Integration of body sensor networks and vehicular ad-hoc networks for traffic safety

The emergence of Body Sensor Networks (BSNs) constitutes a new and fast growing trend for the development of daily routine applications. However, in the case of heterogeneous BSNs integration with Vehicular ad hoc Networks (VANETs) a large number of difficulties remain, that must be solved, especially when talking about the detection of human state factors that impair the driving of motor vehicles. The main contributions of this investigation are principally three: (1) an exhaustive review of the current mechanisms to detect four basic physiological behavior states (drowsy, drunk, driving under emotional state disorders and distracted driving) that may cause traffic accidents is presented; (2) A middleware architecture is proposed. This architecture can communicate with the car dashboard, emergency services, vehicles belonging to the VANET and road or street facilities. This architecture seeks on the one hand to improve the car driving experience of the driver and on the other hand to extend security mechanisms for the surrounding individuals; and (3) as a proof of concept, an Android real-time attention low level detection application that runs in a next-generation smartphone is developed. The application features mechanisms that allow one to measure the degree of attention of a driver on the base of her/his EEG signals, establish wireless communication links via various standard wireless means, GPRS, Bluetooth and WiFi and issue alarms of critical low driver attention levels.Peer ReviewedPostprint (author's final draft

A MAC protocol for quality of service provisioning in adaptive biomedical wireless sensor networks

Doctorate program on Electronics and Computer EngineeringNew healthcare solutions are being explored to improve the quality of care and the quality of life of patients, as well as the sustainability and efficiency of the healthcare services. In this context, wireless sensor networks (WSNs) constitute a key technology for closing the loop between patients and healthcare providers, as WSNs provide sensing ability, as well as mobility and portability, essential characteristics for wide acceptance of wireless healthcare technology. Despite the recent advances in the field, the wide adoption of healthcare WSNs is still conditioned by quality of service (QoS) issues, namely at the medium access control (MAC) level. MAC protocols currently available for WSNs are not able to provide the required QoS to healthcare applications in scenarios of medical emergency or intensive medical care. To cover this shortage, the present work introduces a MAC protocol with novel concepts to assure the required QoS regarding the data transmission robustness, packet delivery deadline, bandwidth efficiency, and energy preservation. The proposed MAC protocol provides a new and efficient dynamic reconfiguration mechanism, so that relevant operational parameters may be redefined dynamically in accordance with the patients’ clinical state. The protocol also provides a channel switching mechanism and the capacity of forwarding frames in two-tier network structures. To test the performance of the proposed MAC protocol and compare it with other MAC protocols, a simulation platform was implemented. In order to validate the simulation results, a physical testbed was implemented to replicate the tests and verify the results. Sensor nodes were specifically designed and assembled to implement this physical testbed. New healthcare solutions are being explored to improve the quality of care and the quality of life of patients, as well as the sustainability and efficiency of the healthcare services. In this context, wireless sensor networks (WSNs) constitute a key technology for closing the loop between patients and healthcare providers, as WSNs provide sensing ability, as well as mobility and portability, essential characteristics for wide acceptance of wireless healthcare technology. Despite the recent advances in the field, the wide adoption of healthcare WSNs is still conditioned by quality of service (QoS) issues, namely at the medium access control (MAC) level. MAC protocols currently available for WSNs are not able to provide the required QoS to healthcare applications in scenarios of medical emergency or intensive medical care. To cover this shortage, the present work introduces a MAC protocol with novel concepts to assure the required QoS regarding the data transmission robustness, packet delivery deadline, bandwidth efficiency, and energy preservation. The proposed MAC protocol provides a new and efficient dynamic reconfiguration mechanism, so that relevant operational parameters may be redefined dynamically in accordance with the patients’ clinical state. The protocol also provides a channel switching mechanism and the capacity of forwarding frames in two-tier network structures. To test the performance of the proposed MAC protocol and compare it with other MAC protocols, a simulation platform was implemented. In order to validate the simulation results, a physical testbed was implemented to replicate the tests and verify the results. Sensor nodes were specifically designed and assembled to implement this physical testbed. Preliminary tests using the simulation and physical platforms showed that simulation results diverge significantly from reality, if the performance of the WSN software components is not considered. Therefore, a parametric model was developed to reflect the impact of this aspect on a physical WSN. Simulation tests using the parametric model revealed that the results match satisfactorily those obtained in reality. After validating the simulation platform, comparative tests against IEEE 802.15.4, a prominent standard used in many wireless healthcare systems, showed that the proposed MAC protocol leads to a performance increase regarding diverse QoS metrics, such as packet loss and bandwidth efficiency, as well as scalability, adaptability, and power consumption. In this way, AR-MAC is a valuable contribution to the deployment of wireless e-health technology and related applications.Novas soluções de cuidados de saúde estão a ser exploradas para melhorar a qualidade de tratamento e a qualidade de vida dos pacientes, assim como a sustentabilidade e eficiência dos serviços de cuidado de saúde. Neste contexto, as redes de sensores sem fios (wireless sensor networks - WSN) são uma tecnologia chave para fecharem o ciclo entre os pacientes e os prestadores de cuidados de saúde, uma vez que as WSNs proporcionam não só capacidade sensorial mas também mobilidade e portabilidade, caracteristicas essenciais para a aceitação à larga escala da tecnologia dos cuidados de saúde sem fios. Apesar dos avanços recentes na área, a aceitação genérica das WSNs de cuidados de saúde ainda está condicionada por aspectos relacionados com a qualidade de serviço (quality of service - QoS), nomeadamente ao nível do controlo de acesso ao meio (medium access control - MAC). Os protocolos MAC actualmente disponíveis para WSNs são incapazes de fornecer a QoS desejada pelas aplicações médicas em cenários de emergência ou cuidados médicos intensivos. Para suprimir esta carência, o presente trabalho apresenta um protocolo MAC com novos conceitos a fim de assegurar a QoS respeitante à robustez de transmissão de dados, ao limite temporal da entrega de pacotes, à utilização da largura de banda e à preservação da energia eléctrica. O protocolo MAC proposto dispõe de um novo e eficiente mecanismo de reconfiguração para que os parâmetros operacionais relevantes possam ser redefinidos dinamicamente de acordo com o estado de saúde do paciente. O protocolo também oferece um mecanismo autónomo de comutação de canal, bem como a capacidade de encaminhar pacotes em redes de duas camadas. Para testar o desempenho do protocolo MAC proposto e compará-lo com outros protocolos MAC foi implementada uma plataforma de simulação. A fim de validar os resultados da simulação foi também implementada uma plataforma física para permitir replicar os testes e verificar os resultados. Esta plataforma física inclui nós sensoriais concebidos e construídos de raiz para o efeito. Testes preliminares usando as plataformas de simulação e física mostraram que os resultados de simulação divergem significativamente da realidade, caso o desempenho dos componentes do software presentes nos componentes da WSN não seja considerado. Por conseguinte, desenvolveu-se um modelo paramétrico para reflectir o impacto deste aspecto numa WSN real. Testes de simulação efectuados com o modelo paramétrico apresentaram resultados muito satisfatórios quando comparados com os obtidos na realidade. Uma vez validada a plataforma de simulação, efectuaram-se testes comparativos com a norma IEEE 802.15.4, proeminentemente usada em projectos académicos de cuidados de saúde sem fios. Os resultados mostraram que o protocolo MAC conduz a um desempenho superior no tocante a diversas métricas QoS, tais como perdas de pacotes e utilização de largura de banda, bem como no respeitante à escalabilidade, adaptabilidade e consumo de energia eléctrica. Assim sendo, o protocolo MAC proposto representa um valioso contributo para a concretização efectiva dos cuidados de saúde sem fios e suas aplicações

Sensor Networks in the Low Lands

This paper provides an overview of scientific and industrial developments of the last decade in the area of sensor networks in The Netherlands (Low Lands). The goal is to highlight areas in which the Netherlands has made most contributions and is currently a dominant player in the field of sensor networks. On the one hand, motivations, addressed topics, and initiatives taken in this period are presented, while on the other hand, special emphasis is given to identifying current and future trends and formulating a vision for the coming five to ten years. The presented overview and trend analysis clearly show that Dutch research and industrial efforts, in line with recent worldwide developments in the field of sensor technology, present a clear shift from sensor node platforms, operating systems, communication, networking, and data management aspects of the sensor networks to reasoning/cognition, control, and actuation

Evolutionary Game Theoretic Multi-Objective Optimization Algorithms and Their Applications

Multi-objective optimization problems require more than one objective functions to be optimized simultaneously. They are widely applied in many science fields, including engineering, economics and logistics where optimal decisions need to be taken in the presence of trade-offs between two or more conicting objectives. Most of the real world multi-objective optimization problems are NP-Hard problems. It may be too computationally costly to find an exact solution but sometimes a near optimal solution is sufficient. In these cases, Multi-Objective Evolutionary Algorithms (MOEAs) provide good approximate solutions to problems that cannot be solved easily using other techniques. However Evolutionary Algorithm is not stable due to its random nature, it may produce very different results every time it runs. This dissertation proposes an Evolutionary Game Theory (EGT) framework based algorithm (EGTMOA) that provides optimality and stability at the same time. EGTMOA combines the notion of stability from EGT and optimality from MOEA to form a novel and promising algorithm to solve multi-objective optimization problems. This dissertation studies three different multi-objective optimization applications, Cloud Virtual Machine Placement, Body Sensor Networks, and Multi-Hub Molecular Communication along with their proposed EGTMOA framework based algorithms. Experiment results show that EGTMOAs outperform many well known multi-objective evolutionary algorithms in stability, performance and runtime

A pervasive body sensor network for monitoring post-operative recovery

Over the past decade, miniaturisation and cost reduction brought about by the semiconductor industry has led to computers smaller in size than a pin head, powerful enough to carry out the processing required, and affordable enough to be disposable. Similar technological advances in wireless communication, sensor design, and energy storage have resulted in the development of wireless “Body Sensor Network (BSN) platforms comprising of tiny integrated micro sensors with onboard processing and wireless data transfer capability, offering the prospect of pervasive and continuous home health monitoring. In surgery, the reduced trauma of minimally invasive interventions combined with initiatives to reduce length of hospital stay and a socioeconomic drive to reduce hospitalisation costs, have all resulted in a trend towards earlier discharge from hospital. There is now a real need for objective, pervasive, and continuous post-operative home recovery monitoring systems. Surgical recovery is a multi-faceted and dynamic process involving biological, physiological, functional, and psychological components. Functional recovery (physical independence, activities of daily living, and mobility) is recognised as a good global indicator of a patient’s post-operative course, but has traditionally been difficult to objectively quantify. This thesis outlines the development of a pervasive wireless BSN system to objectively monitor the functional recovery of post-operative patients at home. Biomechanical markers were identified as surrogate measures for activities of daily living and mobility impairment, and an ear-worn activity recognition (e-AR) sensor containing a three-axis accelerometer and a pulse oximeter was used to collect this data. A simulated home environment was created to test a Bayesian classifier framework with multivariate Gaussians to model activity classes. A real-time activity index was used to provide information on the intensity of activity being performed. Mobility impairment was simulated with bracing systems and a multiresolution wavelet analysis and margin-based feature selection framework was used to detect impaired mobility. The e-AR sensor was tested in a home environment before its clinical use in monitoring post-operative home recovery of real patients who have undergone surgery. Such a system may eventually form part of an objective pervasive home recovery monitoring system tailored to the needs of today’s post-operative patient.Open acces

Olivet Nazarene University Annual Catalog 2010-2011

https://digitalcommons.olivet.edu/acaff_catalog/1083/thumbnail.jp

Olivet Nazarene University Annual Catalog 2010-2011

https://digitalcommons.olivet.edu/acaff_catalog/1083/thumbnail.jp

Identifying The Usage Anomalies For ECG-Based Healthcare Body Sensor Networks

This thesis is looking into the dependability of a Electrocardiogram(ECG) based Healthcare Body Sensor Network system (HC-BSNs). For these type of devices, the dependability is not only depending on the devices themselves, but also heavily depending on how the devices are used. Existing literature has identified that there are around 4% of usage issues when existing ECG devices are used by professionals. The rate of usage issue will not be better for the ECG-Based HC-BSNs as these devices are more likely to be used by untrained people. Subsequently, it is with paramount importance to address the usage issues so that the overall dependability of the ECG-Based HC-BSNs can be assured. Our approach to address the usage issue is to detect the usage-related anomaly, which is contained in the captured signal when erroneous usage is made, and identify the cause to the usage-related anomaly automatically and without human intervention. By doing this, the user can be prompted with clearer and accurate correction instruction. Subsequently, the usage issues can be well corrected by the user. Based on the above concept, in this thesis, we have studied the anomalous signals which can be caused by the usage issues. Two methodologies, names as AID and FFNAID, have been proposed and evaluated to detect the usage-related anomalies. We have also studied how each usage issue can affect the signals on a mote, and we use the knowledge learnt from the study to propose a methodology, named as ACLP, to identify the root cause to the usage-related anomaly. All these methodologies are fully automated and does not require any human intervention once they are deployed. The evaluations have also shown the effectiveness of these methodologies