Made available in DSpace on 2016-04-04T18:31:39Z (GMT). No. of bitstreams: 1 LUIZ RODOLFO BARRETO DA SILVA.pdf: 1309393 bytes, checksum: c820374f746f8a21bb89acd6347d0907 (MD5) Previous issue date: 2014-02-07 / This work discusses the development of a method for estimating the distance of sensor nodes in Wireless Sensor Networks (WSN) in indoor environments, considering the need for adaptation of the method due to the presence of random factors that may influence the estimation of such distances. The estimation method presented is based on a signal strength indicator, RSSI (Received Signal Strength Indicator). / Este trabalho aborda a elabora??o de um m?todo para a estimativa de dist?ncia de n?s sensores em Redes de Sensores Sem Fio (RSSF) em ambientes internos fechados, considerando necessidade de adapta??o do m?todo devido ? presen?a de fatores aleat?rios que podem influenciar a estimativa dessas dist?ncias. O m?todo de estimativa apresentado ? baseado em um indicador de intensidade de sinal, o RSSI (Received Sinal Strength Indicator).

[pt] Algumas características básicas das redes de sensores sem fio (RSSF) dificultam as tarefas de criação e reconfiguração de aplicações. Nesse trabalho apresentamos um modelo de programação que pretende simplificar essas tarefas. O modelo se baseia no uso conjunto de funções parametrizáveis e de máquinas de estados finitos, e permite a implementação de diferentes tipos de aplicações para redes de sensores sem fio e a configuração remota dessas aplicações. Descrevemos alguns testes para avaliar o quanto esse modelo pode facilitar o desenvolvimento de novas aplicações, o quanto é fácil aplicar novas alterações sobre as aplicaçõesem execuçãos, e o impacto na quantidade de mensagens na rede por conta do uso da configuração remota. / [en] Some basic characteristics of wireless sensor networks (WSN) make application creation and reconfiguration dificult tasks. A programming model is presented to simplify these tasks. This model is based on a set of parametrized components and on a Finite State Machine, and allows the remote configuration of different applications over the same set of installed components. We describe some tests to evaluate its impact on the development process, and the ease of applying modifications to a running application. We also measure the additional impact of remote configuration on network activity.

The objective of this thesis is to design and implement a rapid, reconfigurable and portable reader for wirelessly interrogating inductively coupled passive sensors. While the current method of impedance analyzer is sensitive and an accurate, the instruments used are bulky and slow, substantially hampering in-field testing and interrogation of sensors. Current methods cannot provide a quantifiable measure on minimum necessary read-speeds and instrument accuracy desirable for rapid sensing applications. This work summarizes the design and hardware implementation of two reader methods that address the aforementioned requirements. Both reader methods are based on a reflectometer approach: Swept-frequency Reflectometer Reader and Switched-frequency Interrogation Technique (SWIFT). The first method is a much faster alternative to in-lab and in-field testing for structural health monitoring, and is intended as an immediate replacement for the impedance analyzer method. Switched-frequency Interrogation is specifically designed to satisfy the need for rapid and accurate reading, potentially for in-motion sensing applications. This method provides a way of empirically relating minimum necessary read-time required for desired read-ranges. It also facilitates quantification of uncertainty in measurements, which is very critical in determining instrument accuracy in-field. The system design and implementation of both methods are described in detail and experimental results are presented to benchmark the performance of the readers. Issues of instrument reliability and practical limitations are also discussed, with potential solutions. Both methods are intended as universal techniques for wirelessly interrogating coupled passive sensors, not limited to their current form of implementation. / text

A realtime wireless motion tracking system is developed. The system is capable of tracking the orientations of multiple wireless sensors, using a semi-distributed implementation to reduce network bandwidth and latency, to produce real-time animation of rigid body models, such as the human skeleton. The system has been demonstrated to be capable of full-body posture tracking of a human subject using fifteen devices communicating with a basestation over a single, low bandwidth, radio channel. The thesis covers the theory, design, and implementation of the tracking platform, the evaluation of the platform’s performance, and presents a summary of possible future applications.

The Kahne rumen sensor (bolus) is a device developed to measure temperature, pressure and pH in non-fistulated animals. This bolus allows real-time monitoring of the rumen environment, which could help preventing health problems such as rumen acidosis in cows. It is less invasive to use boluses compared to other technologies that measure the ruminal pH (e.g. rumenocentesis). Kahne boluses and transceivers are commercially available in the market. Several studies on the relationships between data recorded by the bolus and actual data recorded by independent devices were conducted. The bolus temperature and pressure were compared with actual temperature and pressure under controlled conditions. The pH drift was studied by comparing the difference between bolus and direct measurement over time. The capture of the data was calculated for each bolus in various experiments to examine the factors affecting the data capture rate of the boluses. Animal to animal variation was studied using boluses in a group of cows fed and managed under uniform conditions. An animal experiment involving fistulated cows eating two different diets was performed using boluses to monitor the changes of ruminal pH. There was no apparent interruption to normal animal behaviour as a result of using boluses. Regression relationships between bolus measurements and actual data for both temperature and pressure were developed and used for calibration of bolus data. The pH drift was a problem, as the regression relation between the pH difference and the time for one bolus from one experiment could not represent this bolus on other experiment. The data capture rate on the hourly basis ranged from 0 to 100%, but was usually between 30 to 70%. The data capture rate was affected by many factors and further studies to identify these factors are needed. A study of animal to animal variation suggests that in a comparison of 2 treatments, a minimum 3 cows per group would be required to detect the standard deviation of 0.11 for a pH difference of 5% of the mean (approximately 0.35 pH units). Seventeen cows per group would be required to detect the standard deviation of 0.33 for the same difference. The boluses effectively monitored the ruminal pH change in cows easting two different diets and the profile of change of pH was successfully analysed. Feeding 7.6 kg baleage twice a day cause pH to decrease at 0.009 pH units per minute during feeding, while offering a similar quantity of grass and hay once a day resulted in a decrease of 0.0009 pH units per minute during feeding. The beginning of pH increase was about 1 hour following feeding and continuous during resting and rumination. The level of pH increase did not differ significantly for two diets.. The Kahne devices appear to have advantages compared to other technologies for the measurement of parameters of the rumen environment on a real-time basis. Boluses are especially good at intensively monitoring the temperature, pressure, and pH in the rumen. The major limitations of this technology to be used are the data capture rate and the pH drift. By improving the limitations found in the experiment, the Kahne rumen sensor could become very useful for both scientific research and under commercial conditions for monitoring animal health.

Made available in DSpace on 2015-04-11T14:02:36Z (GMT). No. of bitstreams: 1 Felipe Lobo.pdf: 609088 bytes, checksum: ab4ee5abe3ca57cd1089d41d9089b070 (MD5) Previous issue date: 2012-03-22 / One of the main applications on Wireless Sensors Networks (WSNs) is the environmental monitoring, particularly in monitoring of the fauna in diverse places like forests, fields, etc. In these environments that are of difficult access, the maintenance of the sensors is impaired and energy restriction becomes a major factor in the life of the network. How in most such cases the data are not needed in real time, in this work is proposed and evaluated a new cross-layer algorithm, called PWAVE, turned to WSNs with periodic data collection, where data transmissions are made through a predetermined interval. While such transfers are not performed, the sensor still collecting information from the environment and turn off their radios to reduce energy consumption. Several other challenges appear before this way of working, for example, the synchronization of clocks, which are readily solved by the algorithm. The results show that the proposed solution is efficient and can save up to 51.2 % of energy with 99 % in the rate of data delivery when compared with similar solutions / Uma das principais aplicações existentes em Redes de Sensores Sem Fio (RSSFs) é o monitoramento ambiental, mais particularmente no acompanhamento da fauna existente em locais diversos como florestas, campos, etc. Nesses ambientes de difícil acesso, a manutenção dos sensores fica prejudicada e a restrição de energia torna-se um fator primordial para a vida útil da rede. Como na maioria desses casos os dados não são necessários em tempo real, neste trabalho é proposto e avaliado um novo algoritmo cross-layer, denominado PWAVE, voltado para RSSFs com coleta periódica, onde as transmissões dos dados são feitas através de intervalos predeterminados. Enquanto essas transmissões não são executadas, o sensor permanece coletando as informações do ambiente e seus rádios desligam-se, a fim de reduzir o consumo de energia. Diversos outros desafios aparecem diante deste modo de trabalho como, por exemplo, a sincronização dos relógios, que são prontamente solucionados pelo algoritmo proposto. Os resultados mostram que a solução proposta é eficiente e consegue economizar até 51.2% de energia com 99% na taxa de entrega de dados quando comparado com soluções similares

Context: Most of the patients suffering from any neurological disorder pose ambulatory disturbance at any stage of disease which may result in falling without showing any warning sign and every patient is different from another. So there is a need to develop a mechanism to detect shaky motion. Objectives: The major objectives are: (i) To check different gait parameters in walking disorders using Shimmer platform (R). (ii) Wearing SHIMMER wireless sensors on hip, waist and chest, to check which one is the most suitable. (iii) To draw effective conclusion/results based on calibrated data in real time and offline processing in EyesWeb/Matlab.To develop an effective mechanism/algorithm for security warning and activating alarm systems. Methods: Our thesis project is related to analyze real-time gait of the patient suffering from Parkinson's disease for actively responding to the shaky movements. Based on real world data, we have developed a mechanism to monitor a real time gait analysis algorithm to detect any gait deviation. This algorithm is efficient, sensitive to detect miner deviation and not hard coded i.e. user can set Sampling Rate & Threshold values to analyze motion. Researchers can directly use this algorithm in their study without need to implement themselves. It works on pre-calculated threshold values while initial sampling rate is set to 100MHz. Results: Accelerometers putting on the chest shows high unnecessary acceleration during fall, suggest putting on waist position. Also, if a patient initiates steps with energy, his/her gait may become more stable as shown in the conscious gait. Results show that after DBS surgical procedure, the patient still experiences postural instability with fall. So it is evident to show that such patients may have reduced cognition even after surgery. Another finding is that such patients may lean left or right during turning. Conclusions: We have presented a real time gait analysis algorithm, capable of detecting the motion of the patient with PD to actively respond to the shakier motion setting threshold values. Our proposed algorithm is easy to implement, reusable and can affectively generate healthcare alarms. Additionally, this system might be used by other researchers without the need to implement by themselves. The proposed method is sensitive to detect fall therefore objectively can be used for fall risk assessment as well .The same algorithm with minor modifications can be used for seizure detection in other disorders mainly epileptic seizers to alert health providers for emergency. / Any malfunctioning of neurons in the nervous system is called Neurological disorder. Over 100 neurological disorders have been discovered throughout the world. In our study, we have chosen one disorder: Falling in Parkinson’s disease. Experiments can be performed on different gait parameters like body velocity, time ratio, ground slope, stance/swing, body gestures and gait patterns. Sensors can be put on hips, knees, thighs, limbs, neck, head, chest or any other suitable body part to capture motion data for further pre-and post-processing. Pre-processing is real time gait analysis through time domain and frequency domain to trigger various security steps and messages for patient care. Post -processing is offline analysis of motion data in different tools such as EyesWeb, BioMOBIUS and Matlab for calculations, analysis and plotting of motion to take decisions to formulate a mechanism for patient activity detection and monitoring. The area which we choose is pretty interesting, pertaining to rehabilitation, wellness and healthcare for older people. Other related keywords may include keywords may be helpful using one or combination of more than one. WSN, BAN or WBAN, biosensors, neurological disorders, gait analysis, fall detection, fall avoidance, Parkinson’s disease, wireless accelerometer, ambulatory monitoring, freezing of gait and fall risk assessment. Most of the patients suffering from any neurological disorder in later stages of disease pose ambulatory disturbance especially falling. Such patients may fall without showing any warning sign and every patient is different from another. So there is a need to develop a mechanism to detect shaky motion to avoid such patients from falling. Therefore, a real time gait analysis algorithm is implemented to trigger security alarms. In order to assess & evaluate gait analysis, accurate, reliable & consistent measurement tools need to be utilized. Even slight deviation in the data monitoring through measurement tools is not encouraged to use [21]. Gait disturbance can be measured using 3 axis accelerometers like SHIMMER(R) for real time motion analysis. In the wireless sensor network, SHIMMER platform provides wireless Body Area Network (BAN) to capture motion data. This data can be saved in CSV (Comma Separated Version) file for post processing or a 2 GB MicroSD card can be used to capture data in the SHIMMER accelerometer itself. The use of accelerometer is more suitable due to the fact that we are 66 capturing data from postural instability. One two or combinations of accelerometers can be put on different body parts. SHIMMER Gyroscope is more suitable for jerky motion with disease such as epilepsy. Mostly accelerometers and gyroscopes are used for gait analysis [4]. Defining our research work, this study is carried out on the patient with Parkinson’s disease (PD), to study various gait parameters, test wireless accelerometers on different body parts, and implementing an algorithm to trigger a security alarm system by setting a threshold value. Criteria for setting threshold value are calculating standard deviation and employed by different researchers like [3]. The main motivation to perform this experimental research work is to avoid the patient with PD from falling during unstable shaky gait. Security alarms can be activated whenever a patient poses a shakier gait. Two types of alarms or sirens can be activated in the lgorithm. First, to activate Warning Alarms when the value from motion data exceeds maximum threshold value 1 and second to activate Emergency Alarms when the value from motion data exceeds maximum threshold value 2. Later on airbag can be put on the patient’s hip position to avoid him/her from injury and hip fracture. The results show the proposed system is fairly simple to implement in the real time environment, flexible to adjust to any necessary change in the future.The major advantage of this algorithm is its reusability. Algorithm is not hard coded because a user can set his own sampling rate or threshold value or both, and check results. This algorithm is further modifiable to trigger airbag, a security push button, SOS calls, messages, siren activation system, automatic email forwarding, health care alert, and many more. The same algorithm with minor modifications can be used for fall avoidance or health care assurance on other disorders mainly in epileptic seizers to alert health providers in case of emergency, can be used for other seizures and disorders such as epilepsy, etc. Overall, this report presents the analysis of an experiment to measure the usability of wireless accelerometer data to monitor the activity of the patient suffering from Parkinson disease. Our research and experimental work can be quoted toward fall risk assessment. / Inam-ul-Haq Lindblomsvagen 37233 Ronneby +46 760609660

yes / This is the tenth workshop to be organised under the postgraduate programmes in electrical and electronic engineering (EEE). Over the past ten years, the Research Seminar Series has provided a snapshot of the research agenda. Early Proceedings addressed issues such as third-generation (3G) mobile and GPS satellite navigation, while in this issue, the importance of the green agenda and the influence of broadband mobile communications, smartphones and the World Wide Web are in evidence. In total, forty-five papers have been selected for the Proceedings.

yes / This is the twelfth workshop to be organised under the postgraduate programmes in electrical and electronic engineering (EEE). In total, thirty-four papers from forty-nine submissions have been selected for the Proceedings. The Proceedings comprises eleven themes, which reflect today's research agenda.

In partnership with iMonSys - an emerging company in the passive care field - a new system, 'Verity', is being developed to fulfil the role of a passive behaviour monitoring and alert detection device, providing an unobtrusive level of care and assessing an individual's changing behaviour and health status whilst still allowing for independence of its elderly user. In this research, a Hidden Markov Model incorporating Fuzzy Logic-based sensor fusion is created for the behaviour detection within Verity, with a method of Fuzzy-Rule induction designed for the system's adaptation to a user during operation. A dimension reduction and classification scheme utilising Curvilinear Distance Analysis is further developed to deal with the recognition task presented by increasingly nonlinear and high dimension sensor readings, and anomaly detection methods situated within the Hidden Markov Model provide possible solutions to identification of health concerns arising from independent living. Real-time implementation is proposed through development of an Instance Based Learning approach in combination with a Bloom Filter, speeding up the classification operation and reducing the storage requirements for the considerable amount of observation data obtained during operation. Finally, evaluation of all algorithms is completed using a simulation of the Verity system with which the behaviour monitoring task is to be achieved.