10 research outputs found
Security Analysis of Wireless BAN in e-Health
The Wireless Body Area Network (WBAN) has gained popularity as a new technology for e-Health, and is considered as one of the key research areas in computer science and healthcare applications. WBAN collects patients’ data, monitors constantly their physiological parameters, using small implantable or wearable sensors, and communicates these data using wireless communication techniques in short range. WBAN is playing a huge role in improving the quality of healthcare. Still, due to sensitive and concurrent nature of e-Heath systems, current research has showed that designers must take into considerations the security and privacy protection of the data collected by a WBAN to safeguard patients from different exploits or malicious attacks, since e-Health technologies are increasingly connected to the Internet via wireless communications. In this paper we outline the most important security requirements for WBANs. Furthermore, we discuss key security threats to avoid. Finally, we conclude with a summary of security mechanisms to follow that address security and privacy concerns of WBANs, and need to be explored in an increasingly connected healthcare world
Security Analysis of Wireless BAN in e-Health
The Wireless Body Area Network (WBAN) has gained popularity as a new technology for e-Health, and is considered as one of the key research areas in computer science and healthcare applications. WBAN collects patients’ data, monitors constantly their physiological parameters, using small implantable or wearable sensors, and communicates these data using wireless communication techniques in short range. WBAN is playing a huge role in improving the quality of healthcare. Still, due to sensitive and concurrent nature of e-Heath systems, current research has showed that designers must take into considerations the security and privacy protection of the data collected by a WBAN to safeguard patients from different exploits or malicious attacks, since e-Health technologies are increasingly connected to the Internet via wireless communications. In this paper we outline the most important security requirements for WBANs. Furthermore, we discuss key security threats to avoid. Finally, we conclude with a summary of security mechanisms to follow that address security and privacy concerns of WBANs, and need to be explored in an increasingly connected healthcare world
Challenges in Blood Pressure Self-Measurement
Blood pressure self-measurement (BPSM) requires patients to follow a range of recommendations in order to be considered reliable for diagnostic use. We investigated currently used BPSM interventions at four medical clinics combined with an online questionnaire targeting BPSM users. We found that the participating healthcare personnel perceived BPSM as a relevant and useful intervention method providing that the recommendations are followed. A total of six challenges were identified: (1) existing devices do not guarantee that the recommendations are followed, (2) healthcare providers cannot verify whether self-monitoring patients follow the recommendations, (3) patients are not aware of all recommendations and the need to follow them, (4) risk of patient induced reporting bias, (5) risk of healthcare provider induced data-transfer bias, and (6) risk of data being registered as belonging to the wrong patient. We conclude that existing BPSM interventions could be significantly affected by user-induced bias resulting in an indeterminable quality of the measurement data. Therefore, we suggest applying context-aware technological support tools to better detect and quantify user errors. This may allow us to develop solutions that could overcome or compensate for such errors in the future
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Cloud-assisted body area networks: state-of-the-art and future challenges
Body area networks (BANs) are emerging as enabling technology for many human-centered application domains such as health-care, sport, fitness, wellness, ergonomics, emergency, safety, security, and sociality. A BAN, which basically consists of wireless wearable sensor nodes usually coordinated by a static or mobile device, is mainly exploited to monitor single assisted livings. Data generated by a BAN can be processed in real-time by the BAN coordinator and/or transmitted to a server-side for online/offline processing and long-term storing. A network of BANs worn by a community of people produces large amount of contextual data that require a scalable and efficient approach for elaboration and storage. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of body sensor data streams. In this paper, we motivate the introduction of Cloud-assisted BANs along with the main challenges that need to be addressed for their development and management. The current state-of-the-art is overviewed and framed according to the main requirements for effective Cloud-assisted BAN architectures. Finally, relevant open research issues in terms of efficiency, scalability, security, interoperability, prototyping, dynamic deployment and management, are discussed
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BodyCloud: a SaaS approach for community body sensor networks
Body Sensor Networks (BSNs) have been recently introduced for the remote monitoring of human activities in a broad range of application domains, such as health care, emergency management, fitness and behaviour surveillance. BSNs can be deployed in a community of people and can generate large amounts of contextual data that require a scalable approach for storage, processing and analysis. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of data streams generated in BSNs. This paper proposes BodyCloud, a SaaS approach for community BSNs that supports the development and deployment of Cloud-assisted BSN applications. BodyCloud is a multi-tier application-level architecture that integrates a Cloud computing platform and BSN data streams middleware. BodyCloud provides programming abstractions that allow the rapid development of community BSN applications. This work describes the general architecture of the proposed approach and presents a case study for the real-time monitoring and analysis of cardiac data streams of many individuals
Virtual Platform-Based Design Space Exploration of Power-Efficient Distributed Embedded Applications
Networked embedded systems are essential building blocks of a broad variety of distributed applications ranging from agriculture to industrial automation to healthcare and more. These often require specific energy optimizations to increase the battery lifetime or to operate using energy harvested from the environment. Since a dominant portion of power consumption is determined and managed by software, the software development process must have access to the sophisticated power management mechanisms provided by state-of-the-art hardware platforms to achieve the best tradeoff between system availability and reactivity. Furthermore, internode communications must be considered to properly assess the energy consumption.
This article describes a design flow based on a SystemC virtual platform including both accurate power models of the hardware components and a fast abstract model of the wireless network. The platform allows both model-driven design of the application and the exploration of power and network management alternatives. These can be evaluated in different network scenarios, allowing one to exploit power optimization strategies without requiring expensive field trials. The effectiveness of the approach is demonstrated via experiments on a wireless body area network application
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Enabling the Virtual Phones to remotely sense the Real Phones in real-time: A Sensor Emulation initiative for virtualized Android-x86
Smartphones nowadays have the ground-breaking features that were only a figment of one’s imagination. For the ever-demanding cellphone users, the exhaustive list of features that a smartphone supports just keeps getting more exhaustive with time. These features aid one’s personal and professional uses as well. Extrapolating into the future the features of a present-day smartphone, the lives of us humans using smartphones are going to be unimaginably agile. With the above said emphasis on the current and future potential of a smartphone, the ability to virtualize smartphones with all their real-world features into a virtual platform, is a boon for those who want to rigorously experiment and customize the virtualized smartphone hardware without spending an extra penny. Once virtualizable independently on a larger scale, the idea of virtualized smartphones with all the virtualized pieces of hardware takes an interesting turn with the sensors being virtualized in a way that’s closer to the real-world behavior. When accessible remotely with the real-time responsiveness, the above mentioned real-world behavior will be a real dealmaker in many real-world systems, namely, the life-saving systems like the ones that instantaneously get alerts about harmful magnetic radiations in the deep mining areas, etc. And these life-saving systems would be installed on a large scale on the desktops or large servers as virtualized smartphones having the added support of virtualized sensors which remotely fetch the real hardware sensor readings from a real smartphone in real-time. Based on these readings the lives working in the affected areas can be alerted and thus saved by the people who are operating the at the desktops or large servers hosting the virtualized smartphones
Hybrid approaches based on computational intelligence and semantic web for distributed situation and context awareness
2011 - 2012The research work focuses on Situation Awareness and Context Awareness topics.
Specifically, Situation Awareness involves being aware of what is happening in the vicinity
to understand how information, events, and one’s own actions will impact goals and objectives,
both immediately and in the near future. Thus, Situation Awareness is especially
important in application domains where the information flow can be quite high and poor
decisions making may lead to serious consequences.
On the other hand Context Awareness is considered a process to support user applications
to adapt interfaces, tailor the set of application-relevant data, increase the precision of
information retrieval, discover services, make the user interaction implicit, or build smart
environments.
Despite being slightly different, Situation and Context Awareness involve common
problems such as: the lack of a support for the acquisition and aggregation of dynamic environmental
information from the field (i.e. sensors, cameras, etc.); the lack of formal approaches
to knowledge representation (i.e. contexts, concepts, relations, situations, etc.)
and processing (reasoning, classification, retrieval, discovery, etc.); the lack of automated
and distributed systems, with considerable computing power, to support the reasoning on a
huge quantity of knowledge, extracted by sensor data.
So, the thesis researches new approaches for distributed Context and Situation Awareness
and proposes to apply them in order to achieve some related research objectives such
as knowledge representation, semantic reasoning, pattern recognition and information retrieval.
The research work starts from the study and analysis of state of art in terms of
techniques, technologies, tools and systems to support Context/Situation Awareness. The
main aim is to develop a new contribution in this field by integrating techniques deriving
from the fields of Semantic Web, Soft Computing and Computational Intelligence. From
an architectural point of view, several frameworks are going to be defined according to the
multi-agent paradigm.
Furthermore, some preliminary experimental results have been obtained in some application
domains such as Airport Security, Traffic Management, Smart Grids and
Healthcare.
Finally, future challenges is going to the following directions: Semantic Modeling of
Fuzzy Control, Temporal Issues, Automatically Ontology Elicitation, Extension to other
Application Domains and More Experiments. [edited by author]XI n.s
Event-driven Middleware for Body and Ambient Sensor Applications
Continuing development of on-body and ambient sensors has led to a vast increase in sensor-based assistance and monitoring solutions. A growing range of modular sensors, and the necessity of running multiple applications on the sensor information, has led to an equally extensive increase in efforts for system development. In this work, we present an event-driven middleware for on-body and ambient sensor networks allowing multiple applications to define information types of their interest in a publish/subscribe manner. Incoming sensor data is hereby transformed into the required data representation which lifts the burden of adapting the application with respect to the connected sensors off the developer's shoulders. Furthermore, an unsupervised on-the-fly reloading of transformation rules from a remote server allows the system's adaptation to future applications and sensors at run-time as well as reducing the number of connected sensors. Open communication channels distribute sensor information to all interested applications. In addition to that, application-specific event channels are introduced that provide tailor-made information retrieval as well as control over the dissemination of critical information.
The system is evaluated based on an Android implementation with transformation rules implemented as OSGi bundles that are retrieved from a remote web server. Evaluation shows a low impact of running the middleware and the transformation rules on a phone and highlights the reduced energy consumption by having fewer sensors serving multiple applications. It also points out the behavior and limits of the open and application-specific event channels with respect to CPU utilization, delivery ratio, and memory usage.
In addition to the middleware approach, four (preventive) health care applications are presented. They take advantage of the mediation between sensors and applications and highlight the system's capabilities. By connecting body sensors for monitoring physical and physiological parameters as well as ambient sensors for retrieving information about user presence and interactions with the environment, full-fledged health monitoring examples for monitoring a user throughout the day are presented. Vital parameters are gathered from commercially available biosensors and the mediator device running both the middleware and the application is an off-the-shelf smart phone. For gaining information about a user's physical activity, custom-built body and ambient sensors are presented and deployed