Exploring Older Adults’ Willingness to Install Home Surveil-Lance Systems in Taiwan: Factors and Privacy Concerns

Abstract

Taiwan has a rapidly increasing aging population with a considerably high life expectancy rate, which poses challenges for healthcare and medical systems. This study examines three key factors: safety concerns, family expectations, and privacy concerns, and their influence on surveillance system installation decisions. A cross-sectional study was conducted involving a group of physically active older adults in Taiwan, using a questionnaire to collect data on the reasons for in-stalling a surveillance system and preferences for three image privacy protection techniques: blurring the face and transformation to a 2D or 3D character. The study concluded that while safety concerns and family expectations facilitate the adoption of surveillance systems, privacy concerns serve as a significant barrier. Furthermore, older adults showed a clear preference for avatar-based privacy protection methods over simpler techniques, such as blurring. The outcomes of this research will be instrumental in shaping the development of privacy-conscious home surveillance technologies, adeptly balancing safety and privacy. This understanding can pave the way for technology design that skillfully balances privacy concerns with remote monitoring quality, thereby enhancing the well-being and safety of this demographic. These results could possibly be extended to other demographics as well.

AI-Driven Privacy in Elderly Care: Developing a Comprehensive Solution for Camera-Based Monitoring of Older Adults

“…In this context, the preferences of older adults for privacy-protective surveillance methods, particularly those utilizing avatar-based systems, become highly relevant. According to one study [7], older adults naturally have concerns regarding both visual and behavioral privacy, with a stronger inclination towards maintaining visual privacy. A significant majority of healthy older adults show a preference for technologies that transform their actual images into avatars, rather than more invasive methods.…”

“…These technologies provide a detailed overview of an elderly individual's environment and health status [5]. Following this, developments in AI, specifically in person detection [6], pose estimation [7], and action recognition [8], have greatly improved the accuracy of these systems. These AI-driven techniques allow for precise identification and automated analysis of elderly movements, aiding in early detection of potential health risks.…”

“…However, recent advances in edge computing rely on minimal data transmission, meaning that only essential information, such as alerts or behavioral data, is transmitted to servers and caregivers. While this method effectively addresses visual privacy concerns [7], it does not provide caregivers with a complete picture of a scene. This limitation is of the utmost concern, since fall detection and behavioral analysis models, although useful, are not infallible and are prone to false alarms and missed incidents.…”

“…With the elderly population valuing their independence and dignity, the intrusive nature of continuous monitoring can be a source of discomfort and stress. Therefore, smart home technologies like camera monitoring systems, increasingly adopted to support aging in place, must balance effective monitoring with privacy protection [7].…”