Intelligent Tele-Homecare: The Application of Soft-Computing Models in Sensor Agent Network Systems

This paper conceptualises the development of an Intelligent Home Care system to assist health care professionals and carers in providing an enhanced level of support to senior citizens. The social demographics in the developed world indicate a decline in population growth, indicating a need for greater resources to be dedicated towards enhancing the lives of an aging society. Furthermore, the dissociation of extended family structures in modern society results in senior citizens to take greater independence in managing their own lives. With the technological advances in the Tele-Homecare domain, there is an impetus to develop improved computational techniques that reflect the nature of complex systems in medicine and biology

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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Collaborative Target Tracking for Laparoscopic Surgery Simulation utilizing Anticipatory Sanets

Laparoscopic Surgical Simulation tools are an essential training resource for surgeons specializing in laparoscopic surgical procedures. This paper presents a Sensor-Actor Network (Sanet) training environment to simulate laparoscopic medical procedures, with the intention of using anticipatory models for target tracking and navigation. This case study implements the Belief-Desire-Intention (BDI) agent-based software reasoning approach, with neural network processes to demonstrate path trajectory planning effectively aids in the handling of laparoscopic equipment in different predefined scenarios. The immersion of the trainer in the simulation environment provides a qualitative and quantitative method of measuring the trainee's efficiency for post-analysis and feedback in laparoscopic procedures

Intelligent Agents for Educational Environments

This paper outlines a concept of employing intelligent agents to simulate, construct and deploy a Smart Library System for an educational facility. Discussion into the many technical challenges driving the concept, ideas behind this approach and the final design rationale are examined. The design model of the Smart Library System that uses Multi-agent simulation and distributed middleware frameworks can be successfully applied to many similar application areas as a means of automating a wide variety of asset monitoring and control tasks in both traditional and distributed systems concerns. Educational environments containing material such as books, multimedia and laboratory equipment can benefit from the proposed software solution allowing such assets to be efficiently managed and monitored. This subsequently would improve the quality of teaching and training support

A Smart-Shop System - Mulit-Agent Simulation System for Monitoring Retail Activities

This paper outlines a concept of employing intelligent agents to simulate and deploy a Smart-Shop System for retail environments. The discussion will examine the technical and conceptual challenges, main ideas and the final design rationale. The design model of the Smart-Shop System uses Multi-Agent Simulation Systems (MASS) and distributed middleware frameworks to automate a wide variety of asset monitoring and control tasks in traditional and distributed system concerns, which can be applied to similar application areas. Retail organisations containing any form of physical inventory can benefit from the proposed software solution by allowing assets to be efficiently managed and monitored. This would improve the quality of business trade and strategic marketing to sustain sales growth

An Anticipatory Sanet Environment for Training and Simulation of Laparoscopic Surgical Procedures

Surgical simulation environments are required to train laparoscopic surgeons to become familiar with the technology, before they operate on patients. The chapter examines how a Sensor-Actor Network (Sanet) incorporated into the laparoscopic training facility can be augmented with the Belief-Desire-Intention (Bdi) agents for autonomous operation of the sensor facility along with the training environment. In addition to neural network processes, path trajectory estimation can be superimposed as a visual aid in a variety of training scenarios. The algorithms used in this experiment provides a balanced approach to monitor the training surgeons level of progress and feedback as they perform the simulated training procedures

Steering a Swarm of Autonomous Sailing Vehicles implementing Biomimetic SANET Middleware

This paper describes the incorporation of object tracking heuristics with a dynamic sailing model for surface sailing vessels, using the maneuvering approach by Jouffroy (2009). A simplified dynamic model is simulated, with a path generation scheme and controller for a fundamental maneuver in sailing known as tacking. In addition, this maneuver is incorporated with obstacle algorithms for detection and avoidance. The incorporation of Sensor-Actor Networks (Sanets) in the sailing vessel makes it possible to incorporate sensors in the structure to monitor localized obstacles in an energy efficient manner, while statistical data is relayed to a centralized base station for post-processing and analysis of global environmental conditions

Sensor-Actor Networks utilising the Spring Tensor Model for Laparoscopic Surgical Training Simulations

The use of Sensor-Actor Networks (SANETs) has been applied to surgical training contexts, to illustrate how the Spring Tensor Model (STEM) can be used for laparoscopic end-effector navigation through obstacles and high-risk areas. The modelling of agents as interactive components of a laparoscopic simulator seeks to emulate the physical environment as a virtualised representation in the integrated SANET infrastructure. Combining SANET middleware framework paradigms to a surgical knowledge-based construct demonstrates how SANETs can enhance medical practice. The architectural hybridisation of the training framework has enabled the adaptation of STEM modelling techniques for a simulated laparoscopic training methodology. The primary benefit of the architecture is that this integration strategy has resulted in a seamless transition of the heuristic framework to be applied to surgical training