Tyrimai įterptines Operacines sistemas skirtus belaidžio korinio daiktų interneto (DI) sistemoms

The master degree final project focusses on Embedded Operating Systems for a Wireless Cellular IoT System. Internet of Things (IoT) is a great chance for upcoming devices to be intelligent, more robust and efficient. This tremendous pathway has become available due to regular cost degradation of various separate systems and accessories like sensors, computing devices, communication methods, the cloud and the big data paradigms. Connectivity is the base for IoT and the type of access needed will focus on the nature of the application. Thus, the target is now on Narrow Band IoT, which is a Low Power Wide Area Network (LPWAN) radio technology standard that has been developed to contribute a wide range of devices and services to be connected via cellular telecommunications bands. Accordingly, the thesis works on ARM MBED OS, an embedded operating system, which is a platform as well as operating system for internet connected devices for 32-bit ARM cortex-M microcontrollers which is needed for NB-IoT system. First, MBED OS is designed and implemented on ARM cortex -M prototyping system MPS2+ as a real-time operating system by bringing latest version of CMSIS-RTOS with RTX as kernel on Cortex-M4 as well as its successor Cortex-M33 contained on MPS2+ hardware board to examine different RTOS parameters such as memory, heap, stack, hardware and software impacts. Next, these obtained parameters for MBED OS is compared with other RTOS, say FreeRTOS on MPS2+ board. Thus, the final outcome would be how cellular IoT system will change when a new embedded operating system will be incorporated into Corelink SSE 200 IoT subsytem and fulfil the requirements for NB-IoT standard

IoT-laitteiden datayhteyden automaattinen määrittely matkapuhelinverkoissa

Cellular networks have existed for almost forty years. During the course of their history, they have transformed from wireless voice communication providers to wireless network providers. Nowadays mobile broadband data forms the bulk of the cellular data transfer which was a staggering 14 exabytes per month in year 2017, or 2.9 gigabytes per smartphone per month. The Internet of Things is changing this connectivity landscape by introducing devices in the millions but with scarce individual resources and data usage. However, there are some challenges related to cellular data connections in constrained IoT devices. This thesis identifies those challenges and proposes solutions to overcome them for enabling simpler cellular data connectivity. We first present the technical challenges and solutions found in today’s cellular IoT devices. We then present a proof of concept prototype that realizes automatic cellular connectivity in a very constrained IoT device. The prototype is capable of connecting to a management system and reporting sensor readings without requiring any user interaction. Besides recognizing important improvements in the next generation of cellular IoT technology, the thesis concludes with suggestions on how to improve the usability of programming interfaces for cellular connectivity.Lähes neljäkymmenvuotisen historiansa aikana atkapuhelinverkot ovat muuttuneet puheen välittäjistä langattomaksi dataverkoksi. Nykyään langaton laajakaista muodostaa suuren osan matkapuhelinverkoissa siirretystä datasta, jota oli 14 exatavua kuukaudessa vuonna 2017. Esineiden Internet tuo verkkoon miljoonia laitteita joiden yksittäinen datansiirron tarve on vähäinen. Matkapuhelinverkon datayhteyden käyttö ei kuitenkaan ole ongelmatonta rajoittuneissa Esineiden Internetin laitteissa. Tämä diplomityö tunnistaa ja luokittelee näitä teknisiä haasteita ja ehdottaa ratkaisuja niihin. Esittelemme prototyypin joka toteuttaa automaatisen matkapuhelinverkon datayhteyden luonnin rajoittuneessa laitteessa. Prototyyppi ottaa yhteyden hallintajärjestelmään ja raportoi mittausdataa ilman käyttäjältä vaadittavia toimia. Johtopäätöksenä tämä diplomityö esittää parannuksia tehtäväksi matkapuhelinverkkojen datayhteyksien ohjelmointirajapintoihin niitä käyttävissä laitteissa. Löysimme myös tärkeitä parannuksia joita on jo tehty tulevan sukupolven matkapuhelinverkon määrittelyssä

Exploration of a Condition Monitoring System for Rolling Bearing Based on a Wireless Sensor Network

In recent years, wireless sensor networks (WSN) have attracted attention in machine condition monitoring (CM) fields for a more efficient system based on the inherent advantages of WSN, including ease of installation and relocation, lower maintenance cost and the ability to be installed in places not easily accessible. As critical components of rotating machines, bearings account for more than 40% of the various types of failures, causing considerable unpredicted breakdowns of a plant. Thus, this thesis intends to develop a cost-effective and reliable wireless measurement system for rolling bearing condition monitoring. Based on the investigation of various wireless protocols, Zigbee has been taken as a the most promising candidate for establishing the wireless condition monitoring system as it can have an acceptable bandwidth at low power consumption. However, a comparison made between wired and wireless measurement system has found that the Zigbee based wireless measurement system is deficient in streaming long continuous data of raw vibration signals from typical application environment with inevitable ambient interference. As a result, data loss can happen from time to time. To solve this issue, an on-board processing scheme is proposed by implementing advanced signal processing algorithms on the sensor side and only transmitting the processed results with a much smaller data size via the wireless sensor network. On this basis, a wireless sensor node prototype based on the state-of-the-art Cortex-M4F is designed to embed customizable signal processing algorithms. As an extensively employed algorithm for bearing fault diagnosis, envelope analysis is chosen as the on-board signal processing algorithm. Therefore, the procedure of envelope analysis and considerations for implementing it on a memory limited embedded processor are discussed in detail. With the optimization, an automatic data acquisition mechanism is achieved, which combines Timer, ADC and DMA to reduce the interference of CPU and thus to improve the efficiency for intensive computation. A 2048-point envelope analysis in single floating point format is realized on the processor with only 32kB memory. Experimental evaluation results show that the embedded envelope analysis algorithm can successfully diagnose the simulated bearing faults and the data transmission throughput can be reduced by at least 95% per frame compared with that of the raw data; this allows a large number of sensor nodes to be deployed in the network for real time monitoring. Furthermore, a computation efficient amplitude based optimal band selection algorithm is proposed for choosing an optimal band-pass filter for envelope analysis. Requiring only a small number of arithmetical operations, it can be embedded on the wireless sensor node to yield the desired performance of bearing fault detection and diagnosis

Imaging Payload System Design for Nano-Satellite Applications in Low-Earth Orbit

학위논문 (석사)-- 서울대학교 대학원 : 기계항공공학부, 2016. 8. 정인석.This study presents a complete hardware and software design of an imaging payload, InterFace Camera (IFCAM), for the CubeSat standard. The payload is intended to take earth images from 350km Low Earth Orbit and is a non-critical mission payload for Seoul National Universitys first CubeSat, SNUSAT-1. The camera has a MT9D111 2M pixel image sensor with a STM32F429ZI processor running at 180MHz, 4GB SD card for data storage, 8MB flash memory and 8MB expandable SDRAM. The camera is configured to take images in 160x120 pixels because of the limited downlink budget given to the imaging payload. Edmund Optics fixed focus M12x0.5 lens with 650mm IR-Cut off filter and the Ground Sampling Distance (GSD) is calculated to about 650km. The Ground Swath, with the optics, is 570x400km which cover South Korea. The payload underwent Random Vibration and Vacuum Testing and showed no issues in the design. Furthermore, the design proposed is modular and has been used for designing the On-Board Computer for SNUSAT-1.1. Introduction 1 1.1. Previous Work 1 1.2. Requirement 3 1.3. Imaging Payload Structure 3 1.4. Remote Sensing 4 1.5. Space Environment 5 2. Hardware 9 2.1. Design Constraint 9 2.2. Hardware Selection 10 2.3. Hardware Design 18 2.4. Prototyping. 19 2.5. Flight Model PCB Design 30 3. Software 31 3.1. Introduction 31 3.2. Software Development Tools/Resources 31 3.3. Software Description 35 4. Verification 40 4.1. Field Testing 40 4.2. Vibration Testing 42 4.3. Vacuum Testing 59 5. Improvements 63 5.1. Software 63 5.2. Hardware 64 6. Conclusion 66 6.1. Requirement Review 66 6.2. Overview 67 References 69 Abstract in Korean 71 Appendices 72Maste

Energetsko učinkovit sistem za detekcijo slonov s pomočjo strojnega učenja

Human-Elephant Conflicts are a major problem in terms of elephant conservation. According to WILDLABS, an average of 400 people and 100 elephants are killed every year in India alone because of them. Early warning systems replace the role of human watchers and warn local communities of nearby, potentially life threatening, elephants, thus minimising the Human-Elephant Conflicts. In this Master\u27s thesis we present the structure of an early warning system, which consists of several low-power embedded systems equipped with thermal cameras and a single gateway. To detect elephants from captured thermal images we used Machine Learning methods, specifically Convolutional Neural Networks. The main focus of this thesis was the design, implementation and evaluation of Machine Learning models running on microcontrollers under low-power conditions. We designed and trained several accurate image classification models, optimised them for on-device deployment and compared them against models trained with commercial software in terms of accuracy, inference speed and size. While writing firmware, we ported a part of the TensorFlow library and created our own build system, suitable for the libopencm3 platform. We also implemented reporting of inference results over the LoRaWAN network and described a possible server-size solution. We finally a constructed fully functional embedded system from various development and evaluation boards, and evaluated its performance in terms of power consumption. We show that embedded systems with Machine Learning capabilities are a viable solution to many real life problems.Konflikti med ljudmi in sloni predstavljajo velik problem ohranjanja populacije slonov. Zaradi fragmentacije in pomanjkanja habitata sloni, v iskanju hrane, pogosto zaidejo na riževa polja in plantaže, kjer pridejo v stik s človekom. Po podatkih skupnosti WILDLABS, zaradi konfliktov, samo v Indiji, letno umre povprečno 400 ljudi in 100 slonov. Sistemi zgodnje opozoritve nadomeščajo vlogo človeških stražarjev in opozarjajo bližnjo skupnost o bližini, potencialno nevarnih, slonov in tako pripomorejo k zmanjševanju konfliktov med ljudmi in sloni. V tem magistrskem delu predstavljamo strukturo sistema zgodnje opozoritve, ki je sestavljen iz večih, nizko porabnih, vgrajenih sistemov, ki so opremljeni s termalnimi kamerami in ene dostopne točke oz. prehoda (gateway). Vgrajeni sistemi so postavljeni na terenu, ob zaznavi slona pošljejo opozorilo preko brezžičnega omrežja do dostopne točke, ki nato lahko opozori lokalno skupnost. Za prepoznavo slonov iz zajetih termalnih slik smo uporabili metode strojnega učenja, bolj specifično konvolucijske nevronske mreže. Glavni cilji tega magistrskega dela so bili zasnova, izvedba in ovrednotenje modelov strojnega učenja, ki jih je možno poganjati na mikrokrmilnkih pod pogoji nizke porabe

Optimisation of vibration monitoring nodes in wireless sensor networks

This PhD research focuses on developing a wireless vibration condition monitoring (CM) node which allows an optimal implementation of advanced signal processing algorithms. Obviously, such a node should meet additional yet practical requirements including high robustness and low investments in achieving predictive maintenance. There are a number of wireless protocols which can be utilised to establish a wireless sensor network (WSN). Protocols like WiFi HaLow, Bluetooth low energy (BLE), ZigBee and Thread are more suitable for long-term non-critical CM battery powered nodes as they provide inherent merits like low cost, self-organising network, and low power consumption. WirelessHART and ISA100.11a provide more reliable and robust performance but their solutions are usually more expensive, thus they are more suitable for strict industrial control applications. Distributed computation can utilise the limited bandwidth of wireless network and battery life of sensor nodes more wisely. Hence it is becoming increasingly popular in wireless CM with the fast development of electronics and wireless technologies in recent years. Therefore, distributed computation is the primary focus of this research in order to develop an advanced sensor node for realising wireless networks which allow high-performance CM at minimal network traffic and economic cost. On this basis, a ZigBee-based vibration monitoring node is designed for the evaluation of embedding signal processing algorithms. A state-of-the-art Cortex-M4F processor is employed as the core processor on the wireless sensor node, which has been optimised for implementing complex signal processing algorithms at low power consumption. Meanwhile, an envelope analysis is focused on as the main intelligent technique embedded on the node due to the envelope analysis being the most effective and general method to characterise impulsive and modulating signatures. Such signatures can commonly be found on faulty signals generated by key machinery components, such as bearings, gears, turbines, and valves. Through a preliminary optimisation in implementing envelope analysis based on fast Fourier transform (FFT), an envelope spectrum of 2048 points is successfully achieved on a processor with a memory usage of 32 kB. Experimental results show that the simulated bearing faults can be clearly identified from the calculated envelope spectrum. Meanwhile, the data throughput requirement is reduced by more than 95% in comparison with the raw data transmission. To optimise the performance of the vibration monitoring node, three main techniques have been developed and validated: 1) A new data processing scheme is developed by combining three subsequent processing techniques: down-sampling, data frame overlapping and cascading. On this basis, a frequency resolution of 0.61 Hz in the envelope spectrum is achieved on the same processor. 2) The optimal band-pass filter for envelope analysis is selected by a scheme, in which the complicated fast kurtogram is implemented on the host computer for selecting optimal band-pass filter and real-time envelope analysis on the wireless sensor for extracting bearing fault features. Moreover, a frequency band of 16 kHz is analysed, which allows features to be extracted in a wide frequency band, covering a wide category of industrial applications. 3) Two new analysis methods: short-time RMS and spectral correlation algorithms are proposed for bearing fault diagnosis. They can significantly reduce the CPU usage, being over two times less and consequently much lower power consumptio

Outils d’analyse de performance de systèmes d’exploitation avec partitionnement spatial et temporel

Résumé Dans le domaine de l’avionique commerciale, les systèmes informatisés sont de plus en plus nombreux et complexes. Le partage des ressources devient alors une nécessité afin de limiter leur croissance en masse et en coût. Puisque ces systèmes embarqués évoluent dans un environnement imposant des contraintes temporelles et de sécurité très strictes, les systèmes d’exploitation temps réel utilisés doivent être conçus spécialement pour ces conditions. Dans ce contexte, le standard ARINC 653 définissant le comportement et les interfaces de systèmes avec partitionnement spatial et temporel a été publié. Ces systèmes d’exploitation fournissent les garanties nécessaires au partage des ressources dans un domaine temps réel critique. Lors du développement d’applications sur ce genre de systèmes, les techniques de débogage classiques ne sont pas adaptées pour tous les types de problèmes pouvant survenir. En effet, l’arrêt complet de l’exécution d’un programme temps réel influence trop son comportement pour que la chaîne d’évènements menant au problème recherché soit observable. Par conséquent, l’enregistrement d’informations durant l’exécution pour une analyse a posteriori est une méthode avantageuse pour ce type de situation. Le traçage est une technique qui permet aussi de récupérer l’information sur le temps d’exécution de certaines composantes, ce qui peut être utile pour la caractérisation de performances du système. Pourtant, la disponibilité de tels outils pour les systèmes d’exploitation temps réel avec partitionnement spatial et temporel est très limitée en ce moment. Dans ce mémoire, nous présentons un environnement d’analyse de traces pour les systèmes temps réel avec partitionnement spatial et temporel. Nous considérons l’exécution de processus à l’intérieur de partitions et l’ordonnancement de ces deux éléments par le système d’exploitation. Grâce à l’information contenue dans une trace, un historique des états des processus à travers le temps est reconstruit. La solution est testée sur Linux et Xen, deux systèmes pour lesquels nous créons des configurations s’approchant du comportement d’un système d’exploitation avec partitionnement spatial et temporel. Pour montrer l’utilité de cet outil de visualisation pour le diagnostic de problèmes de performances, nous développons un banc d’essai adapté aux systèmes avec partitionnement spatial et temporel. Le banc d’essai est conçu pour être utilisé de façon indépendante ou de pair avec l’environnement d’analyse de traces. Cette deuxième option permet d’identifier automatiquement les valeurs extrêmes dans les résultats afin d’observer l’état du système lors de leurs occurrences. Avec cette fonctionnalité, nous montrons comment notre solution permet aussi le diagnostic de problèmes causés par l’exécution concurrente d’applications mal isolées. ----------ABSTRACT:Computer systems in commercial avionics keep increasing in number and complexity. To reduce their cost and mass, it becomes highly interesting to share the resources between the different subsystems. Since the applications composing these subsystems must meet particularly stringent time and safety constraints, the operating systems managing them must be conceived with these specificities in mind. The ARINC 653 standard was published to regulate the development of such operating systems that provide very strong guarantees about the space and time isolation of the running applications, to enable the sharing of resources between them. Traditional debugging techniques are not efficient for every type of problems that developers may encounter while designing real-time applications. Entirely stopping the execution of the studied application is not always an option, since it may impact the chain of events leading to the problematic situation. An alternative to this is to record information about the execution, while the applications are running, and to analyze it offline. This information is also useful to compute performance metrics about the system. Unfortunately, the availability of such tools is very limited for operating systems with space and time partitioning. We present a trace analysis framework for operating systems with space and time partitioning. The visualization tool developed covers the scheduling of processes, and partitions containing these processes. With the information available in the operating system trace, a state history of the processes is built and displayed to the user. The solution is tested on Linux and Xen, two systems for which we created configurations to approximate as accurately as possible the behaviour of operating systems with space and time partitioning. To demonstrate the usefulness of this tool, a new portable and open source benchmark was developed especially for this type of operating systems. The benchmark is self-standing, but can optionally be integrated with the proposed trace analysis framework. By using this option, the developed view can be automatically synchronized to the occurrences of outlier values to observe the state of the system at these points. We will show how this functionality can be used to detect isolation problems while running applications concurrently

Firmware Development of a LoRaWAN Multi-Sensor Generic Node : an Industrial IoT Empirical Study

Connectivity is the defining property of the Internet of Things (IoT). Multiple technologies and techniques allow embedded devices to transmit and receive data. The intersection between connectivity demands, physical and environmental limitations is what triggers the use of a specific technology. Low Power Wide Area (LPWA) wireless communication technologies such as LoRa and LoRaWAN are showing practicality and ease of the use in the field of IoT. LoRa modulation ability to provide devices with longer communication ranges make it an attractive choice in multiple IoT use cases. The energy efficiency and scalability aspects of LoRaWAN protocol trigger the research curiosity around the challenges and opportunities of using the technology. In this study, we provide an extensive overview of the firmware development of an industrial LoRaWAN device. An empirical analysis of the device capabilities provides a deeper understanding of the technology potential and the possible areas of improvements. Energy-efficient firmware design practices are explored, analysed and implemented to provide a foundation for future developments in the field. Furthermore, we propose and evaluate a new LoRaWAN application design that explores over the air firmware configuration in runtime a novel micro update scheme. We devise a simple LoRaWAN energy estimation model and apply it to the proposed application. The same model is used to get an indication of LoRaWAN firmware updates over the air (FUOTA) practicality. The applied model highlighted useful energy optimisation techniques for an improved LoRaWAN firmware development

Material-integrated Prediction, Control, and Distributed Learning in Soft Robots

Soft roboticists promise lofty goals around soft robots, such as Mars, deep-sea, and internal human body exploration. Yet, roboticists design and build algorithms that make the robot reliant on personal computers or clouds for important functions. In most soft robotic designs, a low-power microcontroller unit (MCU) collects sensor signals and sends actuation commands from the material. This work focuses on making the first steps towards computationally untethering advanced prediction, control, and learning algorithms onto the already existing MCUs in the soft robot material by considering the algorithm&rsquo;s memory needs and power consumption. The first step towards this work is the proposal, building, deployment, and open-sourcing of a compiler (nn4mc, https://nn4mc.com) that allows researchers and hobbyists to translate neural network inference trained in Tensorflow into C code that is interpretable by generalized low-power MCUs. The second step consists of untethering real-time high-bandwidth nonlinear control that uses neu�ral network forward kinematic models compiled using nn4mc and real-time optimization toward nonlinear predictive control that consumes less than 46mW of average power and controls soft ac�tuators with less than 2 mm of error for a path following task. The third step consists of encoding sensor signals from the soft robot onto a space where active learning becomes a trivial task through observation embeddings and graph-based distributed semi-supervised learning without the need for backpropagation at the low power memory-restricted compute units in a simulated study. nn4mc has sparked collaborations with many researchers, such as real-time prediction in prosthetic fin�gertips, aeroelastic-aware airplane wings, and real-time pose classification on a wearable garment worn by drag queens. Taken together, this body of work presents tools and methods to deliver on the promise of computationally untethered soft robots; that is, accessible firmware engineering tractable at low-power compute, which belongs in the future of soft robotics.</p

Point of Care Molecular Diagnostics for Humanity

Diagnostics of disease at POC (point of care) has been declared one of the Grand Challenge by the Bill and Melina Gates Foundation (BMGF). Infectious diseases constitute a major cause of disease burden and cause more than half a billion Disability-Adjusted Life Years (DALYs) and millions of deaths each year. They have an especially large effect on children under 5 years of age. We have analyzed data from the GBD 2010 (Global Burden of Disease) project to emphasize the damage caused by infectious diseases, and highlight the opportunity of using diagnostic tools to rapidly identify and treat diseases. To motivate the work of this thesis, we quantify the expected impact of appropriate diagnostic technologies. We have also analyzed the requirements that a diagnostic tool should meet to generate the maximal global impact. We present various existing TPPs (Target Product Profiles) from different organizations and suggest some additions to these existing TPPs. We explain the particular molecular pathology technologies which have the potential to allow deployment of functional products in the developing world for point-of-care pathogen detection, especially in low-resource settings. We perform a detailed analysis on existing polymerase chain reaction (PCR) systems and describe the problems caused with thermal performance and optical interrogation. We list the requirements that disposable cartridges for such instruments should meet and suggest a metal base design with polymer top. After detailed FEA simulations, we demonstrate that the thermal response can be modeled using a one-dimensional (1D) lumped element system. We show improvements in thermal response due to using a metal base and the effect of fluid height. We also performed thermal-structural simulations to quantify the stresses on the adhesive bonds of metal/polymer cartridges. Next, we explain fabrication of these cartridges. We show methods to dispense adhesive using a robot and a custom made jig to spread the adhesive during curing. The cartridge was tested with different PCR reagents and we obtained reaction efficiencies approaching those of the commercial real time PCR machines. Our fabrication technique is useful to join dissimilar materials and is production friendly. By developing custom software, we observed the cartridge performance in a continuous manner. We could see the thermal response of cartridges by continuous fluorescence monitoring, and used reflective aluminum which increase light collection efficiency. We then present a simple and robust new way for thermal cycling. Robust thermal cycling has been a major challenge conducting PCR, especially in point of care situations. Here, we suggest a contact cooling approach, in which the cartridge rests on a thin metal plate with an integrated thin heater constructed from flexible printed circuit board (PCB) material. We use a solenoid to move a metal plate to cool down the sample cartridge during cycling. The metal plate then rests on a larger heat sink to disperse the shuttled heat. Our design is dust and water proof and was verified on a bench-top prototype. A novel optical design for fluorescence detection during qPCR is also described. We suggest a lateral illumination waveguide geometry with prism coupling that eliminates lenses and is integrated into an injection molded cartridge. The light is homogenized using a light guide, and we quantify the sources of scattered stray light from the chamber edge by performing ray tracing simulations to optimize the precise geometry. The design is tolerant to misalignments and enables easy coupling of LED light into the chamber. As the light collection efficiency is high, the size of the chamber can be very small. We tested real PCR reactions using this concept and observed a rapid integration time, enabling very fast reading. Sample preparation has been another challenge for all point-of-care (POC) lab-on-chip devices for many years. Here, we propose a new design which is robust, fast, flexible and simple, and uses a sliding seal to move the collected sample between various reservoir chambers. The sample moves on a slider sandwiched between seals that shuttles a DNA binding membrane between different reactions. Thus, size and volumes of reagents can be increased without increasing dead volumes. This design is easily automated, and positive displacement of fluids can work with many reagents without worrying about their characteristics such as foaming. The speed of the sample preparation protocols is high and complex protocols can be ported on this design concept, which we tested on real clinical samples and obtained impressive results. We designed and injection molded devices to test and verify this concept. Finally, we focus on instrumentation and software required to allow our technology to be used at the POC. We describe our embedded electronics and describe the powerful micro-controller and various high performance ICs that are used to construct a fully functional for sample to answer instrument. We developed various versions of software. The developer software allows us to control our system and bench top setup. Our end user product includes a tablet and cell phone software interface. Software was developed for a windows 8 tablet, windows 8 phone and an Android based devices. To conclude, we very briefly describe the POC systems that are under development: A portable qPCR system with a separate cartridge design, and a universal sample to answer system that performs qPCR, sample preparation and sample to answer protocols in one box depending on the cartridge. As per best of our knowledge the cost of this technology is much lower than any other option in its class. The sample to answer instrument is expected to cost less than $500. The test cost is expected to be less than$5. The performance is not compromised. We hope that this work can help bring a transformative change in the practice of pathology especially in the developing world.</p