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1.
Recent progress in non-enzymatic electroanalytical detection of pesticides based on the use of functional nanomaterials as electrode modifiers
Tanja Vrabelj, Matjaž Finšgar, 2022, review article

Abstract: This review presents recent advances in the non-enzymatic electrochemical detection and quantification of pesticides, focusing on the use of nanomaterial-based electrode modifiers and their corresponding analytical response. The use of bare glassy carbon electrodes, carbon paste electrodes, screen-printed electrodes, and other electrodes in this research area is presented. The sensors were modified with single nanomaterials, a binary composite, or triple and multiple nanocomposites applied to the electrodes’ surfaces using various application techniques. Regardless of the type of electrode used and the class of pesticides analysed, carbon-based nanomaterials, metal, and metal oxide nanoparticles are investigated mainly for electrochemical analysis because they have a high surface-to-volume ratio and, thus, a large effective area, high conductivity, and (electro)- chemical stability. This work demonstrates the progress made in recent years in the non-enzymatic electrochemical analysis of pesticides. The need for simultaneous detection of multiple pesticides with high sensitivity, low limit of detection, high precision, and high accuracy remains a challenge in analytical chemistry.
Keywords: electroanalysis, non-enzymatic sensors, nanomaterials, pesticides
Published in DKUM: 15.05.2025; Views: 0; Downloads: 3
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2.
An autonomous field robot Farmbeast - the field robot event 2023 edition
Gregor Popič, Urban Naveršnik, Jaša Jernej Rakun Kokalj, Erik Rihter, Jurij Rakun, 2024, original scientific article

Abstract: In contemporary agricultural automation, the demand for highly adaptive autonomous systems is rapidly increasing. Addressing this need, we introduce the latest iteration of FarmBeast, an advanced autonomous robot designed for precise navigation and operation within the complex terrain of cornfields. This paper details the technical specifications and functionalities of FarmBeast, developed by a Slovenian student team from the University of Maribor for the international Field Robot Event (FRE) 2023. The enhanced version features significant hardware and software upgrades, including a completely new robotic platform, a multichannel LIDAR system, an Xsens IMU, and advanced algorithms for efficient row navigation and weed removal. These integrated technologies aim to improve the efficiency and reliability of agricultural processes, reflecting the broader trend towards digitization and precision farming. Participation in international competitions like FRE provides a valuable platform for students to apply interdisciplinary knowledge, fostering the development of practical skills and understanding the interconnectedness of various scientific disciplines. As highlighted in the results section, FarmBeast performed notably compared to other 14 robots, securing top-five finishes in navigation, plant treatment, and obstacle detection tasks, demonstrating its capabilities in dynamic agricultural settings.
Keywords: precision agriculture, robotics, sensors, algorithms
Published in DKUM: 23.04.2025; Views: 0; Downloads: 3
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3.
Sensors and artificial intelligence methods and algorithms for human - computer intelligent interaction: a systematic mapping study
Boštjan Šumak, Saša Brdnik, Maja Pušnik, 2022, original scientific article

Abstract: To equip computers with human communication skills and to enable natural interaction between the computer and a human, intelligent solutions are required based on artificial intelligence (AI) methods, algorithms, and sensor technology. This study aimed at identifying and analyzing the state-of-the-art AI methods and algorithms and sensors technology in existing human–computer intelligent interaction (HCII) research to explore trends in HCII research, categorize existing evidence, and identify potential directions for future research. We conduct a systematic mapping study of the HCII body of research. Four hundred fifty-four studies published in various journals and conferences between 2010 and 2021 were identified and analyzed. Studies in the HCII and IUI fields have primarily been focused on intelligent recognition of emotion, gestures, and facial expressions using sensors technology, such as the camera, EEG, Kinect, wearable sensors, eye tracker, gyroscope, and others. Researchers most often apply deep-learning and instance-based AI methods and algorithms. The support sector machine (SVM) is the most widely used algorithm for various kinds of recognition, primarily an emotion, facial expression, and gesture. The convolutional neural network (CNN) is the often-used deep-learning algorithm for emotion recognition, facial recognition, and gesture recognition solutions.
Keywords: human–computer intelligent interaction, intelligent user interfaces, IUI, sensors, artificial intelligence
Published in DKUM: 31.03.2025; Views: 0; Downloads: 4
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4.
A short-range quasi-distributed strain and temperature sensing system utilizing a standard telecom laser diode
Jure Javornik, Denis Đonlagić, 2025, original scientific article

Abstract: This article presents a short-range fiber-optic quasi-distributed sensing device suitable for strain and temperature measurement. The sensing assembly consists of an fs laser inscribed reference mirror and a sensing array of equidistantly positioned mirrors. Utilization of the reference mirror and proper sensor geometry selection provides the possibility for a high-resolution spectral interrogation of the sensing array while relying on an ordinary, cost-effective distributed feedback (DFB) telecom laser diode. Beside the telecom DFB diode, the entire interrogation system includes only an additional detector, optical coupler, analog interface and a microcontroller. Measurement resolution better than 1 µε was demonstrated experimentally at a sampling rate exceeding 65 samples per second, while utilizing a sensing device with a typical length of 50 mm and spatial resolution of approximately 2 mm. To demonstrate the application potential of the proposed measuring device, a few different packages and sensor configurations were demonstrated and tested, including a system for tactile sensing applications and a short-range quasi-distributed temperature measurement probe.
Keywords: optical fiber sensors, short-range quasi-distributed fiber-optic sensor, strain/temperature sensing device, cost-effective interrogation system, tactile sensing, phase subtraction
Published in DKUM: 03.02.2025; Views: 0; Downloads: 11
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Development of biomimetic sensors to determine the functionality of in vitro cell models
Matjaž Frangež, Noah Emil Glisik, Maša Kaiser, Jaro Vezjak, Matic Žnidaršič, Tanja Zidarič, Tina Maver, 2024, original scientific article

Abstract: Advances in biomedical science have enabled the development of in vitro models that mimic human tissues. Non-invasive real-time monitoring of these models would provide valuable insights without disrupting the cellular environment. This study explores the use of molecularly imprinted polymers (MIPs) for this purpose, focusing on insulin and lactate as biomarkers of cellular metabolism. MIP sensors were created by electropolymerizing pyrrole around insulin or lactate templates on carbon electrodes. The sensors showed high sensitivity and selectivity, with detection ranges of 20.0–70.0 pM for insulin (LOD: 2.41 pM) and 0.5–3.0 mM for lactate. These findings highlight MIPs’ potential for personalized diagnostics and therapy monitoring.
Keywords: biomimetic sensors, molecular imprinting, polypyrrole matrix, insulin, MIP sensor
Published in DKUM: 24.01.2025; Views: 0; Downloads: 15
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7.
Potentiometric surfactant sensor with a pt-doped acid-activated multi-walled carbon nanotube-based ionophore nanocomposite
Nada Glumac, Milan Momčilović, Iztok Kramberger, Darko Štraus, Nikola Sakač, Elvira Kovač-Andrić, Bojan Đurin, Marija Kraševac Sakač, Kristina Đambić, Marija Jozanović, 2024, original scientific article

Abstract: Two new surfactant sensors were developed by synthesizing Pt-doped acid-activated multiwalled carbon nanotubes (Pt@MWCNTs). Two different ionophores using Pt@MWCNTs, a new plasticizer, and (a) cationic surfactant 1,3-dihexadecyl-1H-benzo[d]imidazol-3-ium-DHBI (Pt@MWCNT-DHBI ionophore) and (b) anionic surfactant dodecylbenzenesulfonate-DBS (Pt@MWCNT-DBS ionophore) composites were successfully synthesized and characterized. Both surfactant sensors showed a response to anionic surfactants (dodecylsulfate (SDS) and DBS) and cationic surfactants (cetylpyridinium chloride (CPC) and hexadecyltrimethylammonium bromide (CTAB)). The Pt@MWCNT-DBS sensor showed lower sensitivity than expected with the sub-Nernstian response of ≈23 mV/decade of activity for CPC and CTAB and ≈33 mV/decade of activity for SDS and DBS. The Pt@MWCNTDHBI surfactant sensor had superior response properties, including a Nernstian response to SDS (59.1 mV/decade) and a near-Nernstian response to DBS (57.5 mV/decade), with linear response regions for both anionic surfactants down to ≈2 × 10−6 M. The Pt@MWCNT-DHBI was also useful in critical micellar concentration (CMC) detection. Common anions showed very low interferences with the sensor. The sensor was successfully employed for the potentiometric titration of a technical grade cationic surfactant with good recoveries. The content of cationic surfactants was measured in six samples of complex commercial detergents. The Pt@MWCNT-DHBI surfactant sensor showed good agreement with the ISE surfactant sensor and classical two-phase titration and could be used as an analytical tool in quality control
Keywords: potentiometric surfactant sensor, metal-doped MWCNT, surfactants, carbon nanocomposite, sensors
Published in DKUM: 23.08.2024; Views: 110; Downloads: 11
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8.
Sensor fusion-based approach for the field robot localization on Rovitis 4.0 vineyard robot
Jurij Rakun, Matteo Pantano, Peter Lepej, Miran Lakota, 2022, original scientific article

Abstract: This study proposed an approach for robot localization using data from multiple low-cost sensors with two goals in mind, to produce accurate localization data and to keep the computation as simple as possible. The approach used data from wheel odometry, inertial-motion data from the Inertial Motion Unit (IMU), and a location fix from a Real-Time Kinematics Global Positioning System (RTK GPS). Each of the sensors is prone to errors in some situations, resulting in inaccurate localization. The odometry is affected by errors caused by slipping when turning the robot or putting it on slippery ground. The IMU produces drifts due to vibrations, and RTK GPS does not return to an accurate fix in (semi-) occluded areas. None of these sensors is accurate enough to produce a precise reading for a sound localization of the robot in an outdoor environment. To solve this challenge, sensor fusion was implemented on the robot to prevent possible localization errors. It worked by selecting the most accurate readings in a given moment to produce a precise pose estimation. To evaluate the approach, two different tests were performed, one with robot localization from the robot operating system (ROS) repository and the other with the presented Field Robot Localization. The first did not perform well, while the second did and was evaluated by comparing the location and orientation estimate with ground truth, captured by a hovering drone above the testing ground, which revealed an average error of 0.005 m±0.220 m in estimating the position, and 0.6°±3.5° when estimating orientation. The tests proved that the developed field robot localization is accurate and robust enough to be used on a ROVITIS 4.0 vineyard robot.
Keywords: localization, odometry, IMU, RTK GPS, vineyard, robot, sensors fusion, ROS, precision farming
Published in DKUM: 02.07.2024; Views: 123; Downloads: 21
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9.
Measurements of Small Frequency Differences by Dual Mode 4 MHz Quartz Sensors
Vojko Matko, 2023, original scientific article

Abstract: We proposed a method for measuring frequency differences of the order of a few Hz with an experimental error lower than 0.0001% by using two 4 MHz quartz oscillators, the frequencies of which are very close (a few 10 Hz difference) due to the dual mode operation (differential mode with two temperature-compensated signal frequencies or a mode with one signal and one reference frequency). We compared the existing methods for measuring frequency differences with the new method which is based on counting the number of transitions through zero within one beat period of the signal. The measuring procedure requires equal experimental conditions (temperature, pressure, humidity, parasitic impedances etc.) for both quartz oscillators. To ensure equal resonant conditions for oscillation two quartz crystals are needed, which form a temperature pair. The frequencies and resonant conditions of both oscillators must be almost equal, which is achieved by an external inductance or capacitance. In such a way, we minimized all the external effects and ensured highly stable oscillations and high sensitivity of the differential sensors. The counter detects one beat period by an external gate signal former. By using the method of counting transitions through zero within one beat period, we reduced the measuring error by three orders of magnitude, compared to the existing methods.
Keywords: small frequency difference measurement, temperature-compensated quartz sensors, differential sensors, quartz oscillators, transitions-through-zero method
Published in DKUM: 26.03.2024; Views: 357; Downloads: 246
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10.
The development of an electropolymerized, molecularly imprinted polymer (MIP) sensor for insulin determination using single-drop analysis
Tanja Zidarič, David Majer, Tina Maver, Matjaž Finšgar, Uroš Maver, 2023, original scientific article

Abstract: An electrochemical sensor for the detection of insulin in a single drop (50 μL) was developed based on the concept of molecularly imprinted polymers (MIP). The synthetic MIP receptors were assembled on a screen-printed carbon electrode (SPCE) by the electropolymerization of pyrrole (Py) in the presence of insulin (the protein template) using cyclic voltammetry. After electropolymerization, insulin was removed from the formed polypyrrole (Ppy) matrix to create imprinting cavities for the subsequent analysis of the insulin analyte in test samples. The surface characterization, before and after each electrosynthesis step of the MIP sensors, was performed using atomic force microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The performance of the developed MIP–SPCE sensor was evaluated using a single drop of solution containing K3Fe(CN)6 and the square-wave voltammetry technique. The MIP–SPCE showed a linear concentration range of 20.0–70.0 pM (R2 = 0.9991), a limit of detection of 1.9 pM, and a limit of quantification of 6.2 pM. The rapid response time to the protein target and the portability of the developed sensor, which is considered a disposable MIP-based system, make this MIP–SPCE sensor a promising candidate for point-of-care applications. In addition, the MIP–SPCE sensor was successfully used to detect insulin in a pharmaceutical sample. The sensor was deemed to be accurate (the average recovery was 108.46%) and precise (the relative standard deviation was 7.23%).
Keywords: electrochemical sensors, electropolymerisation, electron microscopy
Published in DKUM: 14.03.2024; Views: 335; Downloads: 46
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