any countries face an ever-growing need to supply constant care and support for their disabled and elderly populations. Over the past 30 years, the number of Europeans over 60 years of age has risen by about 50 percent, and now represents more than 25 percent of the population. Within 20 years, experts estimate that this percentage will rise to one-third of the population, or more than 200 million people. 1 Studies in other parts of the world show similar tendencies. In the US, people over 65 years are the fastestgrowing segment of the population; by 2020, they'll represent about 1 of 6 citizens. Furthermore, many people over 85 require continuous monitoring and daily care. Finding more effective ways to provide care for elderly and disabled populations has become a major challenge for the scientific community. 1 Creating secure, unobtrusive, and adaptable environments for monitoring and optimizing healthcare will become vital in the near future. Recently, researchers have begun exploring multiagent systems and architectures to create intelligent supervision systems. These intelligent systems aim to support elderly and Alzheimer's patients in all aspects of daily life, predicting potential hazardous situations and delivering physical and cognitive support. When coupled with RFID, Wi-Fi technologies, and handheld devices, such multiagent systems offer many new possibilities and have given rise to new fields aimed at integrating distributedintelligence software applications into our daily lives. One such field is ambient intelligence, which proposes a new interaction model in which developers adapt technology to people and their context 1 and offer users simple, natural, and effortless system interactions. Ambient intelligence's goal is to develop intelligent, intuitive systems and interfaces that can ubiquitously recognize and respond to user needs. To achieve this, developers must provide ubiquitous computation and communication capabilities, focus on users' needs during development, and create technologically complex environments in medical, domestic, academic, and other contexts. Guided by these requirements, we've developed Geriatric Ambient Intelligence, an intelligent environment that integrates multiagent systems, mobile devices, RFID, and Wi-Fi technologies to facilitate management and control of geriatric residences. At GerAmi's core is the geriatric agent (GerAg), a deliberative agent that incorporates a case-based planning (CBP) mechanism to optimize work schedules and provide up-to-date patient and facility data. We've successfully implemented a system prototype at a care facility for Alzheimer patients. • • •
Multi-agent systems are also used in GerAmi, an AmI environment to supply care and support to elderly people which strongly relies on RFID and Wi-Fi technologies REF .
GerAmi: Improving Healthcare Delivery in Geriatric Residences
IEEE Intelligent Systems
IEEE Intelligent Systems
Computer Science