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IoT and satellite sensor data integration for assessment of environmental variables: a case study on NO2
Jernej Cukjati, Domen Mongus, Krista Rizman Žalik, Borut Žalik, 2022, izvirni znanstveni članek

Opis: This paper introduces a novel approach to increase the spatiotemporal resolution of an arbitrary environmental variable. This is achieved by utilizing machine learning algorithms to construct a satellite-like image at any given time moment, based on the measurements from IoT sensors. The target variables are calculated by an ensemble of regression models. The observed area is gridded, and partitioned into Voronoi cells based on the IoT sensors, whose measurements are available at the considered time. The pixels in each cell have a separate regression model, and take into account the measurements of the central and neighboring IoT sensors. The proposed approach was used to assess NO2 data, which were obtained from the Sentinel-5 Precursor satellite and IoT ground sensors. The approach was tested with three different machine learning algorithms: 1-nearest neighbor, linear regression and a feed-forward neural network. The highest accuracy yield was from the prediction models built with the feed-forward neural network, with an RMSE of 15.49 ×10−6 mol/m2.
Ključne besede: Internet of Things, IoT, remote sensing, sensor integration, machine learning, ensemble method
Objavljeno v DKUM: 22.09.2023; Ogledov: 454; Prenosov: 20
.pdf Celotno besedilo (3,72 MB)
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3.
All Silica Micro-Fluidic Flow Injection Sensor System for Colorimetric Chemical Sensing
Vedran Budinski, Denis Đonlagić, 2021, izvirni znanstveni članek

Opis: This paper presents a miniature, all-silica, flow-injection sensor. The sensor consists of an optical fiber-coupled microcell for spectral absorption measurements and a microfluidic reagent injection system. The proposed sensor operates in back reflection mode and, with its compact dimensions, (no more than 200 µm in diameter) enables operation in small spaces and at very low flow rates of analyte and reagent, thus allowing for on-line or in-line colorimetric chemical sensing.
Ključne besede: optical fiber sensor, spectral absorption microcell, colorimetry
Objavljeno v DKUM: 31.07.2023; Ogledov: 412; Prenosov: 16
.pdf Celotno besedilo (4,40 MB)
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Miniature magneto-optic angular position sensor
Vedran Budinski, Simon Pevec, Stanislav Čampelj, Alenka Mertelj, Darja Lisjak, Denis Đonlagić, 2022, izvirni znanstveni članek

Opis: This Letter describes a miniature Fabry–Perot, contactless, magneto-optic sensor for angular position measurement. The sensor utilizes a magneto-optic fluid comprising barium hexaferrite nanoplatelets that become birefringent in the presence of an external magnetic field and a compact fiber-optic sensor system for tracking the liquid’s optical axis direction. An efficient temperature compensation system is provided which allows the use of otherwise highly temperature-sensitive magneto-optic liquids. An unambiguous measurement range of 90° and a resolution of better than 0.05° are demonstrated experimentally.
Ključne besede: Fiber optic sensor, magneto-optic sensor, angular position measurement
Objavljeno v DKUM: 12.05.2023; Ogledov: 567; Prenosov: 68
.pdf Celotno besedilo (3,76 MB)
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6.
Development of real-time ARM-based control system for autonomous platform Genesis : master's thesis
Hrvoje Pučak, 2021, magistrsko delo

Opis: Against the backdrop of technological advancement, machine learning and artificial intelligence, autonomous vehicles are also developing rapidly. In order for an autonomous vehicle to function properly, it is essential that the main system is provided lots of information about the vehicle, such as speed, orientation or battery state. Likewise, the system must control some actuators, such as drive motors and steering system. The specific objective of this thesis is to create an ARM-based module that will be a part of the Genesis II autonomous vehicle platform. The module is intended to accurately measure vehicle speed, estimate orientation and location, monitor the batteries, control drive motors and steering. The PCB layout of the module was developed by using Altium Designer, while the firmware was written in C programming language and by utilizing RTOS. Measurements were also performed to determine the accuracy of speed measurement process and to determine the accuracy of orientation and location estimations.
Ključne besede: ARM, autonomous vehicle, RTOS, Jetson TX2, magnetoresistive sensor, Genesis
Objavljeno v DKUM: 02.06.2021; Ogledov: 1440; Prenosov: 59
.pdf Celotno besedilo (1,83 MB)

7.
Design of an Embedded Position Sensor with Sub-mm Accuracy : magistrsko delo
Matej Nogić, 2019, magistrsko delo

Opis: This master’s thesis presents the development of a machine-vision based localization unit developed at Robert Bosch GmbH, Corporate Sector Research and Advance Engineering in Renningen, Germany. The localization unit was developed primarily for position detection purposes with three degrees of freedom in highly versatile manufacturing systems but has an immense potential to be used anywhere where a precise, low-cost localization method on a two-dimensional surface is required. The complete product development cycle was carried out, from the components selection, schematic and optical system design, to the development of machine vision algorithms, four-layer Printed Circuit Board design and evaluation using an industrial robot. Thanks to the use of a patented two-dimensional code pattern, the localization unit can cover a surface area of 49 km2. The size and speed optimized, self-developed machine-vision algorithms running on a Cortex-M7 microcontroller allow achieving an accuracy of 100 µm and 60 Hz refresh rate.
Ključne besede: localization, machine-vision, code pattern, image sensor, embedded system
Objavljeno v DKUM: 14.01.2020; Ogledov: 1263; Prenosov: 50
.pdf Celotno besedilo (18,20 MB)

8.
High safety pillars stability control using EL beam displacement sensors in Lipica II quarry
Jože Kortnik, Sunny Nwaubani, Andrej Kos, 2014, izvirni znanstveni članek

Opis: In underground Lipica II. quarry for the excavation of natural stone, a modified room-and-pillar mining method is used, that is adjusted to the conditions of the site. In order to support and ensure the stability of underground chambers high safety pillars (HSP) are used. These pillars are made of surrounding stone and therefore intersected by discontinuities. The discontinuities represent high risk to the stability of underground facilities and workmen below/ itself. To ensure their safety the stress and strain parameters in height safety pillars are continuously monitored using two vibrating wire (WV) stressmeters inside the high safety pillars and two EL (Electronic level) beam sensors on the surface of the high safety pillar VS3. In the time period October 2010/June 2012 absolute max. measured deviation with EL beam sensors were D1=0.9 mm and D2=1.1 mm, which does not compromise the stability of the high safety pillar VS3. This paper presents the procedures of wedges deformation monitoring in safety pillars with EL beam sensors in the Lipica II underground natural stone quarry.
Ključne besede: beam sensor, high saftey pillar, monitoring, natural stone, room and pillar mining method
Objavljeno v DKUM: 14.06.2018; Ogledov: 960; Prenosov: 73
.pdf Celotno besedilo (491,51 KB)
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9.
A wearable device and system for movement and biometric data acquisition for sports applications
Marko Kos, Iztok Kramberger, 2017, izvirni znanstveni članek

Opis: This paper presents a miniature wearable device and a system for detecting and recording the movement and biometric information of a user during sport activities. The wearable device is designed to be worn on a wrist and can monitor skin temperature and pulse rate. Furthermore, it can monitor arm movement and detect gestures using inertial measurement unit. The device can be used for various professional and amateur sport applications and for health monitoring. Because of its small size and minimum weight, it is especially appropriate for swing-based sports like tennis or golf, where any additional weight on the arms would most likely disturb the player and have some influence on the player’s performance. Basic signal processing is performed directly on the wearable device but for more complex signal analysis, the data can be uploaded via the Internet to a cloud service, where it can be processed by a dedicated application. The device is powered by a lightweight miniature LiPo battery and has about 6 h of autonomy at maximum performance.
Ključne besede: biometric data acquisition, inertial sensing, movement detection, pulse rate, sensor fusion, wearable
Objavljeno v DKUM: 03.08.2017; Ogledov: 1372; Prenosov: 521
.pdf Celotno besedilo (8,88 MB)
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10.
Intra-minute cloud passing forecasting based on a low cost iot sensor - a solution for smoothing the output power of PV power plants
Primož Sukič, Gorazd Štumberger, 2017, izvirni znanstveni članek

Opis: Clouds moving at a high speed in front of the Sun can cause step changes in the output power of photovoltaic (PV) power plants, which can lead to voltage fluctuations and stability problems in the connected electricity networks. These effects can be reduced effectively by proper short-term cloud passing forecasting and suitable PV power plant output power control. This paper proposes a low-cost Internet of Things (IoT)-based solution for intra-minute cloud passing forecasting. The hardware consists of a Raspberry PI Model B 3 with a WiFi connection and an OmniVision OV5647 sensor with a mounted wide-angle lens, a circular polarizing (CPL) filter and a natural density (ND) filter. The completely new algorithm for cloud passing forecasting uses the green and blue colors in the photo to determine the position of the Sun, to recognize the clouds, and to predict their movement. The image processing is performed in several stages, considering selectively only a small part of the photo relevant to the movement of the clouds in the vicinity of the Sun in the next minute. The proposed algorithm is compact, fast and suitable for implementation on low cost processors with low computation power. The speed of the cloud parts closest to the Sun is used to predict when the clouds will cover the Sun. WiFi communication is used to transmit this data to the PV power plant control system in order to decrease the output power slowly and smoothly.
Ključne besede: photovoltaic power plant, cloud passing forecasting, algorithm, sensor, Raspberry Pi, camera, wide-angle lens, optical filters, internet of things
Objavljeno v DKUM: 20.07.2017; Ogledov: 2674; Prenosov: 482
.pdf Celotno besedilo (8,15 MB)
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