Claudio Guerra

CARDEAGate: Low-cost, ZigBee-based localization and identification for AAL purposes

World population is facing deep demographic changes. A number of societal challenges are to be tackled, and possible support from ICT is sought for. AAL (Ambient Assisted Living) technologies, aimed at fostering independent life of elderly people, are therefore becoming increasingly important. Based on the AAL-system named CARDEA and previously developed at the University of Parma, in this paper a new feature is presented, named CARDEAGate and aimed at providing an inexpensive and scarcely intrusive way for providing user localization and identification information. Such information is needed to implement a number of useful functionalities, and most notably to carry out behavioral analysis in a multi-user context. A simple approach, based on a “wireless barrier” and exploiting ZigBee protocol features is shown to provide reliable monitoring information. Preliminary test results are given, whereas a full characterization is currently under way.

A Wearable Sensor for AAL-Based Continuous Monitoring

Continuous monitoring of safety and health conditions are among the primary goals of Ambient Assisted Living technologies. Effective solutions, aimed at fostering independent life of elderly persons, need for carefully balancing system intrusiveness, perspicacity, reliability and cost features. Heterogeneous networks, including different combination of environmental and personal wearable sensors can be used, with relevant value coming from data fusion: analysis techniques, aiming at inferring safety and health-related information in an indirect fashion from behavioral features are being deeply investigated with this aim. Device cooperation and interoperability are thus key factors: in this paper, the development of a wearable sensor suitable for broad range AAL application is introduced, addressing features specifically oriented to behavioral analysis. First, the device itself is capable of analyzing different features of the user motion patterns, synthesizing high-level information simple task identification, energy expenditure on board. This result in better battery management less data transferred over the radio link and interoperability thanks to data abstraction. Second, by means of a suitable operating protocol, it cooperates with environmental sensors e.g., a toilet sensor providing the latters with user identification information, and thus allowing to exploit related data even in a multi-user context. This avoid the need of more expensive and complex indoor localization techniques or of more intrusive identification technologies e.g., NFC/RFID tags.

MuSA: Wearable Multi Sensor Assistant for Human Activity Recognition and Indoor Localization

In this paper a wearable multi-sensor device is used for a Behavioral Analysis (BA) focused on Human Activity Recognition (HAR) and Indoor Localization (IL). The analysis exploit a wearable device equipped with inertial sensors like accelerometer, gyroscope and compass in order to evaluate quantity and quality of movements.

Action tagging in a multi-user indoor environment for behavioural analysis purposes

EU population is getting older, so that ICT-based solutions are expected to provide support in the challenges implied by the demographic change. At the University of Parma an AAL (Ambient Assisted Living) system, named CARDEA, has been developed. In this paper a new feature of the system is introduced, in which environmental and personal (i.e., wearable) sensors coexist, providing an accurate picture of the users activity and needs. Environmental devices may greatly help in performing activity recognition and behavioral analysis tasks. However, in a multi-user environment, this implies the need of attributing environmental sensors outcome to a specific user, i.e., identifying the user when he performs a task detected by an environmental device. We implemented such an “action tagging” feature, based on information fusion, within the CARDEA environment, as an inexpensive, alternative solution to the problematic issue of indoor locationing.

The HELICOPTER Project: A Heterogeneous Sensor Network Suitable for Behavioral Monitoring

In this paper, the infrastructure supporting the HELICOPTER AAL-JP project is described. The project aims at introducing behavioral analysis features for early detection of age-related diseases: to this purpose, a heterogeneous sensor network has been designed and implemented, encompassing in the same vision environmental, wearable and clinical sensors. In order to make environmental sensors suitable for behavioral inference, the issue of activity tagging i.e., attribution to a given user of the action detected by the sensors needs to be tackled. Within the HELICOPTER scenario, cooperation between environmental and wearable sensors is exploited to this aim. Preliminary results offer encouraging perspectives: piloting phase, which will validate the approach on a larger scale, is close to start.

Localization and Identification of a Person in an Indoor Environment Using a Low-Cost ZigBee Based Gateway System

The European population is becoming older and older, causing AT and AAL topics to become more and more important. A ZigBee based low-cost home automation system named CARDEA has been developed at the University of Parma, with the aim to permit elderly people to live their lives autonomously and independently. In this paper is presented a new feature: a gateway monitoring system which allows to detect crossing of a doorway or a predefined gateway and, if the person is carrying a wearable ZigBee sensor, to identify he/she. This technology could be helpful to control movements of a not completely self-sufficient person, to supervise the access to a particular location or to keep track of the person’s habits to possibly relate them to his/her health state.

Comprehensive human monitoring based on heterogeneous sensor network

Healthcare paradigms, due to demographic changes, are definitely aiming at effective prevention and early diagnosis strategies. This inherently calls for continuous monitoring of (ageing) people in their own living environment and while attending at daily living activities. Such monitoring may rely on a wide range of sensing technologies, each featuring different trade-offs among main parameters such as accuracy, expressivity, cost, reliability and intrusively. This includes clinical sensors (suitable for self-managed, precise measurement of physiological parameters), wearable devices (continuously monitoring health or activity features) and environmental sensors distributed in the living environment (suitable for indirect assessment of relevant behaviours, besides serving basic safety purposes). In this chapter, the meaning of human monitoring from a home-care point of view will be defined, and the basic sensor categories will be reviewed. Then, the design and the main features of the CARDEA home monitoring system will be discussed. Finally, some application examples, coming from European project living-lab experiences, will be illustrated, and some results obtained by data fusion and analysis techniques, suitable for inferring health and wellness information by effectively correlating raw data coming from the sensor field, will be presented.

MuSA: A Smart Wearable Sensor for Active Assisted Living

This paper focuses at features introduced in the wearable sensor MuSA, to support behavioral analysis within the context of the HELICOPTER project, funded in the AAL European joint program. In particular, the wearable device performs two key function: on one hand it is used as a behavioral data source, continuously monitoring the quantity of user physical activity (through the energy expenditure index evaluation), location and posture; on the other hand, MuSA enables fusion of data coming from the environmental sensors, properly attributing actions on a particular sensor to a specific user in a multi-user environment. These function are carried out without the need of external devices (RFID tags etc.), but only relying on sensors embedded on the wearable device and its communication capabilities. Some sample results coming from pilot studies are shown.

A Low-Cost ZigBee-Based Gateway System for Indoor Localization and Identification of a Person

The European population is becoming older and older, causing AT (Assistive Technology) and AAL (Ambient Assisted Living) topics to become increasingly important. A ZigBee based low-cost home automation system named CARDEA has been developed at the University of Parma, with the aim to allow elderly people to live their lives autonomously and independently. In this paper a new feature is presented, named CARDEAGate: a gateway monitoring system which allows to detect crossing of a doorway or a predefined gateway and, if the person is carrying a wearable ZigBee sensor, to identify he/she. This technology is very useful to supervise the habits of a not completely self-sufficient person monitoring the access to particular locations or tracking he/she in order to execute a long term behavioral analysis.