| 1. |
- Pérez-Penichet, Carlos, et al.
(författare)
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Poster abstract : Augmenting WSNs with interoperable 802.15.4 sensor tags
- 2017
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Ingår i: SenSys 2017 - Proceedings of the 15th ACM Conference on Embedded Networked Sensor Systems. - New York, NY, USA : Association for Computing Machinery, Inc. - 9781450354592
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Konferensbidrag (refereegranskat)abstract
- The sensing capabilities of most sensor networks are fixed at the time of deployment. Adding new sensing capabilities to such networks is a costly and cumbersome process. We present Passive Sensor Tags, battery-free sensing devices that could be used to extend the sensing capabilities of an existing network. Sensor tags feature our new 802.15.4 receiver design which is suitable for micro-power operation, making battery-free tags possible. Because our tags can both transmit and receive 802.15.4 frames there is no need for any modification to the deployed hardware. We present preliminary measurements of transmission and reception range.
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| 2. |
- Grudén, Mathias
(författare)
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Wireless Sensor Network Systems in Harsh Environments and Antenna Measurement Techniques
- 2014
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Wireless sensor network (WSN) has become a hot topic lately. By using WSN things that previously were difficult or impossible to measure has now become available. One of the main reasons using WSN for monitoring is to save money by cost optimization and/or increase safety by letting the user knowing the physical status of the monitored structure. This thesis considers four main topics, empirical testing of WSN in harsh environments, antenna designs, antenna measurements and radio environment emulation.The WSN has been tested in train environment for monitoring of ball bearings and inside jet engines to monitor strain of blades and temperatures. In total, two investigations have been performed aboard the train wagon and one in the jet engine. The trials have been successful and provide knowledge of the difficulties with practical WSN applications. The key issues for WSN are robust communication, energy management (including scavenging) and physical robustness.For the applications of WSN in harsh environments antennas has to be designed. In the thesis, two antennas has been designed, one for train environment and one for the receiver in the jet engine. In the train environment, a more isotropic radiation pattern is preferable; hence a small dual layered patch antenna is designed. The antenna is at the limit of being electrically small; hence slightly lower radiation efficiency is measured. For the WSN in the jet engine, a directive patch array is designed on an ultra-thin and flexible substrate. The thin substrate of the antenna causes rather lower radiation efficiency. But the antenna fulfils the requirements of being conformal and directive.In reverberation chambers are used to measure antennas, but there are difficulties to provide a realistic radio environment, for example outdoor or on-body. In this thesis, a large reverberation chamber is designed and verified. It enables measurement between 400 MHz and 3 GHz. Also, a sample selection method is designed to provide a post processing possibilities to emulate the radio environment inside the chamber. The method is to select samples from a data set that corresponds to a desired probability density function. The method presented in this thesis is extremely fast but the implementation of the method is left for future research.
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| 3. |
- Jobs, Magnus, 1984-
(författare)
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Wireless Interface Technologies for Sensor Networks
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The main focus of the work presented in this thesis concerns the development and improvement of Wireless Sensor Networks (WSNs) as well as Wireless Body Area Networks (WBANs). WSN consist of interlinked, wireless devices (nodes) capable of relaying data wirelessly between the nodes. The applications of WSNs are very broad and cover both wireless fitness monitoring systems such as pulse watches or wireless temperature monitoring of buildings, among others.The topics investigated in the work presented within this thesis covers antenna design, wireless propagation environment evaluation and modeling, adaptive antenna control and wireless nodes system design and evaluation. In order to provide an end-user suitable solution for wireless nodes the devices require both small form factor and good performance in order to be competitive on the marked and thus the main part of this thesis focuses on techniques developed and data collected to help achieve these goals. Several different prototype systems have been developed which have been used to measure data by the Swedish Defence Research Agency (FOI), GKN Aerospace Sweden AB, the Swedish Transport Administration. The system developed with GKN Aerospace was used to do real-time test measurements inside a running RM12 jet engine and required a substantial amount of measurements, environmental modeling and system validation in order to properly design a wireless system suitable for the harsh and fast fading environment inside a jet engine. For FOI improvements were made on a wearable wireless body area network initially developed during the authors master thesis work. Refinements included work on new generation wireless nodes, antenna packaging and node-supported diversity techniques.Work and papers regarding the design of different types of antennas suitable for wireless nodes are presented. The primary constraints on the presented antennas are the limited electrical size. The types of antennas developed include electrically small helix antennas manufactured both on stretchable substrates consisting of a PDMS substrate with Galinstan as the liquid metal conductors, screen printed silver ink for helix antennas and conformal dual patch antennas for wireless sensor nodes. Other standard type antennas are included on the wireless sensors as well.
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| 4. |
- Al Nahas, Beshr, 1985, et al.
(författare)
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Low-power listening goes multi-channel
- 2014
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Ingår i: Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2014. ; , s. 2-9
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Konferensbidrag (refereegranskat)abstract
- Exploiting multiple radio channels for communication has been long known as a practical way to mitigate interference in wireless settings. In Wireless Sensor Networks, however, multi-channel solutions have not reached their full potential: the MAC layers included in TinyOS or the Contiki OS for example are mostly single-channel. The literature offers a number of interesting solutions, but experimental results were often too few to build confidence. We propose a practical extension of low-power listening, MiCMAC, that performs channel hopping, operates in a distributed way, and is independent of upper layers of the protocol stack. The above properties make it easy to deploy in a variety of scenarios, without any extra configuration/scheduling/channel selection hassle. We implement our solution in Contiki and evaluate it in a 97-node~testbed while running a complete, out-of-the-box low-power IPv6 communication stack (UDP/RPL/6LoWPAN). Our experimental results demonstrate increased resilience to emulated WiFi interference (e.g., data yield kept above 90% when Contiki MAC drops in the 40% range). In noiseless environments, MiCMAC keeps the overhead low in comparison to Contiki MAC, achieving performance as high as 99% data yield along with sub-percent duty cycle and sub-second latency for a 1-minute inter-packet interval data collection. © 2014 IEEE.
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| 5. |
- Åmand, Linda, et al.
(författare)
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Aeration control - a review
- 2013
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Ingår i: Water Science and Technology. - : IWA Publishing. - 0273-1223 .- 1996-9732. ; 67:11, s. 2374-2398
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Tidskriftsartikel (refereegranskat)abstract
- This review covers automatic control of continuous aeration systems in municipal wastewater treatment plants. The review focuses on published research in the 21st century and describes research into various methods to decide and control the dissolved oxygen (DO) concentration and to control the aerobic volume with special focus on plants with nitrogen removal. Important aspects of control system implementation and success are discussed, together with a critical review of published research on the topic. With respect to DO control and determination, the strategies used for control span from modifications and developments of conventional control methods which have been explored since the 1970s, to advanced control such as model-based predictive and optimal controllers. The review is supplemented with a summary of comparisons between control strategies evaluated in full-scale, pilot-scale and in simulations.
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| 6. |
- Abdalmoaty, Mohamed, 1986-
(författare)
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Learning Stochastic Nonlinear Dynamical Systems Using Non-stationary Linear Predictors
- 2017
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The estimation problem of stochastic nonlinear parametric models is recognized to be very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the maximum likelihood estimator and the optimal mean-square error predictor using Monte Carlo methods. Albeit asymptotically optimal, these methods come with several computational challenges and fundamental limitations.The contributions of this thesis can be divided into two main parts. In the first part, approximate solutions to the maximum likelihood problem are explored. Both analytical and numerical approaches, based on the expectation-maximization algorithm and the quasi-Newton algorithm, are considered. While analytic approximations are difficult to analyze, asymptotic guarantees can be established for methods based on Monte Carlo approximations. Yet, Monte Carlo methods come with their own computational difficulties; sampling in high-dimensional spaces requires an efficient proposal distribution to reduce the number of required samples to a reasonable value.In the second part, relatively simple prediction error method estimators are proposed. They are based on non-stationary one-step ahead predictors which are linear in the observed outputs, but are nonlinear in the (assumed known) input. These predictors rely only on the first two moments of the model and the computation of the likelihood function is not required. Consequently, the resulting estimators are defined via analytically tractable objective functions in several relevant cases. It is shown that, under mild assumptions, the estimators are consistent and asymptotically normal. In cases where the first two moments are analytically intractable due to the complexity of the model, it is possible to resort to vanilla Monte Carlo approximations. Several numerical examples demonstrate a good performance of the suggested estimators in several cases that are usually considered challenging.
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| 7. |
- Anubhab, Ghosh, et al.
(författare)
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DeepBayes -- an estimator for parameter estimation in stochastic nonlinear dynamical models
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Stochastic nonlinear dynamical systems are ubiquitous in modern, real-world applications. Yet, estimating the unknown parameters of stochastic, nonlinear dynamical models remains a challenging problem. The majority of existing methods employ maximum likelihood or Bayesian estimation. However, these methods suffer from some limitations, most notably the substantial computational time for inference coupled with limited flexibility in application. In this work, we propose DeepBayes estimators that leverage the power of deep recurrent neural networks in learning an estimator. The method consists of first training a recurrent neural network to minimize the mean-squared estimation error over a set of synthetically generated data using models drawn from the model set of interest. The a priori trained estimator can then be used directly for inference by evaluating the network with the estimation data. The deep recurrent neural network architectures can be trained offline and ensure significant time savings during inference. We experiment with two popular recurrent neural networks -- long short term memory network (LSTM) and gated recurrent unit (GRU). We demonstrate the applicability of our proposed method on different example models and perform detailed comparisons with state-of-the-art approaches. We also provide a study on a real-world nonlinear benchmark problem. The experimental evaluations show that the proposed approach is asymptotically as good as the Bayes estimator.
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| 8. |
- Degen, René, 1994-
(författare)
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Urban Virtual Test Field for HighlyAutomated Vehicle Systems
- 2021
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Autonomous driving is one of the key technologies for increasing road safetyand reducing traffic volumes. Therefore, science and industry are workingtogether on new innovative solutions in this field of technology. One importantcomponent in this context is the approval and testing of new solution concepts,with special focus on the ones for urban environments. Not only because ofthe high diversity of traffic situations, but also because of the close contactbetween vulnerable road users (VRU) and automated vehicles.In the course of this work, a novel approach for testing automated drivingfunctions and vehicle systems in urban environments is presented. The goal isto create a safe and valid environment in which the automated vehicle and theVRU can meet and interact. The basis is a highly realistic virtual model of acity center. The physical behavior of the vehicle and VRU is recorded usingmeasurement technology and transferred to the virtual city model.Based on representative urban traffic scenarios, the functionality of the urbantest field is investigated from various points of view. Thereby, the focus is onreal-time capability and the quality of interaction between the vehicle and theVRU.The investigations show that both the real-time capability and the interactionpossibilities could be demonstrated. Further, the developed methodologies aresuitable for real time applications.
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| 9. |
- Grudén, Mathias, 1985-
(författare)
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Wireless Sensor Network and Radio Wave Propagation in Harsh Environments
- 2012
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This licentiate thesis cover two important subjects regarding the application of wireless sensor networks (WSNs). Both subjects are related to propagation mechanisms. The first subject is what the radio channel looks like and how it behaves. In this case three different, and extreme, environments are measured and characterized - a train, a half scale jet engine fan and a full scale military jet engine. The train environment is characterized by measure the path loss and fading over distance. For the case with the jet engines, difficulties were found to measure the path loss over distance, so in this case stationary antennas were used, but with the engine running. Each of these shows an extreme type of fading, also known as Rayleigh fading. For the case of jet engine at full speed (about 10 000 rpm), it was shown that the time between two consecutive fading dips where only 290 μs, which is about twice the length of a data package from the WSN involved in this project. The Rayleigh distributed amplitude fading occurs when there is a multipath environment, the radio waves propagate several different paths between the transmitter and receiver, which causes a superposition at the receiver. When having Rayleigh fading, the performance of the radio link is greatly reduced. When applying a WSN in this type of environment, the use of several antennas will improve the received power of the signal. This is done by adding extra antennas to a wireless system and in a clever way combine the signals, or select one of two signals from the antennas. In a book chapter and in a paper presented in the thesis, a new and low energy type of diversity is described. The performance of this new type of diversity is shown by having a two branch diversity and discretely shifting the phase of each branch before combining them. In this case, four relative phase shifts are performed during each symbol received. When performing a combining like this, the energy is saved by not having any decision circuitry. By using this type of diversity and using a 90 % signal reliability and an ideal environment, the diversity gain is 5.5 dB for an averaging detector and 10.3 dB for a peak detector. The drawback with this system is that it is only limited for systems using simple types of amplitude (ASK) or frequency (FSK) modulation.
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| 10. |
- Ahmed, J., et al.
(författare)
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Automated diagnostic of virtualized service performance degradation
- 2018
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Ingår i: Proceedings 2018 IEEE/IFIP Network Operations and Management Symposium, NOMS 2018. - New York : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1-9
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Konferensbidrag (refereegranskat)abstract
- Service assurance for cloud applications is a challenging task and is an active area of research for academia and industry. One promising approach is to utilize machine learning for service quality prediction and fault detection so that suitable mitigation actions can be executed. In our previous work, we have shown how to predict service-level metrics in real-time just from operational data gathered at the server side. This gives the service provider early indications on whether the platform can support the current load demand. This paper provides the logical next step where we extend our work by proposing an automated detection and diagnostic capability for the performance faults manifesting themselves in cloud and datacenter environments. This is a crucial task to maintain the smooth operation of running services and minimizing downtime. We demonstrate the effectiveness of our approach which exploits the interpretative capabilities of Self- Organizing Maps (SOMs) to automatically detect and localize different performance faults for cloud services.
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