ADVANCEMENTS IN INDUSTRIAL DIGITAL SENSORS (VERSION 3.0 TO 4.0) AND RADAR SYSTEMS FOR OBJECT DETECTION: A STATE-OF-THE-ART REVIEW
UDC: 681.586:621.396.969.3
DOI:
https://doi.org/10.46763/ETIMA2531140mSchlagwörter:
industrial digital sensors, version 3.0 to 4.0, radar systems, object detection, advancements, challenges.Abstract
In this digital age, sensors and digital components are a crucial part of modern life, as they are used daily to simplify various processes. The use of the sensors and other industrial components is wider starting from science, IoT, technology stakeholders and finishing to educational processes which shows that this kind of components are used in every field. This scientific paper represents a review of the latest advancements and developments in the industrial digital sensors and components, focusing on versions 3.0 and 4.0 and also their use to develop radar systems for object detection. The review mostly focuses on covering key advancements and developments, challenges and future directions in these fields and technologies, providing insight for students, researchers, engineers and also industry stakeholders.
Downloads
Literaturhinweise
[1] Eisenmann, Brent: Integrating Sensor Technology with the Arduino UNO Microcontroller for Object Detection. Michigan State University, United States, May 2013.
[2] Ecemis, M. Ihsan / Gaudiano, Paolo: Object Recognition with Ultrasonic Sensors. Boston University Neurobotics Laboratory.
[3] Ghobadi, Seyed Eghbal: Real-Time Object Recognition and Tracking Using 2D/3D Images. Vom Fachbereich Elektrotechnik und Informatik der Universität Siegen zur Erlangung des akademischen Grades, September 2010.
[4] Grönwall, Christina: Ground Object Recognition Using Laser Radar Data – Geometric Fitting, Performance Analysis, and Applications. Division of Automatic Control, Department of Electrical Engineering, Linköpings universitet, Sweden, 2006.
[5] Javaid, Mohd / Haleem, Abid / Singh, Ravi Pratap / Rab, Shanay / Suman, Rajiv: Significance of Sensors for Industry 4.0: Roles, Capabilities, and Applications. Sensors International, 2021.
[6] Kalsoom, Tahera / Ramzan, Naeem / Ahmed, Shehzad / Ur-Rehman, Masood: Advances in Sensor Technologies in the Era of Smart Factory and Industry 4.0. International Conference on UK-China Emerging Technologies (UCET), Glasgow, United Kingdom, 20–21 August 2020.
[7] Liang, Ming / Yang, Bin / Wang, Shenlong / Urtasun, Raquel: Deep Continuous Fusion for Multi-Sensor 3D Object Detection. Uber Advanced Technologies Group 2, University of Toronto, 2018.
[8] Mansi, Sirumalla: Ultrasonic Distance Detector Using Arduino. Dept of ECE, Kakatiya Institute of Technology and Science, Warangal.
[9] Prima, Wandynata / Giap, Yo Ceng: Object Detection Radar Prototype with Ultrasonic Sensor Using IoT-Based Arduino. Universitas Buddhi Dharma, Tangerang, Indonesia, December 2020.
[10] Prasanna, Sheetal: Sensor Fusion in Neural Networks for Object Detection. Department of Electrical and Computer Engineering, Indianapolis, Indiana, May 2022.
[11] Rosário, Albérico Travassos / Dias, Joana Carmo: How Industry 4.0 and Sensors Can Leverage Product Design: Opportunities and Challenges. The Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP), Universidade Europeia, 1200-649 Lisbon, Portugal.
[12] Sarvaiya, Shilpa B / Satange, Dinesh N: Design and Implementation of IoT-Based Object Detection Using IR and Ultrasonic Sensors. Department of Computer Science, Vidyabharati Mahavidyalaya, Amravati, India, December 2022.
[13] Thomas, Ken D. / Quinn, Edward L. / Mauck, Jerry L. / Bockhorst, Richard M.: Digital Sensor Technology. 9th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human Machine Interface Technologies (NPIC&HMIT 2015), February 2015.
[14] Travassos Rosário, Albérico / Dias, Joana Carmo: How Industry 4.0 and Sensors Can Leverage Product Design: Opportunities and Challenges. The Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP), Universidade Europeia, Lisbon, Portugal.
[15] Vaswani, Namrata / Agrawal, Amit K / Zheng, Qinfen / Chellappa, Rama: Moving Object Detection and Compression in IR Sequences. Center for Automation Research, University of Maryland, College Park, MD.
[16] Yao, Shanliang / Guan, Runwei / Huang, Xiaoyu / Li, Zhuoxiao / Sha, Xiangyu: Radar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive Review. Jiangsu Industrial Technology Research Institute (JITRI) and Wuxi National Hi-Tech District (WND), R. China, August 2023.
[17] Divya, P / Bhavana, N / George, M: Arduino-Based Obstacle Detecting System. International Conference of Advance Research and Innovation (ICARI-2020), Department of Electronics, Andhra Loyola College, Vijayawada (AP), India, 2020.