Journal of Future Internet and Hyperconnectivity (e-ISSN: 3048-9210)

Old Pages, New Readers: A Marketplace of Used Books

Bipin Yashasvi, Shivam Tiwari — Mon, 24 Mar 2025 00:00:00 +0000

Students from middle-class or lower-class families aspire to crack competitive exams but fail to purchase standard books, as their prices are very high. At the same time, many used books are sold as scrap for just a few rupees per kilogram. To solve this problem, this project aims to create a website where students can buy and sell used books at affordable prices. This platform will help the students find the books they need at lower prices while allowing sellers to earn a fair amount instead of selling their books as scrap. The website will have a simple interface so that students can easily use it. It will include secure payment options and easy navigation for a smooth experience. It helps in reducing education costs and promotes the reuse of books.

IoT Requirements for Smart Healthcare Systems Using Ambient Intelligence

Mohammad Esmaeili, Maysam Toghraee — Wed, 12 Mar 2025 00:00:00 +0000

The Internet of Things (IoT) and ambient intelligence are transforming healthcare delivery and ushering in a new era of smart healthcare systems. These technologies enable continuous health data collection, remote patient monitoring, and personalized care through IoT medical sensors and IoT-enabled telemedicine. As healthcare providers seek to improve patient outcomes and operational efficiency, integrating IoT and ambient intelligence into smart healthcare systems has become a critical focus. This study examines the key requirements for implementing IoT and ambient intelligence into smart healthcare systems. It examines the essential components of IoT healthcare applications, including sensors, connectivity, and data analytics. This study also looks at how to enhance the ambient intelligence of patient care environments and discusses important considerations around healthcare security, privacy, and interoperability standards. Finally, it addresses the challenges and future directions for advancing smart healthcare solutions based on the Internet of Things. There is great hope that the Internet of Things and ambient intelligence will provide a better future for human life. Of course, the mechanisms for using these technologies should be examined based on human needs and in a way that provides a smart, comfortable, and problem-free life for each individual in society, away from security and privacy concerns and at the lowest cost.

AI-Driven Convergence: Transforming 6G Network Mental Health and Assistive Technologies

Tue, 25 Mar 2025 00:00:00 +0000

This review undertakes a comprehensive examination of the convergence of the sixth-generation (6G) wireless networks, Artificial Intelligence (AI), and their application in mental health and assistive technologies. The review underscores the pivotal role of AI as a catalyst for innovation across these disciplines. In summary, this review presents a visionary framework for future systems wherein AI is not merely a supplementary component but a fundamental element, enabling the creation of intelligent, adaptable, and secure technologies.
These systems are designed to enhance wireless communications, provide effective mental health support, and improve the quality of life through assistive technologies. The focus of this review enfolds the encompassing of both technological advancements and their practical application to cater to a diverse range of user needs. The integration of AI and the 6G wireless networks is expected to revolutionize the way we approach mental health and assistive technologies, enabling more personalized, efficient, and effective interventions.
Furthermore, this review highlights the potential of AI-powered 6G wireless networks to transform the lives of individuals with disabilities, elderly populations, and those living in remote or underserved areas. By leveraging the capabilities of AI and 6G wireless networks, we can create more inclusive, accessible, and equitable technologies that promote social welfare and improve overall quality of life.

Advancing Privacy Standards and Evaluation Metrics for Robust AI Model Deployment

G.V. Rajeswari, Manas Kumar Yogi — Thu, 13 Feb 2025 00:00:00 +0000

The transformative potential of generative AI, encompassing large language models (LLMs) and generative adversarial networks (GANs), is undeniable, revolutionizing content creation, automation, and AI applications. However, this rapid progress is accompanied by escalating security and privacy vulnerabilities. The very capabilities that make these models so powerful also create opportunities for malicious exploitation, including data leakage, adversarial attacks, and the exposure of sensitive information. This paper delves into the critical area of privacy-preserving techniques for generative AI, exploring promising solutions such as differential privacy, federated learning, and homomorphic encryption. We analyze the landscape of emerging security threats, including model inversion attacks aimed at reconstructing training data, and prompt injection attacks designed to manipulate model behavior. Furthermore, we review the evolving landscape of data privacy standards and regulations, with a particular focus on the General Data Protection Regulation (GDPR), to understand the legal and ethical implications of deploying generative AI. A key contribution of this work is the proposal of secure deployment practices, offering practical guidelines for mitigating privacy risks throughout the generative AI lifecycle. This paper aims to establish a robust and comprehensive framework for evaluating and addressing privacy risks, ensuring compliance with relevant regulations, and ultimately promoting the responsible and secure utilization of generative AI across diverse industries. By addressing these critical challenges, we can harness the immense potential of generative AI while safeguarding individual privacy and fostering trust in these powerful technologies.