Multimedia Technologies in the Internet of Things Environment, Volume 4

The convergence of Machine Learning (ML) and Multimedia Internet of Things (IoT) has opened new avenues for advanced analytics and insights generation. This paper investigates the application of machine learning techniques in the realm of Multimedia IoT analytics. By leveraging ML algorithms, this research aims to enhance the interpretation and utilization of multimedia data generated by IoT devices. The study explores various ML models, including deep learning architectures, for tasks such as image and video recognition, audio analysis, and sensor data interpretation within the context of Multimedia IoT. Additionally, the paper addresses challenges related to data heterogeneity, real-time processing, and scalability in deploying ML solutions for multimedia analytics in IoT environments. Through empirical evaluations and case studies, this work contributes to the ongoing discourse on the intersection of Machine Learning and Multimedia IoT, providing valuable insights for researchers and practitioners in the field.

In the aftermath of the COVID-19 pandemic, maintaining good hygiene, particularly hand hygiene, is crucial to preventing the disease. We present a concept for an IoT-based hand hygiene dispenser that monitors temperature and level. It addresses the need for efficient, touchless hand hygiene solutions. Ultrasonic sensors, relays, and solenoids are used in conjunction with a microcontroller to automate the sanitizer dispensing process. A temperature sensor is also incorporated, and RFID tags are used to store personal data, which can be accessed using a Wi-Fi module to track contacts. It reduces cross-contamination risks in public spaces by utilizing touchless technology. Moreover, the system integrates the protocol to enable real-time tracking and reporting, making it a valuable tool in the fight against infectious diseases, especially in densely populated areas.

Presently, the security landscape of Internet of Things (IoT) is filled with challenges, as devices such as smart cameras and sensors, despite their vast potential for big data applications, are exposed to risks due to insufficient security safeguards. Given the large volume of data these devices produce and their pervasive presence in our daily routines, there is an urgent need to enhance IoT security to effectively manage and safeguard this data, and to mitigate privacy and security issues. This paper categorizes multimedia data into four categories and highlighted ways to secure multimedia data using blockchain, cryptography, machine learning and quantum computing. Additionally, it provides recent advancements within each of the solutions and the categories of multimedia data. Finally, several research directions are discussed in order to pave way for future multimedia security and IoT researchers.

The integration of Multimedia Data Processing and Analysis within the IoT framework is a pivotal domain shaping the landscape of intelligent and context-aware systems. This chapter explores the synergy between multimedia data and IoT, focusing on the intricacies of processing and analyzing multimedia content in IoT environments. The study delves into methodologies for efficient multimedia data handling, encompassing visual, auditory, and sensor-generated information. Emphasis is placed on the challenges and opportunities associated with real-time processing, storage, and extraction of meaningful insights from multimedia data in the context of IoT applications. Through a comprehensive examination, this paper seeks to enhance our understanding of the multifaceted interactions between Multimedia Data Processing and Analysis within the dynamic and evolving IoT ecosystem.

The rapid expansion of the Internet of Things (IoT) has led to the generation of vast volumes of multimedia data across diverse sectors. This surge in data necessitates efficient processing mechanisms to extract meaningful insights in real time. This research paper examines the pivotal role played by cloud computing and embedded computing in optimizing multimedia data processing within IoT ecosystems. Cloud computing offers scalable and resource-rich environments ideal for offloading intensive multimedia processing tasks from IoT devices. By harnessing the computational power of remote servers, cloud-based solutions alleviate the burden on constrained IoT devices, enabling them to focus on essential functions while outsourcing resource-demanding computations. Simultaneously, embedded computing techniques empower IoT devices with local processing capabilities, facilitating quick decision-making and reducing reliance on external resources. Through efficient utilization of onboard processing units, embedded computing enhances system responsiveness and reduces latency, critical factors in real-time multimedia applications. This paper presents insights gleaned from empirical studies highlighting the transformative impact of cloud and embedded computing on multimedia data processing in IoT environments. By leveraging these computing paradigms, IoT systems can achieve enhanced scalability, adaptability, and efficiency, paving the way for innovative applications across domains such as smart cities, healthcare, and industrial automation. The findings underscore the importance of integrating cloud and embedded computing strategies to unlock the full potential of IoT technology in handling multimedia data effectively and sustainably.

This study examines the interplay between Internet of Things (IoT) security awareness, social cognitive factors, and social sharing behaviors. The study applies social cognitive theory (SCT) to examine the cognitive determinants of online security behavior in the context of IoT. Using a survey-based approach, data were collected from 393 social media users. Structural equation modeling was used to analyze the relationships between IoT security awareness, self-efficacy, outcome expectations, behavioral ability, and social sharing behavior. The results show that IoT security awareness does not have a significant impact on content-sharing behavior. Meanwhile, self-efficacy, outcome expectations, and behavioral ability had significant positive effects on sharing behavior. These results suggest that individuals with higher self-confidence in their security skills, a stronger belief in the positive outcomes of safe behavior, and greater practical security knowledge are more likely to share safe content on social networks. This study contributes to the theoretical understanding of online safety behavior by extending the applicability of SCT to the digital domain. This highlights the importance of self-efficacy, outcome expectations, and behavioral skills in shaping online safety behavior. This study, therefore, highlights the need for tailored educational and technological interventions to promote safe online practices. However, limitations such as the cross-sectional design and regional focus suggest opportunities for future research, including longitudinal studies and the examination of additional variables that influence digital behavior in the evolving IoT and social networking landscape.

The fusion of Internet of Things (IoT) technology with multimedia applications has significantly impacted the healthcare sector, revolutionizing patient care, telemedicine, and medical imaging. This research explores the diverse applications and transformative potential of IoT-enabled multimedia in healthcare settings. From remote patient monitoring to telemedicine consultations, the integration of multimedia data such as images, videos, and audio has facilitated real-time communication and decision-making. The study delves into the challenges, opportunities, and advancements in leveraging IoT-enabled multimedia for improved diagnostics, treatment, and overall healthcare delivery. By analyzing key use cases and technological considerations, this research aims to provide insights into the evolving landscape of healthcare applications within the IoT and multimedia convergence.

In recent years, due to the extensive need for high computation power for Internet of Things (IoT)-based application, attentiveness in the direction of quantum computing is witnessed. The world has changed significantly because of the internet and in the current period, most of the devices are connected via internet thus giving rise to IoT. However, the multimedia IoT devices are associated with notable vulnerabilities that are often exploited by adversaries. Quantum computing, with its superior processing capabilities makes securing of multimedia data over the IoT network significantly challenging. Post-Quantum Cryptography (PQC) is regarded as an emerging field responsible for designing algorithm and cryptosystems resilient to quantum attacks, ensuring robust security for the multimedia IoT infrastructures. In this paper, we highlight the principles of cryptography, its reliability for classical computing, and how its inefficiency in the quantum era with the emerging quantum computers gave rise to the need for PQC, a novel cryptosystem resilient in the rising quantum environment. It includes different vulnerabilities for multimedia IoT system and attacks that can be performed by exploiting those vulnerabilities. Finally, this paper discusses the recent advancements and proposed ideas about increasing the efficiency of PQC and making the IoT network secure for the multimedia data in the rising quantum environment.

Metaverse technology has been becoming more prevalent recently because of its potential to completely alter how people share and interact with each other worldwide. Central to this growth are two key technologies: blockchain and multimedia. Based on these technologies, features of metaverse recently attract the attention due to its immersive and decentralized nature which include other features also. The inclusion of blockchain technology into facilities of metaverse results in the rise of shared ecosystem and it also offers privacy protection, and security and digital asset monitoring in both real world and in virtual assets. The opportunities and challenges associated with the deployment and development of metaverse technologies, including privacy, scalability, and security issues, are fixed by blockchain integration while multimedia technology is pivotal for creating immersive experiences allowing realistic visuals within the metaverse which support the metaverse to attract the users worldwide. In this paper, an overview of the current state of metaverse technologies are provided with multimedia and blockchain technology. This paper begins by description of blockchain technology following with multimedia technology. Further, the paper discusses various components and characteristics of the metaverse, its different use cases, and associated technologies. Furthermore, the paper illustrates the integration of metaverse with blockchain and discusses about how multimedia technology enhances the metaverse. Finally, this paper highlights various recent advancements such as authentication and identity management, management of data, decentralized governance, system of reputation, extended reality technologies, 3D content creation, and digital avatars.

Cloud computing and multimedia Internet of Things (IoT) represent two transformative technologies that have reshaped the landscape of computing and communication. Cloud computing offers scalable and on-demand resources, enabling efficient storage, processing, and analysis of vast amounts of data. On the other hand, multimedia IoT involves the integration of multimedia elements into the IoT ecosystem, enriching the sensory experience and enabling new applications. This paper explores the intersection of cloud computing and multimedia IoT, examining the synergies and challenges in leveraging cloud services for managing multimedia data in IoT environments. The study delves into the architectural considerations, security implications, and performance optimizations required to harness the full potential of this convergence. Through a comprehensive analysis, this work contributes valuable insights into the evolving paradigm of cloud computing and multimedia IoT, offering guidance for researchers, practitioners, and policymakers navigating this dynamic landscape.

In daily work life, XR refers to VR, AR, and MR, which is becoming more common. These technologies have been developing since 1957. Cross-platform, cross-media story, and brand worlds are the growing fields of XR application, these are few examples which explain that game industry features beyond gaming. But the growing amount of user participation is the main challenge in creating such an application which satisfied the need of user without compromising the experience. XR is also changing multimedia, by combining real-time interaction and push the limits of immersive experience. New technologies in this field deal with great amount of user interaction in real world. For this, new hardware and software have entered the consumer market, and entirely new technologies are being created at affordable pricing. This paper presents the information about the current technologies used in reality spectrum, how they contribute in gaming and different modes for users to interact and immerse. It also explores devices like VR headsets to AR-enabled glasses and MR resultant combination of virtual and physical space. This paper also highlights the role of XR in multimedia, including holographic video, remote rendering, and media streaming. Finally, it provides detailed information about the hardware, software, and devices which are used for developing in this field and recent advancement.

Healthcare has undergone a transformation due to medical imaging technology, which offers detailed insights into the human body. The proposed model aims to advance the analysis of brain tumors by utilizing a complex method that combines CT and MRI -Scan data into an intuitive Flask-based web application. Pioneer-based registration guarantees accurate alignment of various patient pictures, creating a common coordinate system for thorough anatomical comparisons. We use transfer learning to improve the analytical capabilities of the VGG-19 CNN architecture, allowing for more nuanced analysis. The next step, Image Fusion, uses the complimentary capabilities of data from both CT and MRI scans to maximize the segmentation accuracy. By isolating areas of interest, the Watershed transformation makes it easier to categorize data more precisely. Furthermore, a CNN predicts the existence of brain tumors, expediting the process of diagnosis and treatment, and eventually supporting a patient-centered and effective healthcare paradigm. These developments improve accuracy and accessibility in medical procedures while also streamlining the challenging assessment of brain tumors yielding an accuracy of 92.16%.