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Older adults

Characteristics of social robots: A framework for development

May 28, 2025 by Jordan Tschida, Katina Michael, Troy McDaniel

Social robots hold great promise for assisting both older adults with dementia and those in good health. Yet, little is known about how people want to interact with these robots. This article introduces a framework for the key features social robots should have, based on insights from a four-month study of how seniors engage with robots through conversation and interaction. We … [Read more...] about Characteristics of social robots: A framework for development

Ecofriendly autonomous smart walker for enhanced ambulatory assistance

May 24, 2024 by Isaac Asante, Lau Bee Theng, Mark Tee Kit Tsun, John Chua

The global demographic landscape is undergoing a significant transformation, characterized by a rising elderly population and an increasing number of people requiring rehabilitation and ambulatory assistance. This study introduces an innovative, ecofriendly smart walker designed to assist physically disadvantaged individuals in navigating their environment safely and … [Read more...] about Ecofriendly autonomous smart walker for enhanced ambulatory assistance

Social issues of aging: Immersive technology solutions

November 7, 2023 by Xiang-Rui Huang

With the advancement of medical care and technology, human life expectancy is increasing, many advanced countries have aging societies, and the elderly have increasing needs for society to address; these have become some of the main problems to be solved in modern society (Chang et al., 2021). To solve these problems, long-term care institutions have become one of the … [Read more...] about Social issues of aging: Immersive technology solutions

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About the Magazine

IEEE Potentials Magazine is the publication dedicated to undergraduate and graduate students and young professionals. IEEE Potentials explores career strategies, the latest in research, and important technical developments. Through its articles, it also relates theories to practical applications, highlights technology’s global impact, and generates international forums that foster the sharing of diverse ideas about the profession.

POPULAR ARTICLE

Privacy-preserving distributed learning: Techniques, applications, and future challenges

The rapid increase in data generated by connected devices has created a pressing need for privacy-preserving techniques in distributed learning. This article examines methods that enable collaborative machine learning (ML) while maintaining data security and user privacy. Key approaches such as federated learning (FL), differential privacy (DP), secure multiparty computation (SMPC), and homomorphic encryption (HE) are analyzed for their unique capabilities and various applications. FL facilitates model training across decentralized data sources, ensuring data remain local, while DP mitigates privacy risks by adding controlled noise. SMPC and HE support secure computations on encrypted data, maintaining confidentiality during processing. Despite their effectiveness, these techniques face challenges related to computational complexity, scalability, and regulatory compliance. The article reviews current advancements, practical implementations, and future directions, emphasizing the need for optimized, accessible solutions to enhance data security in distributed systems.

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