A QoE Model for Mulsemedia TV in a Smart Home Environment

The provision to the users of realistic media contents is one of the main goals of future media services. The sense of reality perceived by the user can be enhanced by adding various sensorial effects to the conventional audio-visual content, through the stimulation of the five senses stimulation (sight, hearing, touch, smell and taste), the so-called multi-sensorial media (mulsemedia). To deliver the additional effects within a smart home (SH) environment, custom devices (e.g., air conditioning, lights) providing opportune smart features, are preferred to ad-hoc devices, often deployed in a specific context such as for example in gaming consoles. In the present study, a prototype for a mulsemedia TV application, implemented in a real smart home scenario, allowed the authors to assess the user's Quality of Experience (QoE) through test measurement campaign. The impact of specific sensory effects (i.e., light, airflow, vibration) on the user experience regarding the enhancement of sense of reality, annoyance, and intensity of the effects was investigated through subjective assessment. The need for multi sensorial QoE models is an important challenge for future research in this field, considering the time and cost of subjective quality assessments. Therefore, based on the subjective assessment results, this paper instantiates and validates a parametric QoE model for multi-sensorial TV in a SH scenario which indicates the relationship between the quality of audiovisual contents and user-perceived QoE for sensory effects applications

Integration of multi-sensorial effects in synchronised immersive hybrid TV scenarios

[EN] Traditionally, TV media content has exclusively involved 2D or 3D audiovisual streams consumed by using a simple TV device. However, in order to generate more immersive media consumption experiences, other new types of content (e.g., omnidirectional video), consumption devices (e.g., Head Mounted Displays or HMD) and solutions to stimulate other senses beyond the traditional ones of sight and hearing, can be used. Multi-sensorial media content (a.k.a. mulsemedia) facilitates additional sensory effects that stimulate other senses during the media consumption, with the aim of providing the consumers with a more immersive and realistic experience. They provide the users with a greater degree of realism and immersion, but can also provide greater social integration (e.g., people with AV deficiencies or attention span problems) and even contribute to creating better educational programs (e.g., for learning through the senses in educational content or scientific divulgation). Examples of sensory effects that can be used are olfactory effects (scents), tactile effects (e.g., vibration, wind or pressure effects), and ambient effects (e.g., temperature or lighting). In this paper, a solution for providing multi-sensorial and immersive hybrid (broadcast/broadband) TV content consumption experiences, including omnidirectional video and sensory effects, is presented. It has been designed, implemented, and subjectively evaluated (by 32 participants) in an end-to-end platform for hybrid content generation, delivery and synchronised consumption. The satisfactory results which were obtained regarding the perception of fine synchronisation between sensory effects and multimedia content, and regarding the users' perceived QoE, are summarised and discussed.This work was supported in part by the "Vicerrectorado de Investigacion de la Universitat Politecnica de Valencia'' under Project PAID-11-21 and Project PAID-12-21.Marfil, D.; Boronat, F.; González-Salinas, J.; Sapena Piera, A. (2022). Integration of multi-sensorial effects in synchronised immersive hybrid TV scenarios. IEEE Access. 10:79071-79089. https://doi.org/10.1109/ACCESS.2022.319417079071790891

Integration of Multisensorial Stimuli and Multimodal Interaction in a Hybrid 3DTV System

This article proposes the integration of multisensorial stimuli and multimodal interaction components into a sports multimedia asset under two dimensions: immersion and interaction. The first dimension comprises a binaural audio system and a set of sensory effects synchronized with the audiovisual content, whereas the second explores interaction through the insertion of interactive 3D objects into the main screen and on-demand presentation of additional information in a second touchscreen. We present an end-to-end solution integrating these components into a hybrid (internet-broadcast) television system using current 3DTV standards. Results from an experimental study analyzing the perceived quality of these stimuli and their influence on the Quality of Experience are presented

Estimation of the QoE for video streaming services based on facial expressions and gaze direction

As the multimedia technologies evolve, the need to control their quality becomes even more important making the Quality of Experience (QoE) measurements a key priority. Machine Learning (ML) can support this task providing models to analyse the information extracted by the multimedia. It is possible to divide the ML models applications in the following categories: 1) QoE modelling: ML is used to define QoE models which provide an output (e.g., perceived QoE score) for any given input (e.g., QoE influence factor). 2) QoE monitoring in case of encrypted traffic: ML is used to analyze passive traffic monitored data to obtain insight into degradations perceived by end-users. 3) Big data analytics: ML is used for the extraction of meaningful and useful information from the collected data, which can further be converted to actionable knowledge and utilized in managing QoE. The QoE estimation quality task can be carried out by using two approaches: the objective approach and subjective one. As the two names highlight, they are referred to the pieces of information that the model analyses. The objective approach analyses the objective features extracted by the network connection and by the used media. As objective parameters, the state-of-the-art shows different approaches that use also the features extracted by human behaviour. The subjective approach instead, comes as a result of the rating approach, where the participants were asked to rate the perceived quality using different scales. This approach had the problem of being a time-consuming approach and for this reason not all the users agree to compile the questionnaire. Thus the direct evolution of this approach is the ML model adoption. A model can substitute the questionnaire and evaluate the QoE, depending on the data that analyses. By modelling the human response to the perceived quality on multimedia, QoE researchers found that the parameters extracted from the users could be different, like Electroencephalogram (EEG), Electrocardiogram (ECG), waves of the brain. The main problem with these techniques is the hardware. In fact, the user must wear electrodes in case of ECG and EEG, and also if the obtained results from these methods are relevant, their usage in a real context could be not feasible. For this reason, my studies have been focused on the developing of a Machine Learning framework completely unobtrusively based on the Facial reactions

New cross-domain QoE guarantee method based on isomorphism flow

This paper investigates the issue of Quality of Experience(QoE)for multimedia services over heterogeneous networks. Anew concept of “Isomor-phism Flow”(iFlow) was introduced for analyzing multimedia traffics, which is inspired by the abstract algebrabased on experimental research. By using iF-low, the multimedia traffics with similar QoErequirements for differentusersare aggregated. AQoE evaluation method was also proposed for the aggregated traffics. Then a new cross-domain QoE guarantee method based on the iFlow QoEis proposed in this paper to adjust the network resource fromthe perspec-tive of user perception.The proposed scheme is validated through simulations. Simulationresults show that the proposed scheme achieves an enhancement in QoE performanceandoutperforms the existing schemes

Analisa Pengukuran Parameter Quality of Service dan Quality of Experience pada Layanan HbbTV

Hybrid Broadcast Broadband TV (HbbTV) is delivery standard for signaling, transmission, presentation of enhanced interactive television services and related applications, designed for use over broadcast networks and Internet. It is only standard that allows direct connection between linear and online content. It works on hybrid devices that include both broadcast and Internet connections. This standard will bring new dimension to services delivered through television programs (TV and Internet) and enhance consumer user experience by enabling innovative and interactive services over broadcast and broadband networks. improve. The HbbTV specification was developed by the HbbTV Association to effectively manage the rapidly increasing amount of content for today's consumers. HbbTV is a technology that combines traditional television broadcasts with Internet services and interactive applications. This research focuses on role of QoS and QoE in HbbTV implementations and measurement of parameters using Wireshark software that affect quality of service and user experience. The research method is experiment measuring QoS and QoE parameters. The QoS measurements were average throughput 47531,8bps, packet loss 4,9968%, delay 189.38ms, jitter 17700ms. We also conducted QoE measurement survey to collect user data to be collected. Data analysis revealed that 7.7% of consumer expectations of HbbTV users need to be improved.Hybrid Broadcast Broadband TV (HbbTV) adalah standar pengiriman untuk persinyalan, transmisi, presentasi layanan televisi interaktif yang disempurnakan serta aplikasi terkait, dirancang untuk digunakan melalui jaringan penyiaran dan Internet. Standar ini merupakan satu-satunya memungkinkan koneksi langsung antara konten linear dan online, dapat berjalan pada terminal hybrid mencakup koneksi siaran dan Internet. Standar ini memberikan dimensi baru pada layanan yang ditawarkan oleh program saluran televisi (TV dan Internet) dan meningkatkan pengalaman pengguna bagi konsumen dengan memungkinkan layanan yang inovatif dan interaktif melalui jaringan siaran dan broadband. Spesifikasi HbbTV dikembangkan oleh Asosiasi HbbTV untuk secara efektif mengelola jumlah konten yang tersedia untuk meningkatkan pesat yang ditargetkan untuk konsumen akhir saat ini. HbbTV adalah teknologi yang memadukan siaran televisi tradisional dengan layanan internet dan aplikasi interaktif. Penelitian ini membahas peran QoS dan QoE dalam implementasi HbbTV, dengan fokus pada pengukuran parameter menggunakan software wireshark mempengaruhi kualitas layanan dan pengalaman pengguna. Metode penelitian yang digunakan adalah eksperimen dengan mengukur parameter QoS dan QoE. Hasil pengukuran QoS rata-rata throughput 47531,8 bps, Packet loss 4,9968%, delay 189,38 ms dan jitter 17700 ms Selanjutnya dalam pengukuran QoE, survei dilakukan untuk mengumpulkan data dari pengguna. Hasil analisis data menunjukkan bahwa terdapat 7,7% harapan konsumen terhadap penggunaa HbbTV lebih ditingkatkan

6G—Enabling the New Smart City: A Survey

Smart cities and 6G are technological areas that have the potential to transform the way we live and work in the years to come. Until this transformation comes into place, there is the need, underlined by research and market studies, for a critical reassessment of the entire wireless communication sector for smart cities, which should include the IoT infrastructure, economic factors that could improve their adoption rate, and strategies that enable smart city operations. Therefore, from a technical point of view, a series of stringent issues, such as interoperability, data privacy, security, the digital divide, and implementation issues have to be addressed. Notably, to concentrate the scrutiny on smart cities and the forthcoming influence of 6G, the groundwork laid by the current 5G, with its multifaceted role and inherent limitations within the domain of smart cities, is embraced as a foundational standpoint. This examination culminates in a panoramic exposition, extending beyond the mere delineation of the 6G standard toward the unveiling of the extensive gamut of potential applications that this emergent standard promises to introduce to the smart cities arena. This paper provides an update on the SC ecosystem around the novel paradigm of 6G, aggregating a series of enabling technologies accompanied by the descriptions of their roles and specific employment schemes

MediaSync: Handbook on Multimedia Synchronization

This book provides an approachable overview of the most recent advances in the fascinating field of media synchronization (mediasync), gathering contributions from the most representative and influential experts. Understanding the challenges of this field in the current multi-sensory, multi-device, and multi-protocol world is not an easy task. The book revisits the foundations of mediasync, including theoretical frameworks and models, highlights ongoing research efforts, like hybrid broadband broadcast (HBB) delivery and users' perception modeling (i.e., Quality of Experience or QoE), and paves the way for the future (e.g., towards the deployment of multi-sensory and ultra-realistic experiences). Although many advances around mediasync have been devised and deployed, this area of research is getting renewed attention to overcome remaining challenges in the next-generation (heterogeneous and ubiquitous) media ecosystem. Given the significant advances in this research area, its current relevance and the multiple disciplines it involves, the availability of a reference book on mediasync becomes necessary. This book fills the gap in this context. In particular, it addresses key aspects and reviews the most relevant contributions within the mediasync research space, from different perspectives. Mediasync: Handbook on Multimedia Synchronization is the perfect companion for scholars and practitioners that want to acquire strong knowledge about this research area, and also approach the challenges behind ensuring the best mediated experiences, by providing the adequate synchronization between the media elements that constitute these experiences

A selective approach for energy-aware video content adaptation decision-taking engine in android based smartphone

Rapid advancement of technology and their increasing affordability have transformed mobile devices from a means of communication to tools for socialization, entertainment, work and learning. However, advancement of battery technology and capacity is slow compared to energy need. Viewing content with high quality of experience will consume high power. In limited available energy, normal content adaptation system will decrease the content quality, hence reducing quality of experience. However, there is a need for optimizing content quality of experience (QoE) in a limited available energy. With modification and improvement, content adaptation may solve this issue. The key objective of this research is to propose a framework for energy-aware video content adaptation system to enable video delivery over the Internet. To optimise the QoE while viewing streaming video on a limited available smartphone energy, an algorithm for energy-aware video content adaptation decision-taking engine named EnVADE is proposed. The EnVADE algorithm uses selective mechanism. Selective mechanism means the video segmented into scenes and adaptation process is done based on the selected scenes. Thus, QoE can be improved. To evaluate EnVADE algorithm in term of energy efficiency, an experimental evaluation has been done. Subjective evaluation by selected respondents are also has been made using Absolute Category Rating method as recommended by ITU to evaluate EnVADE algorithm in term of QoE. In both evaluation, comparison with other methods has been made. The results show that the proposed solution is able to increase the viewing time of about 14% compared to MPEG-DASH which is an official international standard and widely used streaming method. In term of QoE subjective test, EnVADE algorithm score surpasses the score of other video streaming method. Therefore, EnVADE framework and algorithm has proven its capability as an alternative technique to stream video content with higher QoE and lower energy consumption