Applications of sensors for in-home elder support

The number of retirees in the US is continuously increasing in proportion to the total population as the baby-boomers in the United States age. As these retirees age they are in need on continuous medical treatment and care which impacts the percent of the national budget placed on healthcare. As healthcare issues with the retirees they are often moved by their family members to assisted living facilities or to nursing homes. This movement is costly to both the family members and to the government agencies paying for or subsidizing their care. The proposal brought forth in this thesis is to design a sensor based system that should reduce the need for personnel and enhance elder\u27s quality of life by affording them more independence allowing them to live at home longer; The purpose of this thesis is the evaluation of different sensor types with regard to benefits, specificity of sensor signal to the function being monitored, drawbacks, reliability, acceptance levels by elders, privacy concerns. The design concepts for sensor assembly\u27s configurations under the special set of criteria that must be applied in the homes of elders, information of reliability studies: signal threshold levels, resolution of potential conflicts or false positives. Finally an inference engine R&D: Drawing inferences and conclusions from signals and temporal sequences, correlation with other signals, signal validation and plausibility analysis. (Abstract shortened by UMI.)

Evaluación de prestaciones de soluciones de seguridad en Internet de las Cosas en un entorno experimental

[SPA]Internet de las Cosas (Internet of Things, IoT) plantea dudas importantes e introduce nuevos retos en la privacidad de las personas y en la seguridad de los sistemas y de los procesos. Algunas aplicaciones de IoT están estrechamente vinculadas a infraestructuras sensibles y servicios estratégicos tales como la distribución de agua y electricidad. Otras aplicaciones manejan información sensible acerca de las personas, tales como su ubicación y sus desplazamientos, o sus preferencias de salud o de compra. La confianza y la aceptación de los servicios y sistemas creados sobre la base de IoT dependerán de la protección que ofrezca a la intimidad de las personas y a los niveles de seguridad que garantice a los sistemas y procesos. Del mismo modo, IoT permitirá a cualquier objeto convertirse en un participante activo: estos objetos serán capaces de reconocer los acontecimientos y los cambios en su entorno y detectar y reaccionar de forma autónoma, sin intervención humana. La introducción de objetos en los procesos de control hace que la seguridad en IoT sea difícil de abordar. De hecho, IoT es un sistema complejo en el que las personas interactúan con el ecosistema tecnológico basado en objetos inteligentes a través de procesos complejos. Las interacciones de estos cuatro componentes de IoT: personas, objetos inteligentes, ecosistema tecnológico y procesos resaltan una dimensión sistémica y cognitiva en la seguridad de IoT. La interacción de las personas con el ecosistema tecnológico requiere la protección de su privacidad. Del mismo modo, su interacción con los procesos de control requiere garantizar su seguridad ya que los procesos deben garantizar su fiabilidad y dirigirse hacia los objetivos para los que fueron diseñados. El objetivo de este Trabajo Fin de Master es el diseño, la implementación y el uso de un testbed para pruebas experimentales en el que medir las prestaciones de soluciones de seguridad para Internet de las Cosas.[ENG]Internet of Things (IoT) proposes important questions, introduces new challenges about people privacy and security in processes and systems. Some IoT applications are closely linked to critical structures and strategic services as or electricity water distribution. Other applications handle critical information about people, such as localization or movements, health or shop preferences. The confidence and acceptance of services and systems built over IoT will depend of the people’s intimacy and the security levels. IoT will let to any object become an active: these objects will recognize events and changes in the environment, detecting and responding autonomously, without human intervention. The object introduction in the control processes makes the IoT security difficult to approach. IoT is a complex system where individuals interact with technologic ecosystem based in intelligent objects through complex processes. There are four components that interact: people, intelligent objects, technologic ecosystem and processes that emphasize a systematic and cognitive dimension in IoT security. People interaction with technologic ecosystem requires privacy protection. In addition, the interaction with control processes requires guarantee the security because processes must ensure reliability and be focus to the goals that were designed. The main objective of this Final Master Thesis is the design, implementation and the use of testbed to experimental test and measure performance solutions about security for Internet of Things.Escuela Técnica Superior de Ingeniería de TelecomunicaciónUniversidad Politécnica de CartagenaUniversidad Politécnica de Cartagen

Simulation, modelling and packet sniffing facilities for IoT: A systematic analysis

Man and Machine in terms of heterogeneous devices and sensors collaborate giving birth to the Internet of Things, Internet of future. Within a short span of time 30billions intelligent devices in form of smart applications will get connected making it difficult to test and debug in terms of time and cost.Simulators play vital role in verifying application and providing security before actually deploying it in real environment.Due to constraint environment in terms of memory, computation, and energy this review paper under a single umbrella will throw insight on comprehensive and in-depth analysis keeping in mind various barriers, critical design characteristics along with the comparison of candidate simulator and packet sniffing tool. Post simulated analysis play vital role in deciding behavior of data and helping research community to satisfy quality of service parameters.This review makes it feasible to make an appropriate choice for simulators and network analyzer tool easy fulfilling needs and making IoT a realit

Developing a Wireless Sensor Network Programming Language Application Guide Using Memsic Devices and LabVIEW

The principal objective of this project is to develop a wireless sensor network (WSN) programming language application guide for junior and senior undergraduate students in College of Technology, Architecture and Applied Engineering in Bowling Green State University. Memsic device, MoteWorks and LabVIEW software are used to conduct experiments in developing WSN applications after both software and hardware platform are verified to be usable with experimental and statistical analysis. The guide is divided into six chapters including both theoretical knowledge and practical experiments in WSN area. Programs, both in nesC language and LabVIEW are improved from previous work, tested to run successfully and noted in detail

A heterogeneous network management approach to wireless sensor networks in personal healthcare environments

University of Technology, Sydney. Faculty of Science.Many countries are facing problems caused by a rapid surge in numbers of people over sixty-five. This aging population cohort will place a strain on the existing health systems because the elderly are prone to falls, chronic illnesses, dementia and general frailty. At the same time governments are struggling to attract more people into the health systems and there are already shortages of qualified nurses and care givers. This thesis represents a multi disciplinary approach to trying to solve some of the above issues. In the first instance the researcher has established the validity of the health crisis and then examined ways in which Information Technology could help to alleviate some of the issues. The nascent technology called Wireless Sensor Networks was examined as a way of providing remote health monitoring for the elderly, the infirm and the ill. The researcher postulated that Network Management models and tools that are used to monitor huge networks of computers could be adapted to monitor the health of persons in their own homes, in aged care facilities and hospitals. Wireless Sensor Network (WNS) Personal Healthcare can monitor such vital signs as a patient’s temperature, heart rate and blood oxygen level. WSNs (often referred to as Motes) use wireless transceivers that can do remote sensing. The researcher aimed to assist all stakeholders in the personal healthcare arena to use WSNs to improve monitoring. The researcher provided a solution architecture and framework for healthcare sensor monitoring systems, based on network management techniques. This architecture generalises to heterogeneous and autonomous data acquisition systems. Future directions from this research point towards new areas of knowledge from the development or creation of new technologies to support the exponential growth of ubiquitous, just-in-time WSN health informational services and applications such as the preventive and proactive personal care health management and services around it. The affordable and ubiquitous distributed access to remote personal health care technologies in the future could have an important impact in the society, by allowing the individuals to take immediate preventive actions over their overall health condition. These systems could potentially prevent death as well as improve national health budgets by limiting costly medical interventions that could have been avoided by individual, easy-action early prevention

A Self-organizing Hybrid Sensor System With Distributed Data Fusion For Intruder Tracking And Surveillance

A wireless sensor network is a network of distributed nodes each equipped with its own sensors, computational resources and transceivers. These sensors are designed to be able to sense specific phenomenon over a large geographic area and communicate this information to the user. Most sensor networks are designed to be stand-alone systems that can operate without user intervention for long periods of time. While the use of wireless sensor networks have been demonstrated in various military and commercial applications, their full potential has not been realized primarily due to the lack of efficient methods to self organize and cover the entire area of interest. Techniques currently available focus solely on homogeneous wireless sensor networks either in terms of static networks or mobile networks and suffers from device specific inadequacies such as lack of coverage, power and fault tolerance. Failing nodes result in coverage loss and breakage in communication connectivity and hence there is a pressing need for a fault tolerant system to allow replacing of the failed nodes. In this dissertation, a unique hybrid sensor network is demonstrated that includes a host of mobile sensor platforms. It is shown that the coverage area of the static sensor network can be improved by self-organizing the mobile sensor platforms to allow interaction with the static sensor nodes and thereby increase the coverage area. The performance of the hybrid sensor network is analyzed for a set of N mobile sensors to determine and optimize parameters such as the position of the mobile nodes for maximum coverage of the sensing area without loss of signal between the mobile sensors, static nodes and the central control station. A novel approach to tracking dynamic targets is also presented. Unlike other tracking methods that are based on computationally complex methods, the strategy adopted in this work is based on a computationally simple but effective technique of received signal strength indicator measurements. The algorithms developed in this dissertation are based on a number of reasonable assumptions that are easily verified in a densely distributed sensor network and require simple computations that efficiently tracks the target in the sensor field. False alarm rate, probability of detection and latency are computed and compared with other published techniques. The performance analysis of the tracking system is done on an experimental testbed and also through simulation and the improvement in accuracy over other methods is demonstrated

Security techniques for sensor systems and the Internet of Things

Sensor systems are becoming pervasive in many domains, and are recently being generalized by the Internet of Things (IoT). This wide deployment, however, presents significant security issues. We develop security techniques for sensor systems and IoT, addressing all security management phases. Prior to deployment, the nodes need to be hardened. We develop nesCheck, a novel approach that combines static analysis and dynamic checking to efficiently enforce memory safety on TinyOS applications. As security guarantees come at a cost, determining which resources to protect becomes important. Our solution, OptAll, leverages game-theoretic techniques to determine the optimal allocation of security resources in IoT networks, taking into account fixed and variable costs, criticality of different portions of the network, and risk metrics related to a specified security goal. Monitoring IoT devices and sensors during operation is necessary to detect incidents. We design Kalis, a knowledge-driven intrusion detection technique for IoT that does not target a single protocol or application, and adapts the detection strategy to the network features. As the scale of IoT makes the devices good targets for botnets, we design Heimdall, a whitelist-based anomaly detection technique for detecting and protecting against IoT-based denial of service attacks. Once our monitoring tools detect an attack, determining its actual cause is crucial to an effective reaction. We design a fine-grained analysis tool for sensor networks that leverages resident packet parameters to determine whether a packet loss attack is node- or link-related and, in the second case, locate the attack source. Moreover, we design a statistical model for determining optimal system thresholds by exploiting packet parameters variances. With our techniques\u27 diagnosis information, we develop Kinesis, a security incident response system for sensor networks designed to recover from attacks without significant interruption, dynamically selecting response actions while being lightweight in communication and energy overhead

Reducing complexity in developing wireless sensor network systems using model-driven development

Wireless Sensor Network (WSN) is a collection of small and low-powered gadgets called sensor nodes (motes), which are capable of sensing the environment, collecting and processing the sensed data, and communicating with each other to accomplish a specific task. Moreover, all sensed and processed data are finally handed over to a central gathering point called a base station (sink), where all collected data are stored and can be reviewed by the user. Most of the current methods concerning WSN development are application or platform-dependent; hence it is not a trivial task to reuse developed applications in another environment. Therefore, WSN application development is a challenging and complex task because of the low-level technical details and programming complexity. Furthermore, most WSN development projects are managed by software engineers, not application field experts or WSN end users. Consequently, WSN solutions are considered expensive, due to the amount of effort that has to be put into these projects. This research project aims to reduce the complexity in developing WSN applications, by abstracting the low-level technical and programming details for average developers and domain experts. In this research, we argue that reducing complexity can be achieved by defining a new Domain-Specific Language (DSL) as a new application development and programming abstraction, which supports multi-levels modelling (i.e. network, group, and node-level). The outcome of this work is the definition of a new language called SenNet, which is an open source DSL programming abstraction that enables application developers to concentrate on the high-level application logic rather than the low-level complex details. SenNet was developed using the principles of Model-Driven Development (MDD) and macro-programming. Developers can use SenNet as a high-level programming abstraction to auto-generate a ready-to-deploy single node nesC code for all sensor nodes that comprise the SenNet application. SenNet gives developers the flexibility they need by offering them a broad range of predefined monitoring tasks and activities, enabling developers to develop different application types such as Sense-Forward (SF), and Event-Triggered (ET); besides providing a set of node-level and in-network data processing tasks. The current SenNet version is configured to generate nesC code, yet SenNet can be set up to produce and generate any programming language such as Java, or C++, by reconfiguring the code generator to produce the new language format, without changing the language design and produced semantics. Various tests and user study have been used to evaluate SenNet’s usability and functional suitability. Evaluation results found that SenNet could save 88.45% of the LOC required to be programmed by a developer, and 87.14% of the required vocabularies. Furthermore, results showed that SenNet could save 92.86% and 96.47% of the program length and volume respectively. Most of the user study participants (96%) found SenNet to be usable and helps to achieve the required WSN application with reduced development effort. Moreover, 82% of the participants believe that SenNet is functionally suitable for WSN application development. Two real-world business case studies developed were used to assess SenNet’s appropriateness to develop WSN real applications, and how it can be used to develop applications related to data processing tasks. Based on the final evaluation results, it can be concluded that our research has been successful in introducing SenNet as a new abstraction to reduce complexity in the WSN application development process