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Träfflista för sökning "WFRF:(O'Nils Mattias) "

Sökning: WFRF:(O'Nils Mattias)

  • Resultat 41-50 av 211
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41.
  • Fedorov, Igor, 1980-, et al. (författare)
  • Towards calibration of outdoor multi-camera visual monitoring system
  • 2018
  • Ingår i: ACM International Conference Proceeding Series. - New York, NY, US : ACM Digital Library. - 9781450365116
  • Konferensbidrag (refereegranskat)abstract
    • This paper proposes a method for calibrating of multi-camera systems where no natural reference points exist in the surrounding environment. Monitoring the air space at wind farms is our test case. The goal is to monitor the trajectories of flying birds to prevent them from colliding with rotor blades. Our camera calibration method is based on the observation of a portable artificial reference marker made out of a pulsed light source and a navigation satellite sensor module. The reference marker can determine and communicate its position in the world coordinate system at centimeter precision using navigartion sensors. Our results showed that simultaneous detection of the same marker in several cameras having overlapping field of views allowed us to determine the markers position in 3D world coordinate space with an accuracy of 3-4 cm. These experiments were made in the volume around a wind turbine at distances from cameras to marker within a range of 70 to 90 m.
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42.
  • Forsström, Stefan, 1984-, et al. (författare)
  • Specialanpassade kurser för yrkesverksamma ingenjörer : Erfarenheter och upplevelser
  • 2023
  • Ingår i: Bidrag från den 9:e utvecklingskonferensen för Sveriges ingenjörsutbildningar. - : Mälardalens universitet. - 9789174856200 ; , s. 348-353
  • Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
    • I dagens samhälle blir det allt viktigare att fortbilda sig under hela sitt yrkesverksamma liv. För att möta efterfrågan på det livslånga lärandet har Mittuniversitetet utvecklat och genomfört ett antal kurser som riktar sig mot yrkesverksamma ingenjörer. Detta arbete presenterar våra erfarenheter av att ge dessa kurser, med en tyngdpunkt på studenternas upplevelser. Syftet med detta är att bygga upp en vetenskaplig bas för vad vi gör som är bra, men även vad som kan förbättras och förändras. Målsättningen är att göra dessa specialanpassade kurser riktade mot yrkesverksamma ingenjörer så givande och flexibla som möjligt. Våra initiala resultat visar bland annat att studenternas negativa upplevelser ofta var kopplade till antagningsförfarandet och det praktiska genomförandet av kurserna. Man hade svårigheter med att hitta hur man skulle registrera sig på kursen och att tidsramen för registrering kunde vara ett problem. Läroplattformen uppfattades som svår att överblicka och det förekom även viss otydlighet gällande var undervisningen skulle äga rum. Den positiva responsen i utvärderingarna gällde främst det faktiska kursinnehållet, då man ansåg att uppgifter och kursmaterial var givande. Vidare uppskattades kursupplägget, att man kunde kombinera studierna med arbete. Framledes kommer vi att fortsätta med dessa utvärderingar i takt med att kurserna ges, och därefter anpassa vårt mottagande och kommunikationen med studenterna. Även kursupplägget ses över kontinuerligt via den återkoppling vi mottar. 
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43.
  • Gallo, Vincenzo, et al. (författare)
  • Metrological Characterization of a Clip Fastener assembly fault detection system based on Deep Learning
  • 2023
  • Ingår i: 2023 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). - : IEEE. - 9781665453837
  • Konferensbidrag (refereegranskat)abstract
    • In a time when Artificial Intelligence (AI) technologies are nearly ubiquitous, railway construction and maintenance systems have not fully grasped the capabilities of such technologies. Traditional railway inspection methods rely on inspection from experienced workers, making such tasks costly from both, the monetary and the time perspective. From an overview of the state-of-the-art research in this area regarding AI-based systems, we observed that their main focus was solely on detection accuracy of different railway components. However, if we consider the critical importance of railway fastening in the overall safety of the railway, there is a need for a thorough analysis of these AI-based methodologies, to define their uncertainty also from a metrological perspective. In this article we address this issue, proposing an image-based system that detects the rotational displacement of the fastened railway clips. Furthermore, we provide an uncertainty analysis of the measurement system, where the resulting uncertainty is of 0.42°, within the 3° error margin defined by the clip manufacturer. 
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44.
  • Hussain, Mazhar, 1980-, et al. (författare)
  • A Deep Learning Approach for Classification and Measurement of Hazardous Gases Using Multi-Sensor Data Fusion
  • 2023
  • Ingår i: 2023 IEEE Sensors Applications Symposium (SAS). - : IEEE conference proceedings.
  • Konferensbidrag (refereegranskat)abstract
    • Significant risks to public health and the environment are posed by the release of hazardous gases from industries such as pulp and paper. In this study, the aim was to develop a multi-sensor system with a minimal number of sensors to detect and identify hazardous gases. Training and test data for two gases, hydrogen sulfide and methyl mercaptan, which are known to contribute significantly to odors, were generated in a controlled laboratory environment. The performance of two deep learning models, a 1d-CNN and a stacked LSTM, for data fusion with different sensor configurations was evaluated. The performance of these models was compared with a baseline machine learning model. It was observed that the baseline model was outperformed by the deep learning models and achieved good accuracy with a four-sensor configuration. The potential of a cost-effective multi-sensor system and deep learning models in detecting and identifying hazardous gases is demonstrated by this study, which can be used to collect data from multiple locations and help guide the development of in-situ measurement systems for real-time detection and identification of hazardous gases at industrial sites. The proposed system has important implications for reducing pollution and protecting public health.
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45.
  • Hussain, Mazhar, 1980-, et al. (författare)
  • A Study on the Correlation between Change in the Geometrical Dimension of a Free-Falling Molten Glass Gob and Its Viscosity
  • 2022
  • Ingår i: Sensors. - : MDPI. - 1424-8220. ; 22:2, s. 661-661
  • Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
    • To produce flawless glass containers, continuous monitoring of the glass gob is required. It is essential to ensure production of molten glass gobs with the right shape, temperature, viscosity and weight. At present, manual monitoring is common practice in the glass container industry, which heavily depends on previous experience, operator knowledge and trial and error. This results in inconsistent measurements and consequently loss of production. In this article, a multi-camera based setup is used as a non-invasive real-time monitoring system. We have shown that under certain conditions, such as keeping the glass composition constant, it is possible to do in-line measurement of viscosity using sensor fusion to correlate the rate of geometrical change in the gob and its temperature. The correlation models presented in this article show that there is a strong correlation, i.e., 0.65, between our measurements and the projected viscosity.
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46.
  • Hussain, Mazhar, 1980-, et al. (författare)
  • Multi-Camera Based Setup for Geometrical Measurement of Free-Falling Molten Glass Gob
  • 2021
  • Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 21:4
  • Tidskriftsartikel (refereegranskat)abstract
    • High temperatures complicate the direct measurements needed for continuous characterization of the properties of molten materials such as glass. However, the assumption that geometrical changes when the molten material is in free-fall can be correlated with material characteristics such as viscosity opens the door to a highly accurate contactless method characterizing small dynamic changes. This paper proposes multi-camera setup to achieve accuracy close to the segmentation error associated with the resolution of the images. The experimental setup presented shows that the geometrical parameters can be characterized dynamically through the whole free-fall process at a frame rate of 600 frames per second. The results achieved show the proposed multi-camera setup is suitable for estimating the length of free-falling molten objects.
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47.
  • Hussain, Mazhar, 1980-, et al. (författare)
  • Selection of optimal parameters to predict fuel consumption of city buses using data fusion
  • 2022
  • Ingår i: 2022 IEEE Sensors Applications Symposium (SAS). - : IEEE. - 9781665409810
  • Konferensbidrag (refereegranskat)abstract
    • The study aims to explore the fuel consumption of city buses with data fusion using a dataset with multiple parameters such as travelled distance, weekday, hour of the day, drivers, buses, and routes, that influence the trip fuel consumption. In this study, manipulated parameters such as modified driver, bus and route identification numbers are used together with original parameters to identify the optimal combination of parameters that can be used to enhance the accuracy of the prediction model. Two regression methods, i.e. cubic SVM and artificial neural networks (ANN), are used to demonstrate the performance of the proposed approach. Results shows that a combination of original parameters and processed parameters increases the performance.
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48.
  • Imran, Muhammad, et al. (författare)
  • Analysis and Characterization of Embedded Vision Systems for Taxonomy Formulation
  • 2013
  • Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - USA : SPIE - International Society for Optical Engineering. - 9780819494290 ; , s. Art. no. 86560J-
  • Konferensbidrag (refereegranskat)abstract
    • The current trend in embedded vision systems is to propose bespoke solutions for specific problems as each application has different requirement and constraints. There is no widely used model or benchmark which aims to facilitate generic solutions in embedded vision systems. Providing such model is a challenging task due to the wide number of use cases, environmental factors, and available technologies. However, common characteristics can be identified to propose an abstract model. Indeed, the majority of vision applications focus on the detection, analysis and recognition of objects. These tasks can be reduced to vision functions which can be used to characterize the vision systems. In this paper, we present the results of a thorough analysis of a large number of different types of vision systems. This analysis led us to the development of a system’s taxonomy, in which a number of vision functions as well as their combination characterize embedded vision systems. To illustrate the use of this taxonomy, we have tested it against a real vision system that detects magnetic particles in a flowing liquid to predict and avoid critical machinery failure. The proposed taxonomy is evaluated by using a quantitative parameter which shows that it covers 95 percent of the investigated vision systems and its flow is ordered for 60 percent systems. This taxonomy will serve as a tool for classification and comparison of systems and will enable the researchers to propose generic and efficient solutions for same class of systems.
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49.
  • Imran, Muhammad, et al. (författare)
  • Architecture Exploration Based on Tasks Partitioning Between Hardware, Software and Locality for a Wireless Vision Sensor Node
  • 2012
  • Ingår i: International Journal of Distributed Systems and Technologies. - IGI Global, USA. : IGI Global. - 1947-3532 .- 1947-3540. ; 3:2, s. 58-71
  • Tidskriftsartikel (refereegranskat)abstract
    • Wireless Vision Sensor Networks (WVSNs) is an emerging field which consists of a number of Visual Sensor Nodes (VSNs). Compared to traditional sensor networks, WVSNs operates on two dimensional data, which requires high bandwidth and high energy consumption. In order to minimize the energy consumption, the focus is on finding energy efficient and programmable architectures for the VSN by partitioning the vision tasks among hardware (FPGA), software (Micro-controller) and locality (sensor node or server). The energy consumption, cost and design time of different processing strategies is analyzed for the implementation of VSN. Moreover, the processing energy and communication energy consumption of VSN is investigated in order to maximize the lifetime. Results show that by introducing a reconfigurable platform such as FPGA with small static power consumption and by transmitting the compressed images after pixel based tasks from the VSN results in longer battery lifetime for the VSN.
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50.
  • Imran, Muhammad, et al. (författare)
  • Architecture of Wireless Visual Sensor Node with Region of Interest Coding
  • 2012
  • Ingår i: Proceedings - 2012 IEEE 3rd International Conference on Networked Embedded Systems for Every Application, NESEA 2012. - : IEEE conference proceedings. - 9781467347235 ; , s. Art. no. 6474029-
  • Konferensbidrag (refereegranskat)abstract
    • The challenges involved in designing a wirelessVision Sensor Node include the reduction in processing andcommunication energy consumption, in order to maximize itslifetime. This work presents an architecture for a wireless VisionSensor Node, which consumes low processing andcommunication energy. The processing energy consumption isreduced by processing lightweight vision tasks on the VSN andby partitioning the vision tasks between the wireless VisionSensor Node and the server. The communication energyconsumption is reduced with Region Of Interest coding togetherwith a suitable bi-level compression scheme. A number ofdifferent processing strategies are investigated to realize awireless Vision Sensor Node with a low energy consumption. Theinvestigation shows that the wireless Vision Sensor Node, usingRegion Of Interest coding and CCITT group4 compressiontechnique, consumes 43 percent lower processing andcommunication energy as compared to the wireless Vision SensorNode implemented without Region Of Interest coding. Theproposed wireless Vision Sensor Node can achieve a lifetime of5.4 years, with a sample period of 5 minutes by using 4 AAbatteries.
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