Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: May 19, 2025
Language: Английский
Sustainability, Journal Year: 2023, Volume and Issue: 15(10), P. 8354 - 8354
Published: May 21, 2023
The integration of AI and the IoT in education has potential to revolutionize way we learn. Personalized learning, real-time feedback support, immersive learning experiences are some benefits that can bring system. In this regard, research paper aims investigate how be integrated into sustainable order provide students with personalized during pandemics, such as COVID-19, for smart cities. study’s key findings report employed through learning. AI-powered algorithms used analyze student data create each student. This includes providing tailored content, assessments, align their unique style pace. Additionally, communicate a more natural human-like way, making experience engaging interactive. Another aspect obtained from is ability support. IoT-enabled devices, cameras microphones, monitor engagement feedback. then use these adapt real time. tablets laptops, collect process work, allowing automatic grading assignments assessments. technology facilitate remote monitoring which would particularly useful who cannot attend traditional classroom settings. Furthermore, also intelligent personal environments (PLEs) personalized, adaptive, experiences. combined algorithms, PLE student’s needs preferences. It concluded integrating people learn, support opening up new opportunities disadvantaged students. However, it will important ensure ethical responsible all have equal access technologies.
Language: Английский
Citations
48
The Journal of Supercomputing, Journal Year: 2024, Volume and Issue: 81(1)
Published: Dec. 10, 2024
The integration of artificial intelligence (AI) has caused information and communication technology (ICT) to undergo a number recent rapid fluctuations. These changes have primarily affected the areas management, end-to-end device interconnectivity, resource organization, communication, networking, application-related aspects ICT. Owing complex structure applicational connectedness, evaluating each aforementioned opportunities concurrently reflects idea heterogeneity. association multiple end devices, particularly in interoperable space, integrity, privacy protection, security, provenance, massive volume everyday media data generated modern healthcare setting could also provide significant issues. To address these issues, decentralized, secure, economical optimization, intelligent network activities organization are necessary. Blockchain plays crucial role providing distributed storage sharing, exchange for automated decision-making, privacy, security AI-enabled machine learning (ML) models. However, models—support vector machine, particular—have impact on growth consortium networks among connected nodes, resolving issues with scalability, processing. By three main problems seamless peer-to-peer between infrastructure we novel technique this proposed architecture. approach is unique, as demonstrated by simulation-based results, which display huge differences 1.37%, 1.56%, 1.87%, respectively. background evaluation consists following areas: (i) protect decision-making; (ii) integrity smooth sharing exchange; (iii) optimization enable across heterogeneous devices.
Language: Английский
Citations
17
Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 141, P. 109838 - 109838
Published: Dec. 13, 2024
Language: Английский
Citations
15
International Journal of Intelligent Systems, Journal Year: 2024, Volume and Issue: 2024, P. 1 - 16
Published: March 22, 2024
Electronic Health Record (EHR) systems are a valuable and effective tool for exchanging medical information about patients between hospitals other significant healthcare sector stakeholders in order to improve patient diagnosis treatment around the world. Nevertheless, majority of hospital infrastructures that now place lack proper security, trusted access control, management privacy confidentiality concerns current EHR supposed provide. Goal. For various systems, this research proposes Blockchain-enabled Hyperledger Fabric Architecture as solution delicate issue. The three steps suggested system secure upload phase, download authentication. Patient registration, login, verification make up authentication step. administrator grants authorization read, edit, delete, or revoke files following user details verification. In feature extraction is carried out first, then hashed policy created from extracted feature. Next, hash value stored an IoT-based blockchain. uploaded additionally encrypted before being on cloud server. step, physician uses send request decrypts corresponding files. experimental findings demonstrate outperformed cutting-edge techniques. proposed Modified Key Policy Attribute-Based Encryption performs better remaining 10 25 mb file sizes. This IoT framework compares MKP-ABE with certain efficiency indicators, such encryption, decryption period, protection level analysis memory use, resource use decryption, time, transfer which present KP-ABE, ECC, RSA, AES. Here, device requires 4008 ms data encryption 4138 decryption.
Language: Английский
Citations
12
IEEE Transactions on Green Communications and Networking, Journal Year: 2024, Volume and Issue: 8(3), P. 1026 - 1036
Published: May 6, 2024
Autonomous decision-making is considered an intercommunication use case that needs to be addressed when integrating open radio access networks with mobile-based 5G communication. The robustness of innovations diminished by the conventional method designing end-to-end network solution. Through analysis these possibilities, this paper presents a machine learning-based intelligent system whose primary goal load balancing using Artificial Neural Networks Particle Swam Optimization-enabled metaheuristic optimization mechanisms for telecommunication industry requests, like product compatibility. We increase proposed system's reliability third-generation partnership project standards automate distribution transactional among various connected units. This encloses hierarchy automation enabled artificial intelligence. Conversely, AI-enabled control explores barriers next-generation intercommunication, including those after 5G. It covers deterministic latency and capabilities, physical layer-based dynamic controls, privacy security, testing applications AI-based controller designs.
Language: Английский
Citations
12
Computer Standards & Interfaces, Journal Year: 2024, Volume and Issue: 91, P. 103876 - 103876
Published: May 28, 2024
Language: Английский
Citations
12
Egyptian Informatics Journal, Journal Year: 2024, Volume and Issue: 27, P. 100502 - 100502
Published: July 1, 2024
Owing to the major development of social media platforms, usage technological adaptation increases by means editing software tools. Posting in communication environments has become one our common daily routines. Before posting, various generators are used manipulate pixel values, such as for enhancing brightness and contrast. Undoubtedly, this helps bring posting from ordinary outstanding. But a type crosses line terms creating fakes—anything that comes anywhere does not retain its originality anyway. It poses series issues process multimedia forensics investigation chain custody. In order restrict attempts at deep faking make hierarchy more effective, efficient, reliable socio-cyber space (SCS), paper presents novel framework called DF-SCW. A digital forensics-enabled world with artificial intelligence (AI), especially neural networks (DNNs), detecting analyzing fake investigations on platforms. compares pixels their neighboring values same (such images videos) identify information about original one. There is flag designed filter out malicious dangerous attempts, like powerful leader declaring war. Putting flags fakes investigators resist sharing posts. addition, other prospect research ecosystem appropriate take qualitative judgments real-time while uploaded The simulation proposed DF-SCW tested three different Instagram, Facebook, Twitter. Through experiment, outperformed detection, identification, analysis deepfake an increased rate 3.77%.
Language: Английский
Citations
11
IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 96946 - 96996
Published: Jan. 1, 2024
Internet of Things (IoT) is an important technology employed in a variety different applications, such as transportation, healthcare, and manufacturing. In recent years, the number IoT devices deployed globally has been increasing at rapid pace estimated to reach 20 billion by end 2025. modern industry, plays pivotal role monitoring condition industrial machines and, consequently, improving efficiency processes. To optimize various Artificial Intelligence (AI) techniques have adopted, leading new computing paradigm, namely, Industrial (i.e. AIoT). this paper, we describe challenges tackle opportunities explore AIoT. Specifically, first review use state-of-the-art AI methods AIoT with focus on Deep Learning (DL) Machine (ML) techniques. Thereafter, present series applications The key associated implementation are also discussed. addition, societal economic impacts briefly described. Finally, outline future research directions AIoT, which should be further investigated fully utilize potential innovative technology.
Language: Английский
Citations
10
Computer Networks, Journal Year: 2024, Volume and Issue: 245, P. 110373 - 110373
Published: March 27, 2024
Language: Английский
Citations
7
Future Internet, Journal Year: 2024, Volume and Issue: 16(11), P. 394 - 394
Published: Oct. 26, 2024
The Internet of Things (IoT) has radically changed the industrial world, enabling integration numerous systems and devices into ecosystem. There are many areas manufacturing industry in which IoT contributed, including plants’ remote monitoring control, energy efficiency, more efficient resources management, cost reduction, paving way for smart framework Industry 4.0. This review article provides an up-to-date overview machine learning (ML) algorithms applied to (SM), analyzing four main application fields: security, predictive maintenance, process additive manufacturing. In addition, paper presents a descriptive comparative ML mainly used Furthermore, each discussed topic, deep analysis recent solutions reported scientific literature is introduced, dwelling on architectural aspects, sensing solutions, implemented data strategies, communication tools, performance, other characteristic parameters. comparison highlights strengths weaknesses solution. Finally, presented work outlines features functionalities future IoT-based applications.
Language: Английский
Citations
7