper not only provides the discussion of open challenges, but also proposes a possible solution based on the above-mentioned aspects for Future Internet.
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Saha, Avishek, Young-Woon Lee, Young-Sup Hwang, Kostas E. Psannis, and Byung-Gyu Kim. "Context-aware block-based motion estimation algorithm for multimedia internet of things (IoT) platform." Personal and Ubiquitous Computing 22, no. 1 (2017): 163–72. http://dx.doi.org/10.1007/s00779-017-1058-5.
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Xu, Ronghua, Deeraj Nagothu, and Yu Chen. "EconLedger: A Proof-of-ENF Consensus Based Lightweight Distributed Ledger for IoVT Networks." Future Internet 13, no. 10 (2021): 248. http://dx.doi.org/10.3390/fi13100248.
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The rapid advancement in artificial intelligence (AI) and wide deployment of Internet of Video Things (IoVT) enable situation awareness (SAW). The robustness and security of IoVT systems are essential for a sustainable urban environment. While blockchain technology has shown great potential in enabling trust-free and decentralized security mechanisms, directly embedding cryptocurrency oriented blockchain schemes into resource-constrained Internet of Video Things (IoVT) networks at the edge is not feasible. By leveraging Electrical Network Frequency (ENF) signals extracted from multimedia recordings as region-of-recording proofs, this paper proposes EconLedger, an ENF-based consensus mechanism that enables secure and lightweight distributed ledgers for small-scale IoVT edge networks. The proposed consensus mechanism relies on a novel Proof-of-ENF (PoENF) algorithm where a validator is qualified to generate a new block if and only if a proper ENF-containing multimedia signal proof is produced within the current round. The decentralized database (DDB) is adopted in order to guarantee efficiency and resilience of raw ENF proofs on the off-chain storage. A proof-of-concept prototype is developed and tested in a physical IoVT network environment. The experimental results validated the feasibility of the proposed EconLedger to provide a trust-free and partially decentralized security infrastructure for IoVT edge networks.
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Sgora, Aggeliki, and Periklis Chatzimisios. "Defining and Assessing Quality in IoT Environments: A Survey." IoT 3, no. 4 (2022): 493–506. http://dx.doi.org/10.3390/iot3040026.
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With the proliferation of multimedia services, Quality of Experience (QoE) has gained a lot of attention. QoE ties together the users’ needs and expectations to multimedia application and network performance. However, in various Internet of Things (IoT) applications such as healthcare, surveillance systems, traffic monitoring, etc., human feedback can be limited or infeasible. Moreover, for immersive augmented and virtual reality, as well as other mulsemedia applications, the evaluation in terms of quality cannot only focus on the sight and hearing senses. Therefore, the traditional QoE definition and approaches for evaluating multimedia services might not be suitable for the IoT paradigm, and more quality metrics are required in order to evaluate the quality in IoT. In this paper, we review existing quality definitions, quality influence factors (IFs) and assessment approaches for IoT. This paper also introduces challenges in the area of quality assessment for the IoT paradigm.
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Aslam, Asra, and Edward Curry. "A Survey on Object Detection for the Internet of Multimedia Things (IoMT) using Deep Learning and Event-based Middleware: Approaches, Challenges, and Future Directions." Image and Vision Computing 106 (February 2021): 104095. http://dx.doi.org/10.1016/j.imavis.2020.104095.
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Khakim, Lukmanul, Wildani Eko Nugroho, David Bani Adam, and Mohammad Humam. "Upaya Mengenalkan Teknologi Internet of Things (IoT) pada Siswa SMK Negeri 1 Slawi." Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming 6, no. 3 (2023): 785–91. http://dx.doi.org/10.30591/japhb.v6i3.5095.
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Internet of Things (IoT) merupakan suatu teknologi yang memungkinkan setiap peralatan elektronika dapat dikontrol dan di monitoring dari jarak jauh dengan media transmisinya yaitu internet. Teknologi ini sangat menjanjikan untuk dilakukan pengembangan dan penerapan di era teknologi yang perkembangannya sangat pesat. Oleh karena itu dalam kegiatan ini dilakukan sebuah upaya untuk mengenalkan teknologi Internet of Things (IoT) yang telah dilaksanakan di salah satu sekolah menengah kejuruan (SMK) yang berada di kabupaten Tegal, yaitu SMK Negeri 1 Slawi, kegiatan ini berbentuk sebuah seminar teknologi berbasis IoT. Target dari kegiatan ini adalah siswa-siswi dengan jurusan yang memang ada korelasinya dengan teknologi IoT, jurusan yang dimaksud adalah jurusan teknik komputer jaringan, multimedia dan rekayasa perangkat lunak. Kegiatan ini dilakukan dengan cara seminar yang dilakukan di ruang aula SMK Negeri 1 Slawi, dengan jumlah peserta sebanyak 232 siswa, di mana dari jumlah tersebut 231 siswa menyatakan kegiatan tersebut bermanfaat, dan 1 siswa menyatakan tidak bermanfaat. Hasil responden tersebut menunjukan bahwa kegiatan seminar teknologi tersebut telah berhasil dilakukan dan dapat dipahami oleh peserta seminar.
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Karaagac, Abdulkadir, Enri Dalipi, Pieter Crombez, Eli De Poorter, and Jeroen Hoebeke. "Light-weight streaming protocol for the Internet of Multimedia Things: Voice streaming over NB-IoT." Pervasive and Mobile Computing 59 (October 2019): 101044. http://dx.doi.org/10.1016/j.pmcj.2019.101044.
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Liu, Jinhua, Caiping Wang, and Xianchun Xiao. "Internet of Things (IoT) Technology for the Development of Intelligent Decision Support Education Platform." Scientific Programming 2021 (December 22, 2021): 1–12. http://dx.doi.org/10.1155/2021/6482088.
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Improving the intelligence of teaching environment and making the multimedia teaching equipment has become a major concern of the colleges and universities. To this end, the design of Internet of Things (IoT) technology based wisdom of higher education platform is of great interest. Designing the structure of online management platform for college education and realizing the functions of examination result inquiry, online teaching, and attendance management have gained more importance in the educational research. The wisdom classroom is the key structure of the wisdom education platform. A smart classroom architecture based on IoT technology is designed, which connects with traditional network facilities through the IoT gateway. Different layers of the architectures have been designed and implemented. The proposed platform tests results and shows that the intelligent education platform can effectively control classroom utilization and has high throughput, low application latency, and good practicability.
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Alzaidi, Mohammed S., Chatti Subbalakshmi, T. V. Roshini, et al. "5G-Telecommunication Allocation Network Using IoT Enabled Improved Machine Learning Technique." Wireless Communications and Mobile Computing 2022 (June 10, 2022): 1–10. http://dx.doi.org/10.1155/2022/6229356.
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Recent improvements in communication technology have undergone a significant shift over the last two decades, with state-of-the-art communication equipment, standards, and protocols simplifying the lives of consumers everywhere. For more than a decade, advancements in communication technology have mostly focused on increasing the speed with which information can be delivered and retrieved from anywhere in the globe at any time of day or night, regardless of location. Four-generation (4G) communication technologies, which have already been developed and implemented, are used to offer users with seamless access to multimedia content at transmission rates of 100 megabits per second (Mbps). It is becoming more vital to create new technologies in order to meet the growing need for faster speed as well as a variety of other advanced features. 5G networks have just recently been built as a result of extensive research and development. This has resulted in the gradual replacement of existing 4G services with new 5G networks, which are capable of transmitting multimedia content such as audio-video and high definition images, among other things, at data transmission rates in the gigabyte range or higher (up to several gigabits per second). Further recent development, in addition to the Internet of Things (IoT), which was made possible by future communication technology, is the Internet of Things-based social network. Aspects of this include the ability to connect and expanding Internet connectivity to all physical devices that consumers use to access common commercial and industrial services available on the Internet. In spite of this, with the advancement of existing high-speed communication networks, the effective interaction of devices with their inputs and responses via the Internet may be made possible through 5G Internet of Things networks. This new generation of automation and communication systems has emerged as innovative platforms for the next generation of automation and communication systems to be developed further in the future. M2M data may be utilised to more efficiently distribute resources if machine learning (ML) and optimum cell clustering are applied to the situation. It is because of this heterogeneity that the ML is able to make the best use of the remaining resources of the M2M network in order to optimise efficiency. Over the last several years, the shortage of radio frequency spectrum has proven to be the most challenging hindrance to wireless communication. This has occurred from the large number of high-frequency devices that need significant amounts of bandwidth allowance. Cognitive radio networks have been designed to meet this higher demand as a result of this increased demand.
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Adão, Telmo, Tatiana Pinho, Luís Pádua, Luís G. Magalhães, Joaquim J. Sousa, and Emanuel Peres. "Prototyping IoT-Based Virtual Environments: An Approach toward the Sustainable Remote Management of Distributed Mulsemedia Setups." Applied Sciences 11, no. 19 (2021): 8854. http://dx.doi.org/10.3390/app11198854.
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Business models built upon multimedia/multisensory setups delivering user experiences within disparate contexts—entertainment, tourism, cultural heritage, etc.—usually comprise the installation and in-situ management of both equipment and digital contents. Considering each setup as unique in its purpose, location, layout, equipment and digital contents, monitoring and control operations may add up to a hefty cost over time. Software and hardware agnosticity may be of value to lessen complexity and provide more sustainable management processes and tools. Distributed computing under the Internet of Things (IoT) paradigm may enable management processes capable of providing both remote control and monitoring of multimedia/multisensory experiences made available in different venues. A prototyping software to perform IoT multimedia/multisensory simulations is presented in this paper. It is fully based on virtual environments that enable the remote design, layout, and configuration of each experience in a transparent way, without regard of software and hardware. Furthermore, pipelines to deliver contents may be defined, managed, and updated in a context-aware environment. This software was tested in the laboratory and was proven as a sustainable approach to manage multimedia/multisensory projects. It is currently being field-tested by an international multimedia company for further validation.
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Rehman, Amjad, Tanzila Saba, Khalid Haseeb, Teg Alam, and Jaime Lloret. "Sustainability Model for the Internet of Health Things (IoHT) Using Reinforcement Learning with Mobile Edge Secured Services." Sustainability 14, no. 19 (2022): 12185. http://dx.doi.org/10.3390/su141912185.
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In wireless multimedia networks, the Internet of Things (IoT) and visual sensors are used to interpret and exchange vast data in the form of images. The digital images are subsequently delivered to cloud systems via a sink node, where they are interacted with by smart communication systems using physical devices. Visual sensors are becoming a more significant part of digital systems and can help us live in a more intelligent world. However, for IoT-based data analytics, optimizing communications overhead by balancing the usage of energy and bandwidth resources is a new research challenge. Furthermore, protecting the IoT network’s data from anonymous attackers is critical. As a result, utilizing machine learning, this study proposes a mobile edge computing model with a secured cloud (MEC-Seccloud) for a sustainable Internet of Health Things (IoHT), providing real-time quality of service (QoS) for big data analytics while maintaining the integrity of green technologies. We investigate a reinforcement learning optimization technique to enable sensor interaction by examining metaheuristic methods and optimally transferring health-related information with the interaction of mobile edges. Furthermore, two-phase encryptions are used to guarantee data concealment and to provide secured wireless connectivity with cloud networks. The proposed model has shown considerable performance for various network metrics compared with earlier studies.
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Alamri, Faten S., Khalid Haseeb, Tanzila Saba, Jaime Lloret, and Jose M. Jimenez. "Multimedia IoT-surveillance optimization model using mobile-edge authentic computing." Mathematical Biosciences and Engineering 20, no. 11 (2023): 19174–90. http://dx.doi.org/10.3934/mbe.2023847.
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<abstract> <p>Smart technologies are advancing the development of cutting-edge systems by exploring the future network. The Internet of Things (IoT) and many multimedia sensors interact with each other for collecting and transmitting visual data. However, managing enormous amounts of data from numerous network devices is one of the main research challenges. In this context, various IoT systems have been investigated and have provided efficient data retrieval and processing solutions. For multimedia systems, however, controlling inefficient bandwidth utilization and ensuring timely transmission of vital information are key research concerns. Moreover, to transfer multimedia traffic while balancing communication costs for the IoT system, a sustainable solution with intelligence in real-life applications is demanded. Furthermore, trust must be formed for technological advancement to occur; such an approach provides the smart communication paradigm with the incorporation of edge computing. This study proposed a model for optimizing multimedia using a combination of edge computing intelligence and authentic strategies. Mobile edges analyze network states to discover the system's status and minimize communication disruptions. Moreover, direct and indirect authentication determines the reliability of data forwarders and network stability. The proposed authentication approach minimizes the possibility of data compromise and increases trust in multimedia surveillance systems. Using simulation testing, the proposed model outperformed other comparable work in terms of byte delivery, packet overhead, packet delay, and data loss metrics.</p> </abstract>