Technologies for Ambient Assisted Living: Ambient Communication and Indoor Positioning

In all industrialised countries, the population is aging rapidly as the average life expectancy continues to rise and the number of younger age groups grows smaller. Hence, due to economical and practical reasons, the elders of the near future will likely live longer in their own apartments, particularly because institutionalization is significantly expensive and there is not room for the entire elderly population in currently existing nursing homes. Even more important, nearly all people would choose to live independently as long as possible before moving into an assisted-living facility.A longer period of independent living for elders can be enabled by technical solutions. In this work, two technology areas for assisted living are studied. First, the prevention of feelings of loneliness in elders living alone is studied, and a solution for social inclusion and remote presence is presented. The results of long-lasting field trials are presented and analysed. Secondly, as information regarding the location of the inhabitant in the apartment can be used to provide several assistive services, indoor positioning systems are also studied in this work. Several technologies for indoor positioning are presented and compared. Furthermore, a new system based on capacitive measurement and the results of testing of the system are introduced.Technologies and systems developed here have been implemented into actual systems, and real end users have tested them over long periods of time. Thus, these technologies can be developed into commercial products with reasonable effort. Moreover, in this work it has been proven that the systems developed can actually be used to support the independent living of elders

Hand gesture recognition through capacitive sensing : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Electronics & Computer Engineering at Massey University, School of Food and Advanced Technology (SF&AT), Auckland, New Zealand

Figures 1.1, 1.2, 1.3, 2.1, 2.3 & 2.4 are re-used with permission. Figure 2.2 (=Smith, 1996 Fig 1) ©1996 by International Business Machines Corporation was removed.This thesis investigated capacitive sensing-based hand gesture recognition by developing and validating through custom built hardware. We attempted to discover if massed arrays of capacitance sensors can produce a robust system capable of simple hand gesture detection and recognition. The first stage of this research was to build the hardware that performed capacitance sensing. This hardware needs to be sensitive enough to capture minor variations in capacitance values, while also reducing stray capacitance to their minimum. The hardware designed in this stage formed the basis of all the data captured and utilised for subsequent training and testing of machine learning based classifiers. The second stage of this system used mass arrays of capacitance sensor pads to capture frames of hand gestures in the form of low-resolution 2D images. The raw data was then processed to account for random variations and noise present naturally in the surrounding environment. Five different gestures were captured from several test participants and used to train, validate and test the classifiers. Different methods were explored in the recognition and classification stage: initially, simple probabilistic classifiers were used; afterwards, neural networks were used. Two types of neural networks are explored, namely Multilayer Perceptron (MLP) and Convolutional Neural Network (CNN), which are capable of achieving upwards of 92.34 % classification accuracy

Developing a person guidance module for hospital robots

This dissertation describes the design and implementation of the Person Guidance Module (PGM) that enables the IWARD (Intelligent Robot Swarm for attendance, Recognition, Cleaning and delivery) base robot to offer route guidance service to the patients or visitors inside the hospital arena. One of the common problems encountered in huge hospital buildings today is foreigners not being able to find their way around in the hospital. Although there are a variety of guide robots currently existing on the market and offering a wide range of guidance and related activities, they do not fit into the modular concept of the IWARD project. The PGM features a robust and foolproof non-hierarchical sensor fusion approach of an active RFID, stereovision and cricket mote sensor for guiding a patient to the X-ray room, or a visitor to a patient’s ward in every possible scenario in a complex, dynamic and crowded hospital environment. Moreover, the speed of the robot can be adjusted automatically according to the pace of the follower for physical comfort using this system. Furthermore, the module performs these tasks in any unconstructed environment solely from a robot’s onboard perceptual resources in order to limit the hardware installation costs and therefore the indoor setting support. Similar comprehensive solution in one single platform has remained elusive in existing literature. The finished module can be connected to any IWARD base robot using quick-change mechanical connections and standard electrical connections. The PGM module box is equipped with a Gumstix embedded computer for all module computing which is powered up automatically once the module box is inserted into the robot. In line with the general software architecture of the IWARD project, all software modules are developed as Orca2 components and cross-complied for Gumstix’s XScale processor. To support standardized communication between different software components, Internet Communications Engine (Ice) has been used as middleware. Additionally, plug-and-play capabilities have been developed and incorporated so that swarm system is aware at all times of which robot is equipped with PGM. Finally, in several field trials in hospital environments, the person guidance module has shown its suitability for a challenging real-world application as well as the necessary user acceptance

New Approach of Indoor and Outdoor Localization Systems

Accurate determination of the mobile position constitutes the basis of many new applications. This book provides a detailed account of wireless systems for positioning, signal processing, radio localization techniques (Time Difference Of Arrival), performances evaluation, and localization applications. The first section is dedicated to Satellite systems for positioning like GPS, GNSS. The second section addresses the localization applications using the wireless sensor networks. Some techniques are introduced for localization systems, especially for indoor positioning, such as Ultra Wide Band (UWB), WIFI. The last section is dedicated to Coupled GPS and other sensors. Some results of simulations, implementation and tests are given to help readers grasp the presented techniques. This is an ideal book for students, PhD students, academics and engineers in the field of Communication, localization & Signal Processing, especially in indoor and outdoor localization domains

Machine Learning Techniques for Device-Free Indoor Person Tracking

L'abstract è presente nell'allegato / the abstract is in the attachmen

Human tracking using electric fields

Abstract—In this paper we describe a simple, cheap, and unobtrusive demo system that can track multiple persons with low-frequency electric fields. The system’s operation is based on measuring the capacitance between multiple floor tiles and a receiving electrode. The presented system is invisible to the user and uses a single-chip solution to measure the capacitances. The system was provided for hands-on evaluation for conference attendees with a 3.0 x 1.8 m floor space. The position and the track of the persons walking on the floor were projected on a screen. The floor of the demo system is divided to two different sections that are built of two different sizes of floor tiles to show how the tile size affects the positioning accuracy and the update rate of the system. Pervasive positioning, pervasive tracking, human tracking, ubiquitous location systems, electric fields I