A Distributed Ambient Intelligence Based Multi-Agent System for Alzheimer Health Care

This chapter presents ALZ-MAS (Alzheimer multi-agent system), an ambient intelligence (AmI)-based multi-agent system aimed at enhancing the assistance and health care for Alzheimer patients. The system makes use of several context-aware technologies that allow it to automatically obtain information from users and the environment in an evenly distributed way, focusing on the characteristics of ubiquity, awareness, intelligence, mobility, etc., all of which are concepts defined by AmI. ALZ-MAS makes use of a services oriented multi-agent architecture, called flexible user and services oriented multi-agent architecture, to distribute resources and enhance its performance. It is demonstrated that a SOA approach is adequate to build distributed and highly dynamic AmI-based multi-agent systems

3rd Symposium of Ubiquitous Computing and Ambient Intelligence 2008

The Symposium on Ubiquitous Computing and Ambient Intelligence (UCAmI) began as a workshop held in 2003 in San Sebastián (Spain) under the Spanish Artificial Intelligence Conference. This event gathered 32 attendees and 18 papers were presented. The second edition, already as a Symposium, took place in Granada (Spain) under the first Spanish Computer Science Conference (CEDI). Later, in 2006, a second workshop was celebrated in Ciudad Real and, in 2007; the second Symposium was organized in Zaragoza by the CEDI conference. Now we continue to work on the organization of this event in Salamanca, a beautiful Spanish city. The European Community and the Sixth and Seventh Framework Programs encourage researchers to explore the generic scope of the AmI vision. In fact, some researchers have a crucial role in this vision. Emile Aarts from Philips describes Ambient Intelligence as "the integration of technology into our environment, so that people can freely and interactively utilize it". This idea agrees with the proposal of Mark Weiser regarding the Ubiquitous Computing paradigm. The UCAmI community tries to join experts around the world in order to promote collaborations and to put into practice studies for involving people into intelligent environments so that the "Everyday Computing" concept can be a reality. The UCAmI technical program includes 40 papers (31 long paper, 6 short paper and 3 doctoral consortium) selected from a submission pool of 56 papers, from 11 different countries

ALZ-MAS: Alzheimer’s special care multi-agent system.

This paper presents a multi-agent based solution for Alzheimer's residential health care. The carers work in a very dynamic environment and the use of planning agents helps them to adapt to changes and optimizes their working day. The ALZ MAS system includes agents that take care of the patients and of the security of the environment. Some of the agents use RFID technology to control the location of the patients, necessary to create and execute dynamic plans and to guarantee the security of the residence. The deliberative agents used cooperate with each other and have learning capabilities. This paper also shows how to construct multi-objective driven agents using a case-based reasoning methodolog

CROS: A Contingency Response multi-agent system for Oil Spills situations

This paper presents CROS, a Contingency Response multi-agent system for Oil Spill situations. The system uses the Case-Based Reasoning methodology to generate predictions to determine the probability of finding oil slicks in certain areas of the ocean. CBR uses past information to generate new solutions to the current problem. The system employs a SOA-based multi-agent architecture so that the main components of the system can be remotely accessed. Therefore, all functionalities (applications and services) can communicate in a distributed way, even from mobile devices. The core of the system is a group of deliberative agents acting as controllers and administrators for all applications and services. CROS manages information such as sea salinity, sea temperature, wind speed, ocean currents and atmosphere pressure, obtained from several sources, including satellite images. The system has been trained using historical data obtained after the Prestige accident on the Galician west coast of Spain. Results have demonstrated that the system can accurately predict the presence of oil slicks in determined zones after an oil spill. The use of a distributed multi-agent architecture has been shown to enhance the overall performance of the system

Ambient Intelligence Based Architecture for Automated Dynamic Environments.

This paper presents an Ambient Intelligence based architecture that uses intelligent agents with reasoning and planning mechanisms. The agents have the ability to obtain automatic and real time information about the context using a set of technologies, such as radio frequency identification, wireless networks and wireless control devices. The architecture can be implemented on a wide diversity of dynamic environments. A case study is presented, describing the main characteristics of the planning mechanism supported by the architecture, implemented in a geriatric residence, giving the agents a high level of autonomy and flexibility for solving problems

Improving an Ambient Intelligence Based Multi-Agent System for Alzheimer Health Care using Wireless Sensor Networks

This paper describes last improvements made on ALZ-MAS; an Ambient Intelligence based multi-agent system aimed at enhancing the assistance and health care for Alzheimer patients. The system makes use of several context-aware technologies that allow it to automatically obtain information from users and the environment in an evenly distributed way, focusing on the characteristics of ubiquity, awareness, intelligence, mobility, etc., all of which are concepts defined by Ambient Intelligence. Among these context-aware technologies we have Wireless Sensor Networks. In this sense, ALZ-MAS is currently being improved by the use of a new platform of ZigBee devices that provides the system with new telemonitoring and locating engine

Combining Improved FYDPS Neural Networks and Case-Based Planning — A Case Study

This paper presents a hybrid deliberative architecture based on the concept of CBPBDI agent. A CBP-BDI agent is a BDI agent that incorporates a CBP reasoning engine. The work here presented focuses in the development of the CBP internal structure. The planning mechanism has been implemented by means of a novel FYDPS neural network. The system has been tested and this paper presents the results obtained

A Case-Based Planning Mechanism for a Hardware-Embedded Reactive Agents Platform

Wireless Sensor Networks is a key technology for gathering relevant in- formation from different sources. In this sense, Multi-Agent Systems can facilitate the integration of heterogeneous sensor networks and expand the sensors’ capa- bilities changing their behavior dynamically and personalizing their reactions. Both Wireless Sensor Networks and Multi-Agent Systems can be successfully applied to different management scenarios, such as logistics, supply chain or pro- duction. The Hardware-Embedded Reactive Agents (HERA) platform allows developing applications where agents are directly embedded in heterogeneous wireless sensor nodes with reduced computational resources. This paper presents the reasoning mechanism included in HERA to provide HERA Agents with Case- Based Planning features that allow solving problems considering past experiences.

Intelligent environment for monitoring Alzheimer patients, agent technology for health care

This paper presents an autonomous intelligent agent developed for monitoring Alzheimer patients' health care in execution time in geriatric residences. The AGALZ (Autonomous aGent for monitoring ALZheimer patients) is an autonomous deliberative case-based planner agent designed to plan the nurses' working time dynamically, to maintain the standard working reports about the nurses' activities, and to guarantee that the patients assigned to the nurses are given the right care. The agent operates in wireless devices and is integrated with complementary agents into a multi-agent system, named ALZ-MAS (ALZheimer Multi-Agent System), capable of interacting with the environment. AGALZ description, its relationship with the complementary agents, and preliminary results of the multi-agent system prototype in a real environment are presented

Mitigation of the Ground Reflection Effect in Real-Time Locating Systems

Real-Time Locating Systems (RTLS) are one of the most promising ap- plications based on Wireless Sensor Networks and represent a currently growing market. However, accuracy in indoor RTLS is still a problem requiring novel solu- tions. One of the main challenges is to deal with the problems that arise from the effects of the propagation of radio frequency waves, such as attenuation, diffrac- tion, reflection and scattering. These effects can lead to other undesired problems, such as multipath and the ground reflection effect. This paper presents an innova- tive mathematical model for improving the accuracy of RTLS, focusing on the mitigation of the ground reflection effect by using Artificial Neural Networks