Find It - An Assistant Home Agent

Cognitive impaired population face with innumerable problems in their daily life. Surprisingly, they are not provided with any help to perform those tasks for which they have difficulties. As a consequence, it is necessary to develop systems that allow those people to live independently and autonomously. Living in a technological era, people could take advantage of the available technology, being provided with some solutions to their needs. This paper presents a platform that assists users with remembering where their possessions are. Mainly, an object recognition process together with an intelligent scheduling applications are integrated in an Ambient Assisted Living (AAL) environment.

Sensor-driven agenda for intelligent home care of the elderly

The exponential increase of home-bound persons who live alone and are in need of continuous monitoring requires new solutions to current problems. Most of these cases present illnesses such as motor or psychological disabilities that deprive of a normal living. Common events such as forgetfulness or falls are quite common and have to be prevented or dealt with. This paper introduces a platform to guide and assist these persons (mostly elderly people) by providing multisensory monitoring and intelligent assistance. The platform operates at three levels. The lower level, denominated ‘‘Data acquisition and processing’’performs the usual tasks of a monitoring system, collecting and processing data from the sensors for the purpose of detecting and tracking humans. The aim is to identify their activities in an intermediate level called ‘‘activity detection’’. The upper level, ‘‘Scheduling and decision-making’’, consists of a scheduler which provides warnings, schedules events in an intelligent manner and serves as an interface to the rest of the platform. The idea is to use mobile and static sensors performing constant monitoring of the user and his/her environment, providing a safe environment and an immediate response to severe problems. A case study on elderly fall detection in a nursery home bedroom demonstrates the usefulness of the proposal.

A Platform to Emulate Ambient Assisted Living Environments

According to the opinion of clinicians, emerging medical conditions can be timely detected by observing changes in the activities of daily living and/or in the physiological signals of a person. To accomplish such purpose, it is necessary to properly monitor both the person’s physiological signals as well as the home environment with sensing technology. Wireless sensor networks (WSNs) are a promising technology for this support. After receiving the data from the sensor nodes, a computer processes the data and extracts information to detect any abnormality. The computer runs algorithms that should have been previously developed and tested in real homes or in living-labs. However, these installations (and volunteers) may not be easily available. In order to get around that difficulty, this paper suggests the making of a physical model to emulate basic actions of a user at home, thus giving autonomy to researchers wanting to test the performance of their algorithms. This paper also studies some data communication issues in mobile WSNs namely how the orientation of the sensor nodes in the body affects the received signal strength, as well as retransmission aspects of a TDMA-based MAC protocol in the data recovery process.