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Journal articles on the topic 'Object Detecting Sensors'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Jung, Sejung, Won Hee Lee, and Youkyung Han. "Change Detection of Building Objects in High-Resolution Single-Sensor and Multi-Sensor Imagery Considering the Sun and Sensor’s Elevation and Azimuth Angles." Remote Sensing 13, no. 18 (2021): 3660. http://dx.doi.org/10.3390/rs13183660.

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Building change detection is a critical field for monitoring artificial structures using high-resolution multitemporal images. However, relief displacement depending on the azimuth and elevation angles of the sensor causes numerous false alarms and misdetections of building changes. Therefore, this study proposes an effective object-based building change detection method that considers azimuth and elevation angles of sensors in high-resolution images. To this end, segmentation images were generated using a multiresolution technique from high-resolution images after which object-based building

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Jeong, Seonghark, Minseok Ko, and Jungha Kim. "LiDAR Localization by Removing Moveable Objects." Electronics 12, no. 22 (2023): 4659. http://dx.doi.org/10.3390/electronics12224659.

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In this study, we propose reliable Light Detection and Ranging (LiDAR) mapping and localization via the removal of moveable objects, which can cause noise for autonomous driving vehicles based on the Normal Distributions Transform (NDT). LiDAR measures the distances to objects such as parked and moving cars and objects on the road, calculating the time of flight required for the sensor’s beam to reflect off an object and return to the system. The proposed localization system uses LiDAR to implement mapping and matching for the surroundings of an autonomous vehicle. This localization is applied

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Yoon, Sungan, Ahmad Jalal, and Jeongho Cho. "MODAN: Multifocal Object Detection Associative Network for Maritime Horizon Surveillance." Journal of Marine Science and Engineering 11, no. 10 (2023): 1890. http://dx.doi.org/10.3390/jmse11101890.

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In maritime surveillance systems, object detection plays a crucial role in ensuring the security of nearby waters by tracking the movement of various objects, such as ships and aircrafts, that are found at sea, detecting illegal activities and preemptively countering or predicting potential risks. Using vision sensors such as cameras to monitor the sea can help to identify the shape, size, and color of objects, enabling the precise analysis of maritime situations. Additionally, vision sensors can monitor or track small ships that may escape radar detection. However, objects located at consider

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Rakesh, L., V. Priyanka, K. Pavan Kumar, N. Mahesh, and K. Sai Kiran. "Radar Based Object Detection using Ultrasonic Sensor." Journal of Remote Sensing GIS & Technology 8, no. 2 (2022): 7–14. http://dx.doi.org/10.46610/jorsgt.2022.v08i02.002.

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Aurdino-controlled radar is the subject of this project. A servo motor and an ultrasonic sensor are the essential components of this RADAR system. Components of the system primary role of the system is to detect something. Objects that fall within the specified parameters Ultrasonic sensors are built inside the servo motor. It rotates 180 degrees and uses software to show a visual representation. It's referred to as Processing IDE. A graphical representation of the data is provided by the Processing IDE. The angle or location of the object is also indicated, as well as its distance. This syste

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Reda, A. M., N. El-Sheimy, and A. Moussa. "DEEP LEARNING FOR OBJECT DETECTION USING RADAR DATA." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-1/W1-2023 (December 5, 2023): 657–64. http://dx.doi.org/10.5194/isprs-annals-x-1-w1-2023-657-2023.

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Abstract. Recently, Deep learning algorithms are becoming increasingly instrumental in autonomous driving by identifying and acknowledging road entities to ensure secure navigation and decision-making. Autonomous car datasets play a vital role in developing and evaluating perception systems. Nevertheless, the majority of current datasets are acquired using Light Detection and Ranging (LiDAR) and camera sensors. Utilizing deep neural networks yields remarkable outcomes in object recognition, especially when applied to analyze data from cameras and LiDAR sensors which perform poorly under advers

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Ma, Tian J., and Robert J. Anderson. "Remote Sensing Low Signal-to-Noise-Ratio Target Detection Enhancement." Sensors 23, no. 6 (2023): 3314. http://dx.doi.org/10.3390/s23063314.

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In real-time remote sensing application, frames of data are continuously flowing into the processing system. The capability of detecting objects of interest and tracking them as they move is crucial to many critical surveillance and monitoring missions. Detecting small objects using remote sensors is an ongoing, challenging problem. Since object(s) are located far away from the sensor, the target’s Signal-to-Noise-Ratio (SNR) is low. The Limit of Detection (LOD) for remote sensors is bounded by what is observable on each image frame. In this paper, we present a new method, a “Multi-frame Movin

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Hahn, Bongsu. "Research and Conceptual Design of Sensor Fusion for Object Detection in Dense Smoke Environments." Applied Sciences 12, no. 22 (2022): 11325. http://dx.doi.org/10.3390/app122211325.

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In this paper, we propose a conceptual framework for a sensor fusion system that can detect objects in a dense smoke environment with a visibility of less than 1 m. Based on the review of several articles, we determined that by using a single thermal IR camera, a single Frequency-Modulated Continuous-Wave (FMCW) radar, and multiple ultrasonic sensors simultaneously, the system can overcome the challenges of detecting objects in dense smoke. The four detailed methods proposed are as follows: First, a 3D ultrasonic sensor system that detects the 3D position of an object at a short distance and i

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Schlemmer, Matthias J., Georg Biegelbauer, and Markus Vincze. "Rethinking Robot Vision – Combining Shape and Appearance." International Journal of Advanced Robotic Systems 4, no. 3 (2007): 29. http://dx.doi.org/10.5772/5691.

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Equipping autonomous robots with vision sensors provides a multitude of advantages by simultaneously bringing up difficulties with regard to different illumination conditions. Furthermore, especially with service robots, the objects to be handled must somehow be learned for a later manipulation. In this paper we summarise work on combining two different vision sensors, namely a laser range scanner and a monocular colour camera, for shape-capturing, detecting and tracking of objects in cluttered scenes without the need of intermediate user interaction. The use of different sensor types provides

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Kasinath, S., S. K. Stephan, Edward Lisha, K.G. Parthive, and R. Remya. "Enhanced Blind Navigation using YOLO and Sensor Fusion." Recent Innovations in Wireless Network Security 7, no. 3 (2025): 1–10. https://doi.org/10.5281/zenodo.15516516.

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<em>Blind navigation remains a significant challenge for visually impaired individuals, particularly in complex and dynamic environments such as crowded streets, public transport, and indoor spaces. Traditional mobility aids like canes and guide dogs offer assistance but have limitations in detecting fast-moving obstacles or recognizing objects beyond immediate reach. With advancements in artificial intelligence (AI) and sensor technologies, there is an opportunity to develop smarter, real-time navigation solutions that enhance mobility and independence for visually impaired individuals.</em>

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Wahyu Rizki Ananda, Abdul Jabbar Lubis, and Ummul Khair. "Implementation of Motion Sensors and Buzzers on Robots to Detect Object Movement." Journal of Artificial Intelligence and Engineering Applications (JAIEA) 4, no. 2 (2025): 1354–61. https://doi.org/10.59934/jaiea.v4i2.907.

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Technological advances in this modern era have brought many significant changes in various fields, including security and surveillance. One innovation that stands out is the use of robots to detect object movement. This research aims to implement motion sensors and buzzers on robots to detect the movement of objects around them. This system uses a Passive Infrared (PIR) sensor to detect changes in infrared radiation produced by object movement, and a buzzer as an auditory warning device when movement is detected. In addition, the robot is designed to operate automatically by identifying moveme

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Wang, Gai Fang, Feng Feng Fan, Xi Tao Xing, and Yong Wang. "Design and Implementation of Digital Sensor Simulator." Applied Mechanics and Materials 411-414 (September 2013): 1581–87. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.1581.

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With the rapid development of sensor technology recently, sensors have been applied to various fields for detecting object states, e.g. intelligent agriculture, intelligent power, intelligent city, the Internet of Things, etc., and have becoming more and more critical for dynamic data acquisition. Due to detection environment, detection technology, costs and other factors, access to actual sensors for developing or debugging a sensor application may cause additional costs and time. Meanwhile, testing new sensor applications and protocols needs appropriate feasible ways with low costs and short

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Zhang, Yaqiang, Zhenhua Wang, Lin Meng, and Zhangbing Zhou. "Boundary Region Detection for Continuous Objects in Wireless Sensor Networks." Wireless Communications and Mobile Computing 2018 (2018): 1–13. http://dx.doi.org/10.1155/2018/5176569.

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Industrial Internet of Things has been widely used to facilitate disaster monitoring applications, such as liquid leakage and toxic gas detection. Since disasters are usually harmful to the environment, detecting accurate boundary regions for continuous objects in an energy-efficient and timely fashion is a long-standing research challenge. This article proposes a novel mechanism for continuous object boundary region detection in a fog computing environment, where sensing holes may exist in the deployed network region. Leveraging sensory data that have been gathered, interpolation algorithms h

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Gao, Yuhan, Peng Wang, Xiaoyan Li, et al. "MonoDFNet: Monocular 3D Object Detection with Depth Fusion and Adaptive Optimization." Sensors 25, no. 3 (2025): 760. https://doi.org/10.3390/s25030760.

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Monocular 3D object detection refers to detecting 3D objects using a single camera. This approach offers low sensor costs, high resolution, and rich texture information, making it widely adopted. However, monocular sensors face challenges from environmental factors like occlusion and truncation, leading to reduced detection accuracy. Additionally, the lack of depth information poses significant challenges for predicting 3D positions. To address these issues, this paper presents a monocular 3D object detection method based on improvements to MonoCD, designed to enhance detection accuracy and ro

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Shorkin, Nikita E., and Kirill L. Tassov. "METHOD FOR DETECTING FOREIGN OBJECTS ON THE RUNWAY BY VIDEO STREAM." RSUH/RGGU Bulletin. Series Information Science. Information Security. Mathematics, no. 1 (2022): 46–62. http://dx.doi.org/10.28995/2686-679x-2022-1-46-62.

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The article considers a problem of detecting foreign objects on the runway. Existing automated systems that solve that issue are based on cameras and radar sensors. However, in those systems, cameras are used only for visual confirmation and are rarely used directly to perform detection. The use of video information for object detection will increase the degree of automation of such systems. The article proposes a method for detecting foreign objects in a video stream based on threshold segmentation. The method works with data from static cameras and can be used both in systems with only camer

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Zhuchenko, Anatoliy, Oleksiy Kuchkin, Artem Sazonov, and Danylo Zghurskyi. "Energy efficient RANSAC algorithm for flat surface detection in point clouds." Energy engineering and control systems 9, no. 1 (2023): 47–53. http://dx.doi.org/10.23939/jeecs2023.01.047.

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Mobile robots control systems achieve greater efficiency through the use of robust environmental analysis algorithms based on data collected from optical sensors such as depth cameras, Light Detection and Ranging sensors (LIDARs). These data sources provide information about control object environment in point cloud. The work of such algorithms, as a rule, is aimed at detecting the objects of interest and searching for the specified objects, as well as relocating its own position on the scene. There are many different approaches for solving object detection problem in point clouds, but most of

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Sazonov, Artem, Oleksiy Kuchkin, Anatoliy Zhuchenko, and Danylo Zghurskyi. "Energy Efficient RANSAC Algorithm for Flat Surface Detection in Point Clouds." Energy Engineering and Control Systems 9, no. 1 (2023): 47–53. https://doi.org/10.23939/jeecs2023.01.047.

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Mobile robots control systems achieve greater efficiency through the use of robust environmental analysis algorithms based on data collected from optical sensors such as depth cameras, Light Detection and Ranging sensors (LIDARs). These data sources provide information about control object environment in point cloud. The work of such algorithms, as a rule, is aimed at detecting the objects of interest and searching for the specified objects, as well as relocating its own position on the scene. There are many different approaches for solving object detection problem in point clouds, but most of

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Helwig, Martin, Yun Xu, Uwe Hentschel, Anja Winkler, and Niels Modler. "Numerical and Experimental Investigation of Time-Domain-Reflectometry-Based Sensors for Foreign Object Detection in Wireless Power Transfer Systems." Sensors 23, no. 23 (2023): 9425. http://dx.doi.org/10.3390/s23239425.

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Foreign object detection (FOD) is considered a key method for detecting objects in the air gap of a wireless charging system that could pose a risk due to strong inductive heating. This paper describes a novel method for the detection of metallic objects utilizing the principle of electric time domain reflectometry. Through an analytical, numerical and experimental investigation, two key parameters for the design of transmission lines are identified and investigated with respect to the specific constraints of inductive power transfer. For this purpose, a transient electromagnetic simulation mo

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Imron, Imron, Bagus Satria, and Nuraini Nuraini. "THE DESIGN OF PEOPLE FOLLOWER ROBOT TO TRANSPORT HARVESTS USING YOLO V5 DETECTION." SemanTIK : Teknik Informasi 9, no. 2 (2023): 173. http://dx.doi.org/10.55679/semantik.v9i2.45261.

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Robots transporting harvested products is commonly use automatic navigation systems with sensors such as lidar, cameras and ultrasonic proximity sensors are important for detecting obstacles and avoiding collisions. Mapping and positioning algorithm are crucial for precise the robot determine position in the field. A dependable drive system, adaptable to diverse terrains, and a robust motor are essential components. Efficient energy requirements must be addressed by using long-lasting battery systems and, where possible, automatic charging solutions. Robots picking mechanisms that can adapt to

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Mirdanies, Midriem, and Roni Permana Saputra. "Experimental review of distance sensors for indoor mapping." Journal of Mechatronics, Electrical Power, and Vehicular Technology 8, no. 2 (2017): 85. http://dx.doi.org/10.14203/j.mev.2017.v8.85-94.

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One of the most important required ability of a mobile robot is perception. An autonomous mobile robot has to be able to gather information from the environment and use it for supporting the accomplishing task. One kind of sensor that essential for this process is distance sensor. This sensor can be used for obtaining the distance of any objects surrounding the robot and utilize the information for localizing, mapping, avoiding obstacles or collisions and many others. In this paper, some of the distance sensor, including Kinect, Hokuyo UTM-30LX, and RPLidar were observed experimentally. Streng

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Borgmann, B., M. Hebel, M. Arens, and U. Stilla. "USAGE OF MULTIPLE LIDAR SENSORS ON A MOBILE SYSTEM FOR THE DETECTION OF PERSONS WITH IMPLICIT SHAPE MODELS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2 (May 30, 2018): 125–31. http://dx.doi.org/10.5194/isprs-archives-xlii-2-125-2018.

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The focus of this paper is the processing of data from multiple LiDAR (light detection and ranging) sensors for the purpose of detecting persons in that data. Many LiDAR sensors (e.g., laser scanners) use a rotating scan head, which makes it difficult to properly timesynchronize multiple of such LiDAR sensors. An improper synchronization between LiDAR sensors causes temporal distortion effects if their data are directly merged. A merging of data is desired, since it could increase the data density and the perceived area. For the usage in person and object detection tasks, we present an alterna

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Garrote, Luís, João Perdiz, Luís A. da Silva Cruz, and Urbano J. Nunes. "Point Cloud Compression: Impact on Object Detection in Outdoor Contexts." Sensors 22, no. 15 (2022): 5767. http://dx.doi.org/10.3390/s22155767.

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Increasing demand for more reliable and safe autonomous driving means that data involved in the various aspects of perception, such as object detection, will become more granular as the number and resolution of sensors progress. Using these data for on-the-fly object detection causes problems related to the computational complexity of onboard processing in autonomous vehicles, leading to a desire to offload computation to roadside infrastructure using vehicle-to-infrastructure communication links. The need to transmit sensor data also arises in the context of vehicle fleets exchanging sensor d

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Ha, Sungjae, Dongwoo Lee, Hoijun Kim, et al. "Neural Network for Metal Detection Based on Magnetic Impedance Sensor." Sensors 21, no. 13 (2021): 4456. http://dx.doi.org/10.3390/s21134456.

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The efficiency of the metal detection method using deep learning with data obtained from multiple magnetic impedance (MI) sensors was investigated. The MI sensor is a passive sensor that detects metal objects and magnetic field changes. However, when detecting a metal object, the amount of change in the magnetic field caused by the metal is small and unstable with noise. Consequently, there is a limit to the detectable distance. To effectively detect and analyze this distance, a method using deep learning was applied. The detection performances of a convolutional neural network (CNN) and a rec

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Mihai-Alin, Bîtea, and Dolga Valer. "Object Detection with Ultrasound Sensors in Mobile Robots Working Area." Applied Mechanics and Materials 239-240 (December 2012): 84–87. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.84.

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The ultrasound sensor imitates the bats and the other animals’ abilities to use ultrasound frequencies for navigation in order to determine the distance between them and the obstacles. These sensors are recommended to be used for difficult applications, in gasiform environments and represent one of the mobile robot’s sensor options. Our purpose of this study lies in presenting a method of detecting the distance between the mobile robot and obstacles and recording it, and in the same time the possibility of implementing it in order for it to be used by individuals (subjects) in applied studies.

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Russell, R. Andrew, and Jaury Adi Wijaya. "Recognising and manipulating objects using data from a whisker sensor array." Robotica 23, no. 5 (2005): 653–64. http://dx.doi.org/10.1017/s0263574704000748.

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For many biological creatures sensory whiskers are an effective means of detecting and recognising nearby objects. The project described in this paper has the aim of demonstrating that whisker sensors can be used as a similarly effective form of robot sensing. Many mobile robots have used whiskers as simple switches to warn of an imminent collision. However, these devices cannot provide the detailed surface profile information required to recognise and accurately locate objects. Several research groups have built advanced whisker sensors that can determine the position of a contact along the l

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Ghayal, Sumedh V., Yamini A. Bawanthade, Swapnil B. Sonkamble, Dr Tarun Shrivasatava, Saurabh L. Katore, and Megha D. Gedam. "Iot Based Sensor Network for Crack & Bend Monitoring in Railway Track." International Journal for Research in Applied Science and Engineering Technology 10, no. 12 (2022): 1774–79. http://dx.doi.org/10.22214/ijraset.2022.48319.

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Abstract: In India railway is one of the most common means of transport, which is the fourth largest railway community in the world. Even though Indian railways has an outstanding boom, it remains plagued because of some of the major issues like problem in gate crossing, fire accidents and problem in the track which remains unmonitored causing derailment. The tracks contract and expand due to changes in season. Due to this crack may develop on the track. This proposed system identifies the cracks and the obstacles on the track using sensors The project railway crack and object detection are a

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Jung, Sukwoo, Youngmok Cho, Doojun Kim, and Minho Chang. "Moving Object Detection from Moving Camera Image Sequences Using an Inertial Measurement Unit Sensor." Applied Sciences 10, no. 1 (2019): 268. http://dx.doi.org/10.3390/app10010268.

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This paper describes a new method for the detection of moving objects from moving camera image sequences using an inertial measurement unit (IMU) sensor. Motion detection systems with vision sensors have become a global research subject recently. However, detecting moving objects from a moving camera is a difficult task because of egomotion. In the proposed method, the interesting points are extracted by a Harris detector, and the background and foreground are classified by epipolar geometry. In this procedure, an IMU sensor is used to calculate the initial fundamental matrix. After the featur

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Zhang, Biwei, Murat Simsek, Michel Kulhandjian, and Burak Kantarci. "Enhancing the Safety of Autonomous Vehicles in Adverse Weather by Deep Learning-Based Object Detection." Electronics 13, no. 9 (2024): 1765. http://dx.doi.org/10.3390/electronics13091765.

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Recognizing and categorizing items in weather-adverse environments poses significant challenges for autonomous vehicles. To improve the robustness of object-detection systems, this paper introduces an innovative approach for detecting objects at different levels by leveraging sensors and deep learning-based solutions within a traffic circle. The suggested approach improves the effectiveness of single-stage object detectors, aiming to advance the performance in perceiving autonomous racing environments and minimizing instances of false detection and low recognition rates. The improved framework

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Park, Jaehyeon, and Jedo Kim. "Movement tracking using asymmetric impedance meta-surface based on Helmholtz resonator." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 268, no. 4 (2023): 4239–44. http://dx.doi.org/10.3397/in_2023_0599.

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Acoustic sensors are one of the most commonly used sensors for detecting obstacles in mobile robots and vehicles by providing distance information of the obstacles in their path. However, although a single sensor can determine an object's distance, two or more sensors must be used to detect the movement of an object. Here, we propose a method to determine the distance and direction of an object traveling to a single sensor using an asymmetrically formed acoustic field. The acoustic field is formed by impedance-varying acoustic meta-surface using an asymmetric Helmholtz resonator array. We pres

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Zhang, Bing, Bowen Wang, Yunkai Li, and Shaowei Jin. "Magnetostrictive tactile sensor of detecting friction and normal force for object recognition." International Journal of Advanced Robotic Systems 17, no. 4 (2020): 172988142093232. http://dx.doi.org/10.1177/1729881420932327.

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Tactile information is valuable in determining properties of objects that are inaccessible from visual perception. A new type of tangential friction and normal contact force magnetostrictive tactile sensor was developed based on the inverse magnetostrictive effect, and the force output model has been established. It can measure the exerted force in the range of 0–4 N, and it has a good response to the dynamic force in cycles of 0.25–0.5 s. We present a tactile perception strategy that a manipulator with tactile sensors in its grippers manipulates an object to measure a set of tactile features.

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Chen, Minwei, Yajun Liu, Zenghui Zhang, and Weiwei Guo. "RCRFNet: Enhancing Object Detection with Self-Supervised Radar–Camera Fusion and Open-Set Recognition." Sensors 24, no. 15 (2024): 4803. http://dx.doi.org/10.3390/s24154803.

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Robust object detection in complex environments, poor visual conditions, and open scenarios presents significant technical challenges in autonomous driving. These challenges necessitate the development of advanced fusion methods for millimeter-wave (mmWave) radar point cloud data and visual images. To address these issues, this paper proposes a radar–camera robust fusion network (RCRFNet), which leverages self-supervised learning and open-set recognition to effectively utilise the complementary information from both sensors. Specifically, the network uses matched radar–camera data through a fr

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Zhang, Shuwei. "Heavy Metal Ions Detection in Cosmetics: Nanogold Based Sensors." Highlights in Science, Engineering and Technology 73 (November 29, 2023): 418–22. http://dx.doi.org/10.54097/hset.v73i.14039.

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Makeup has become an important way for people to pursue beauty. At the same time, heavy metal pollution in cosmetics is receiving increasing attention. In order to improve the quality of cosmetics and promote the development of cosmetics industry, finding a convenient and obvious method to detect heavy metals ions in cosmetics has great significance. Large numbers of detection methods have been established, among which the most noteworthy is the detection method based on nanogold sensors. Nanogold is a new type of material with unique properties at the nanoscale. Therefore, sensors based on na

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Mansurov, Tofig Magomed ogly, Rahman Salman Mammadov, and Elnur Tofig ogly Mansurov. "FIBER-OPTIC SENSOR OF THE OBJECT PERIMETER PROTECTION SYSTEM." SYNCHROINFO JOURNAL 8, no. 5 (2022): 2–6. http://dx.doi.org/10.36724/2664-066x-2022-8-5-2-6.

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An analysis of the existing fiber-optic sensors of the system for detecting unauthorized entry into the territory of a protected facility was carried out. It is noted that an attractive feature of such sensors is immunity to electromagnetic radiation and electrical safety. As a result of the analysis, it was concluded that the well-known fiber optic sensors alone can detect only the fact of unauthorized entry, and with a multizone security system – both the fact and the zone of unauthorized entry, but not the reason for the operation of the fiber optic sensor, i.e. parameter of the offending o

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Wu, Qizhou, Yong Jin, Zhaoba Wang, and Zhaoqian Xiao. "Spatial Spectroscopy Approach for Detection of Internal Defect of Component without Zero-Position Sensors." Journal of Spectroscopy 2016 (2016): 1–5. http://dx.doi.org/10.1155/2016/5958236.

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Conventional approach to detect the internal defect of a component needs sensors to mark the “zero” positions, which is time-consuming and lowers down the detecting efficiency. In this study, we proposed a novelty approach that uses spatial spectroscopy to detect internal defect of objects without zero-position sensors. Specifically, the spatial variation wave of distance between the detecting source and object surface is analyzed, from which a periodical cycle is determined with the correlative approaches. Additionally, a wavelet method is adopted to reduce the noise of the periodic distance

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Marzuki, Marza Ihsan, Rinny Rahmania, Penny Dyah Kusumaningrum, et al. "Fishing boat detection using Sentinel-1 validated with VIIRS Data." IOP Conference Series: Earth and Environmental Science 925, no. 1 (2021): 012058. http://dx.doi.org/10.1088/1755-1315/925/1/012058.

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Abstract Detecting fishing boat activity is still a challenge for the biggest archipelago countries, such as Indonesia, to monitor the huge marine area. Space technology using sensors SAR to detect ships has been developed since 1985. However, the cost of using SAR images is one of the barriers to operational aspects, mainly for detecting fishing boats to deter IUU fishing activities. This research aims to evaluate the use of Sentinel 1-SAR imagery for identifying fishing boats from space. We used VIIRS data for validating the purposes. Both data sources could be accessed freely. The object de

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Herbuś, Krzysztof, Andrzej Dymarek, Piotr Ociepka, et al. "Development and Validation of Concept of Innovative Method of Computer-Aided Monitoring and Diagnostics of Machine Components." Applied Sciences 14, no. 21 (2024): 10056. http://dx.doi.org/10.3390/app142110056.

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The monitoring and diagnostic system has been suggested as a non-destructive diagnostic method. The structure and operation of the suggested system can be described by the concept of digital shadow (DS). One of the main DS subsystems is a set of sensors properly placed on the monitored object and coupled with a discrete data processing model created in Matlab/Simulink. The discrete model, as another important DS subsystem of the monitored facility, transfers information about its technical condition to the operator based on data recorded by the sensor system. The digital monitoring model proce

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Ha, Sungjae, and Mikyoung Kim. "A Study on the Metal Detection Development for CNN and RNN Algorithm Based." Korea Industrial Technology Convergence Society 27, no. 4 (2022): 9–19. http://dx.doi.org/10.29279/jitr.2022.27.4.9.

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This paper is a study on the efficiency of the filtering method of signal processing and the metal detection method using deep learning for data obtained from multiple MI sensors. The MI sensor is a principle that detects changes in magnetic field and is a passive sensor that detects metal objects. However, when detecting a metal object, the amount of change in the magnetic field caused by the metal is small, so there is a limit to the detectable distance. In order to effectively detect and analyze this, a method using deep learning was applied. In addition, the performance of the deep learnin

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Cho, Geun-Sik, and Yong-Jai Park. "Soft Gripper with EGaIn Soft Sensor for Detecting Grasp Status." Applied Sciences 11, no. 15 (2021): 6957. http://dx.doi.org/10.3390/app11156957.

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With the Fourth Industrial Revolution, many factories aim for efficient mass production, and robots are being used to reduce human workloads. In recent years, the field of gripper robots with a soft structure that can grip and move objects without damaging them has attracted considerable attention. This paper proposes a variable-stiffness soft gripper, based on previous designs, with an added silicone coating for increased friction and an EGaIn soft sensor for monitoring grip forces. The variable-stiffness structure used in this study was constructed by connecting soft structures to rigid stru

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Li, Yanfen, Hanxiang Wang, L. Minh Dang, Hyoung-Kyu Song, and Hyeonjoon Moon. "ORCNN-X: Attention-Driven Multiscale Network for Detecting Small Objects in Complex Aerial Scenes." Remote Sensing 15, no. 14 (2023): 3497. http://dx.doi.org/10.3390/rs15143497.

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Currently, object detection on remote sensing images has drawn significant attention due to its extensive applications, including environmental monitoring, urban planning, and disaster assessment. However, detecting objects in the aerial images captured by remote sensors presents unique challenges compared to natural images, such as low resolution, complex backgrounds, and variations in scale and angle. Prior object detection algorithms are limited in their ability to identify oriented small objects, especially in aerial images where small objects are usually obscured by background noise. To a

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Karagoz, Ahmet, and Gokhan Dindis. "Object Recognition and Positioning with Neural Networks: Single Ultrasonic Sensor Scanning Approach." Sensors 25, no. 4 (2025): 1086. https://doi.org/10.3390/s25041086.

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Ultrasonic sensing may become a useful technique for distance measurement and object detection when optical visibility is not available. However, the research on detecting multiple target objects and locating their coordinates is limited. This makes it a valuable topic. Reflection signal data obtained from a single ultrasonic sensor may be just enough for the measurements of distance and reflection strength. On the other hand, if extracted properly, a scanned set of signal data by the same sensor holds a significant amount of information about the surrounding geometries. Evaluating this datase

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Tejas, Patel. "IoT-based ultrasonic sensors and buzzer systems in home security." i-manager’s Journal on Pattern Recognition 10, no. 2 (2023): 35. http://dx.doi.org/10.26634/jpr.10.2.20351.

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With the increasing demand for security in various aspects of daily life, including homes, the need for reliable and costeffective security systems has increased. This paper presents an Internet of Things (IoT)-based approach to home security utilizing ultrasonic sensors and buzzer systems. The proposed system, implemented using Arduino microcontrollers, offers a wireless solution for detecting intruders within a specified range using ultrasonic sensors. Upon detecting an object, the system activates a piezoelectric buzzer, effectively acting as an alarm. Additionally, the sensor data is proce

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Tang, Li, Yunpeng Shi, Qing He, Adel W. Sadek, and Chunming Qiao. "Performance Test of Autonomous Vehicle Lidar Sensors Under Different Weather Conditions." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 1 (2020): 319–29. http://dx.doi.org/10.1177/0361198120901681.

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This paper intends to analyze the Light Detection and Ranging (Lidar) sensor performance on detecting pedestrians under different weather conditions. Lidar sensor is the key sensor in autonomous vehicles, which can provide high-resolution object information. Thus, it is important to analyze the performance of Lidar. This paper involves an autonomous bus operating several pedestrian detection tests in a parking lot at the University at Buffalo. By comparing the pedestrian detection results on rainy days with the results on sunny days, the evidence shows that the rain can cause unstable performa

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Almajdoub, R., Almajdoub, R., and Shiba, O. Shiba, O. "An Assistant System For Blind To Avoid Obstacles Using Artificial Intelligence Techniques." International Journal of Engineering & Information Technology (IJEIT) 12, no. 1 (2024): 226–38. http://dx.doi.org/10.36602/ijeit.v12i1.491.

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This study focuses on developing an assistive system for blind individuals for collision avoidance of obstacles by combining artificial intelligence techniques; Convolutional Neural Networks (CNN), fuzzy logic control (FLC), and genetic algorithms(GA), This integrated system, named the (NFG) Neural Fuzzy Genetic). The proposed system combines artificial intelligence techniques through detecting and tracking objects, measuring the distance between objects and the blind person, and providing movement guidance using three ultrasonic sensors with FLC and optimization GA. The integration of these t

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Ma, Zhong Li, and Hong Da Liu. "Temperature Error Compensation New Method of MFL Sensor to Oil-Gas Pipeline Corrosion Inspection." Advanced Materials Research 204-210 (February 2011): 1026–30. http://dx.doi.org/10.4028/www.scientific.net/amr.204-210.1026.

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Magnetic flux leakage (MFL) inspection is a common method for detecting inner corrosions of oil-gas pipelines; the Hall Effect element is the core sensor of MFL inspections. The Hall sensor is sensitive to temperature, so environmental changes will lead to output error of Hall sensors. In order to compensate for temperature errors of Hall sensors, a segment of oil-gas pipeline with diameter 6 inch was taken as a research object. A fusion model including 50 Hall sensors and 1 temperature sensor was built up, and a functional link artificial neural network optimized by the artificial immune algo

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Cao, Yue, Yanshuo Fan, Junchi Bin, and Zheng Liu. "Lightweight Transformer for Multi-Modal Object Detection (Student Abstract)." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 13 (2023): 16172–73. http://dx.doi.org/10.1609/aaai.v37i13.26946.

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It has become a common practice for many perceptual systems to integrate information from multiple sensors to improve the accuracy of object detection. For example, autonomous vehicles use visible light, and infrared (IR) information to ensure that the car can cope with complex weather conditions. However, the accuracy of the algorithm is usually a trade-off between the computational complexity and memory consumption. In this study, we evaluate the performance and complexity of different fusion operators in multi-modal object detection tasks. On top of that, a Poolformer-based fusion operator

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Huang, Shih-Chang, and Cong-Han Huang. "Algorithms for Detecting and Refining the Area of Intangible Continuous Objects for Mobile Wireless Sensor Networks." Algorithms 15, no. 2 (2022): 31. http://dx.doi.org/10.3390/a15020031.

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Detecting the intangible continuous object (ICO) is a significant task, especially when the ICO is harmful as a toxic gas. Many studies used steady sensors to sketch the contour and find the area of the ICO. Applying the mobile sensors can further improve the precision of the detected ICO by efficiently adjusting the positions of a subset of the deployed sensors. This paper proposed two methods to figure out the area of the ICO, named Delaunay triangulation with moving sensors (MDT) and convex hull with moving sensors (MCH). First, the proposed methods divide the sensors into ICO-covered and I

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Leshchiner, Dmitry, Konstantin Zvezdin, Anatoly Popkov, Grigory Chepkov, and Pietro Perlo. "Image reconstruction algorithms for the microwave holographic vision system with reliable gap detection at theoretical limits." EPJ Web of Conferences 185 (2018): 01004. http://dx.doi.org/10.1051/epjconf/201818501004.

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We present a reliable image reconstruction algorithm suitable for a microwave holographic vision system with several sensors coupled to the spin-diode based microwave detector and a single emission source. An objective is, by reconstructing the spatial microwave scattering density on the scene, to detect the presence and the nature of road obstacles impeding driving in the near vehicle zone. The idea of holographic visualization is to reconstruct the spatial microwave scattering density of an object by detecting an amplitude and phase of a reflected signal by lattice of sensors. We discuss ver

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Costanzo, Marco, Giuseppe De Maria, and Ciro Natale. "Detecting and Controlling Slip through Estimation and Control of the Sliding Velocity." Applied Sciences 13, no. 2 (2023): 921. http://dx.doi.org/10.3390/app13020921.

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Slipping detection and avoidance are key issues in dexterous robotic manipulation. The capability of robots to grasp and manipulate objects of common use can be greatly enhanced by endowing these robots with force/tactile sensors on their fingertips. Object slipping can be caused by both tangential and torsional loads when the grip force is too low. Contact force and moment measurements are required to counteract such loads and avoid slippage by controlling the grip force. In this paper, we use the SUNTouch force/tactile sensor, which provides the robotic control system with reliable measureme

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Savitha, A. C., Kumar KM Madhu, N. V. Keerthana, C. G. Keerthi, R. Nithyashree, and K. V. Poorvi. "Embedded Smart Glass for Blind Person." Journal of Scholastic Engineering Science and Management (JSESM), A Peer Reviewed Universities Refereed Multidisciplinary Research Journal 4, no. 5 (2025): 62–68. https://doi.org/10.5281/zenodo.15400892.

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This report presents the design and development of smart glasses for visually impaired individuals, utilizing ultrasonic sensors to enhance navigation and obstacle detection. Blind and visually impaired individuals face numerous challenges in navigating their environment safely and independently. Traditional aids such as white canes and guide dogs are helpful but have limitations in detecting obstacles above ground level or at a distance. To address these challenges, wearable technology, particularly smart glasses integrated with ultrasonic sensors, has emerged as an innovative solution. The p

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S., S., S. Renuka, R. Shakthi Priyaa, et al. "CL-FusionBEV: A Cross-Attention Based Fusion Model for Camera and LiDAR in Bird’s Eye View Perception." Fusion: Practice and Applications 19, no. 2 (2025): 15–27. https://doi.org/10.54216/fpa.190202.

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In autonomous navigation, the ability to detect 3D objects from a Bird’s-Eye View (BEV) perspective is essential. Nevertheless, many obstacles remain before LiDAR and camera data can be effectively combined. We propose CL-FusionBEV, a novel framework for sensor fusion that enhances Three-dimensional object recognition in the BEV domain. This method structures LiDAR point clouds for improved spatial feature extraction while converting camera data into BEV format via an implicit learning technique. An implicit fusion network and a multi-modal cross-attention mechanism facilitate seamless sensor

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Drashti Parmar, Sumeet Rajak, Sourabh Patil, and Prof. Rupali Satpute. "Robotic Arm for Segregation Using Image Processing." International Research Journal on Advanced Engineering Hub (IRJAEH) 2, no. 04 (2024): 755–60. http://dx.doi.org/10.47392/irjaeh.2024.0106.

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The recent surge in industrial expansion can be attributed significantly to the advancements in automation technology. For better performance of industrial processes, automated systems are used. Image processing has played a great role in the applications of robotics and embedded systems. Sorting of objects is usually done by humans which takes a lot of time and effort. By employing image processing methods alongside appropriate sensors, object detection becomes feasible, enabling the utilization of robotic arms for sorting diverse items. This reduces human effort and improves the time to mark

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