Internet of Things (IoT) for Automated and Smart Applications

Internet of Things (IoT) is a recent technology paradigm that creates a global network of machines and devices that are capable of communicating with each other. Security cameras, sensors, vehicles, buildings, and software are examples of devices that can exchange data between each other. IoT is recognized as one of the most important areas of future technologies and is gaining vast recognition in a wide range of applications and fields related to smart homes and cities, military, education, hospitals, homeland security systems, transportation and autonomous connected cars, agriculture, intelligent shopping systems, and other modern technologies. This book explores the most important IoT automated and smart applications to help the reader understand the principle of using IoT in such applications

Algorithms design for improving homecare using Electrocardiogram (ECG) signals and Internet of Things (IoT)

Due to the fast growing of population, a lot of hospitals get crowded from the huge amount of patients visits. Moreover, during COVID-19 a lot of patients prefer staying at home to minimize the spread of the virus. The need for providing care to patients at home is essential. Internet of Things (IoT) is widely known and used by different fields. IoT based homecare will help in reducing the burden upon hospitals. IoT with homecare bring up several benefits such as minimizing human exertions, economical savings and improved efficiency and effectiveness. One of the important requirement on homecare system is the accuracy because those systems are dealing with human health which is sensitive and need high amount of accuracy. Moreover, those systems deal with huge amount of data due to the continues sensing that need to be processed well to provide fast response regarding the diagnosis with minimum cost requirements. Heart is one of the most important organ in the human body that requires high level of caring. Monitoring heart status can diagnose disease from the early stage and find the best medication plan by health experts. Continues monitoring and diagnosis of heart could exhaust caregivers efforts. Having an IoT heart monitoring model at home is the solution to this problem. Electrocardiogram (ECG) signals are used to track heart condition using waves and peaks. Accurate and efficient IoT ECG monitoring at home can detect heart diseases and save human lives. As a consequence, an IoT ECG homecare monitoring model is designed in this thesis for detecting Cardiac Arrhythmia and diagnosing heart diseases. Two databases of ECG signals are used; one online which is old and limited, and another huge, unique and special from real patients in hospital. The raw ECG signal for each patient is passed through the implemented Low Pass filter and Savitzky Golay filter signal processing techniques to remove the noise and any external interference. The clear signal in this model is passed through feature extraction stage to extract number of features based on some metrics and medical information along with feature extraction algorithm to find peaks and waves. Those features are saved in the local database to apply classification on them. For the diagnosis purpose a classification stage is made using three classification ways; threshold values, machine learning and deep learning to increase the accuracy. Threshold values classification technique worked based on medical values and boarder lines. In case any feature goes above or beyond these ranges, a warning message appeared with expected heart disease. The second type of classification is by using machine learning to minimize the human efforts. A Support Vector Machine (SVM) algorithm is proposed by running the algorithm on the features extracted from both databases. The classification accuracy for online and hospital databases was 91.67% and 94% respectively. Due to the non-linearity of the decision boundary, a third way of classification using deep learning is presented. A full Multilayer Perceptron (MLP) Neural Network is implemented to improve the accuracy and reduce the errors. The number of errors reduced to 0.019 and 0.006 using online and hospital databases. While using hospital database which is huge, there is a need for a technique to reduce the amount of data. Furthermore, a novel adaptive amplitude threshold compression algorithm is proposed. This algorithm is able to make diagnosis of heart disease from the reduced size using compressed ECG signals with high level of accuracy and low cost. The extracted features from compressed and original are similar with only slight differences of 1%, 2% and 3% with no effects on machine learning and deep learning classification accuracy without the need for any reconstructions. The throughput is improved by 43% with reduced storage space of 57% when using data compression. Moreover, to achieve fast response, the amount of data should be reduced further to provide fast data transmission. A compressive sensing based cardiac homecare system is presented. It gives the channel between sender and receiver the ability to carry small amount of data. Experiment results reveal that the proposed models are more accurate in the classification of Cardiac Arrhythmia and in the diagnosis of heart diseases. The proposed models ensure fast diagnosis and minimum cost requirements. Based on the experiments on classification accuracy, number of errors and false alarms, the dictionary of the compressive sensing selected to be 900. As a result, this thesis provided three different scenarios that achieved IoT homecare Cardiac monitoring to assist in further research for designing homecare Cardiac monitoring systems. The experiment results reveal that those scenarios produced better results with high level of accuracy in addition to minimizing data and cost requirements

Smart home technology for aging

The majority of the growing population, in the US and the rest of the world requires some degree of formal and or informal care either due to the loss of function or failing health as a result of aging and most of them suffer from chronic disorders. The cost and burden of caring for elders is steadily increasing. This thesis focuses on providing the analysis of the technologies with which a Smart Home is built to improve the quality of life of the elderly. A great deal of emphasis is given to the sensor technologies that are the back bone of these Smart Homes. In addition to the Analysis of these technologies a survey of commercial sensor products and products in research that are concerned with monitoring the health of the occupants of the Smart Home is presented. A brief analysis on the communication technologies which form the communication infrastructure for the Smart Home is also illustrated. Finally, System Architecture for the Smart Home is proposed describing the functionality and users of the system. The feasibility of the system is also discussed. A scenario measuring the blood glucose level of the occupant in a Smart Home is presented as to support the system architecture presented

Telemedicine

Telemedicine is a rapidly evolving field as new technologies are implemented for example for the development of wireless sensors, quality data transmission. Using the Internet applications such as counseling, clinical consultation support and home care monitoring and management are more and more realized, which improves access to high level medical care in underserved areas. The 23 chapters of this book present manifold examples of telemedicine treating both theoretical and practical foundations and application scenarios

Distributed Computing and Monitoring Technologies for Older Patients

This book summarizes various approaches for the automatic detection of health threats to older patients at home living alone. The text begins by briefly describing those who would most benefit from healthcare supervision. The book then summarizes possible scenarios for monitoring an older patient at home, deriving the common functional requirements for monitoring technology. Next, the work identifies the state of the art of technological monitoring approaches that are practically applicable to geriatric patients. A survey is presented on a range of such interdisciplinary fields as smart homes, telemonitoring, ambient intelligence, ambient assisted living, gerontechnology, and aging-in-place technology. The book discusses relevant experimental studies, highlighting the application of sensor fusion, signal processing and machine learning techniques. Finally, the text discusses future challenges, offering a number of suggestions for further research directions

A Mobile ECG Monitoring System with Context Collection

An objective of a health process is one where patients can stay healthy with the support of expert medical advice when they need it, at any location and any time. An associated aim would be the development of a system which places increased emphasis on preventative measures as a first point of contact with the patient. This research is a step along the road towards this type of preventative healthcare for cardiac patients. It seeks to develop a smart mobile ECG monitoring system that requests and records context information about what is happening around the subject when an arrhythmia event occurs. Context information about the subject’s activities of daily living will, it is hoped, provide an enriched data set for clinicians and so improve clinical decision making. As a first step towards a mobile cardiac wellness guidelines system, the focus of this work is to develop a system that can receive bio-signals wirelessly, analyzing and storing the bio-signal in a handheld device and can collect context information when there are significant changes in bio-signs. For this purpose the author will use a low cost development environment to program a state of the art wireless prototype on a handheld computer that detects and responds to changes in the heart rate as calculated form the interval between successive heart beats. Although the general approach take in this work could be applied to a wide range of bio-signals, the research will focus on ECG signals. The pieces of the system are, A wireless receiver, data collection and storage module An efficient real time ECG beat detection algorithm A rule based (Event-Condition-Action) interactive system A simple user interface, which can request additional information form the user. A selection of real-time ECG detection algorithms have been investigated and one algorithm was implemented in MATLAB [110] and then in Java [142] for this project. In order to collect ECG signals (and in principle any signals) the generalised data collection architecture has also been developed utilizing Java [142] and Bluetooth [5] technology. This architecture uses an implementation of the abstract factory pattern [91] to ensure that the communication channel can be changed conveniently. Another core part of this project is a “wellness” guideline based on Event-Condition-Action (E-C-A) [68] production rule approach that originated in active databases. The work also focuses on design of a guideline based expert system which an E-C-A based implementation will be fully event driven using the Java programming language. Based on the author’s experience and the literature review, some important issues in mobile healthcare along with the corresponding reasons, consequences and possible solutions will be presented

Ageing and Technology: Perspectives from the Social Sciences

The booming increase of the senior population has become a social phenomenon and a challenge to our societies, and technological advances have undoubtedly contributed to improve the lives of elderly citizens in numerous aspects. In current debates on technology, however, the "human factor" is often largely ignored. The ageing individual is rather seen as a malfunctioning machine whose deficiencies must be diagnosed or as a set of limitations to be overcome by means of technological devices. This volume aims at focusing on the perspective of human beings deriving from the development and use of technology: this change of perspective - taking the human being and not technology first - may help us to become more sensitive to the ambivalences involved in the interaction between humans and technology, as well as to adapt technologies to the people that created the need for its existence, thus contributing to improve the quality of life of senior citizens

Ageing and Technology

The booming increase of the senior population has become a social phenomenon and a challenge to our societies, and technological advances have undoubtedly contributed to improve the lives of elderly citizens in numerous aspects. In current debates on technology, however, the »human factor« is often largely ignored. The ageing individual is rather seen as a malfunctioning machine whose deficiencies must be diagnosed or as a set of limitations to be overcome by means of technological devices. This volume aims at focusing on the perspective of human beings deriving from the development and use of technology: this change of perspective – taking the human being and not technology first – may help us to become more sensitive to the ambivalences involved in the interaction between humans and technology, as well as to adapt technologies to the people that created the need for its existence, thus contributing to improve the quality of life of senior citizens