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UAV Remote Sensing of Cyber-Physical System
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Department of Geography, Kyungpook National University, Daegu 41566, Republic of Korea
School of Computer Science, University of Petroleum and Energy Studies (UPES), Dehradun 248007, Uttarakhand, India
Geospatial Information Sciences Program; School of Economic, Political and Policy Sciences; The University of Texas at Dallas, Richardson, TX 75080, USA
Department of Engineering Design and Mathematics, Faculty of Environment and Technology, University of the West of England (UWE Bristol), Frenchay Campus, Coldharbour Lane, Bristol BS16 1QY, UK
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UAV Remote Sensing of Cyber-Physical System

Abstract submission deadline
closed (31 May 2023)
Manuscript submission deadline
closed (31 August 2023)
Viewed by
3917

Topic Information

Dear Colleagues,

In cyber–physical systems (CPS), cyber to physical bridging is a sensing process that uses sensors to acquire spatial information about physical phenomena. The term Metaverse or digital twin can be described as a digital copy of any physical system. The CPS links the physical world to the cyber world through the internet and a computer, and vice versa; the Metaverse performs real-world activities in the cyber world. UAV remote sensing is a foundation and golden thread in cyber to physical bridging since massive, real-time, and high-resolution data can be utilized for deep learning in artificial intelligence, such as self-driving cars. The unexpected COVID-19 pandemic has accelerated the creation of a new ecosystem called the Metaverse, which is an extended concept of cyber–physical systems.

This Topic is expected to initiate the conversation that will drive the development of a foundational theory to describe how to utilize the strength of UAV remote sensing in cyber and physical bridging. We particularly welcome research (theories, methods, and practices) that addresses the gaps between industry versus more theoretical academia in cyber to physical bridging. This Topic is particularly interested in multidisciplinary reflection—views from many disciplines, including the social sciences, physical sciences, life sciences, and many others. Potential topics include but are not limited to:

1. Review articles on cyber to physical bridging in cyber–physical systems and the Metaverse:
  • The role of UAV remote sensing in cyber to physical bridging;
  • Cyber–physical systems and the Metaverse in real-time operations;
  • Modelling and simulation of cyber–physical systems and the Metaverse;
  • Cyber–physical systems and the Metaverse as educational technology.
2. Science and technology for cyber to physical bridging:
  • AI solutions for cyber–physical systems and the Metaverse;
  • Hardware and software for cyber to physical bridging;
  • Cloud/edge computing for cyber to physical bridging;
  • Processing, maintenance, and optimization for cyber to physical bridging.
3. Cyber–physical systems and the Metaverse in engineering:
  • Smart construction and buildings;  
  • Smart manufacturing and smart cities.
4. Cyber–physical systems and the Metaverse in social sciences and the arts:
  • The conservation and exhibition of cultural heritage;
  • Real-estate and the tourism industry;
  • Art design and exhibition;
  • Social welfare and media art.
5. Cyber–physical systems and the Metaverse in physical sciences:
  • Climate change and air or water pollution;
  • Natural and man-made disasters;
  • Applications to tackle development activities that endanger biodiversity.

Prof. Dr. Jung-Sup Um
Dr. Tanupriya Choudhury
Dr. Muhammad T. Rahman
Dr. Hamidreza Nemati
Topic Editors

Keywords

  • cyber–physical systems
  • cyber to physical bridging
  • metaverse
  • digital twins
  • UAV remote sensing
  • The Fourth Industrial Revolution
  • internet of things
  • smart city
  • self-driving vehicles
  • virtual reality, augmented reality, mixed reality, and extended reality
  • mirror world, virtual world

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
AI
ai 		3.1 7.2 2020 17.6 Days CHF 1600
Applied Sciences
applsci 		2.5 5.3 2011 17.8 Days CHF 2400
Drones
drones 		4.4 5.6 2017 21.7 Days CHF 2600
Remote Sensing
remotesensing 		4.2 8.3 2009 24.7 Days CHF 2700
Sensors
sensors 		3.4 7.3 2001 16.8 Days CHF 2600

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Published Papers (2 papers)

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21 pages, 18878 KiB  
Article
Assessment of Active Ground Subsidence in the Dibrugarh and Digboi Areas of Assam, Northeast India, Using the PSInSAR Technique
by Abhishek Lakhote, Girish Ch Kothyari, Atul Kumar Patidar, Jayshree Changmai, Rashmi Borgohain, Tanupriya Choudhury and Jung-Sup Um
Remote Sens. 2023, 15(20), 4963; https://doi.org/10.3390/rs15204963 - 14 Oct 2023
Cited by 2 | Viewed by 1315
Abstract
Ground deformation on a regional to local scale is the consequence of a wide range of natural processes such as tectonic and anthropogenic activities. Globally, the over-extraction of groundwater and hydrocarbon exploitation are the primary causes of ground subsidence. The current study demonstrates [...] Read more.
Ground deformation on a regional to local scale is the consequence of a wide range of natural processes such as tectonic and anthropogenic activities. Globally, the over-extraction of groundwater and hydrocarbon exploitation are the primary causes of ground subsidence. The current study demonstrates regional scale ground subsidence analysis of the Dibrugarh and Digboi regions of Brahmaputra alluvial plain, Assam, Northeast India. To understand the ongoing surface deformation satellite base, the RADAR technique has been applied using SENTINEL-1A data, which were acquired between 15 October 2015 to 25 January 2022. The assessment carried out via the time series analysis of the radar data suggests that the Dibrugarh area is subsiding at a rate of ~5 mm/yr, whereas the Digboi is deforming at a much faster rate (±22 mm/yr) than Dibrugarh. The presence of active faults in the subsurface and associated deformation is another reason for active ground subsidence. The outcomes of the current study validate that the study area is currently undergoing active subsurface deformation caused by both endogenic as well as exogenic processes. Furthermore, our Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) and satellite-based analysis suggest that the over-exploitation of the natural resources is enhancing the rate of deformation in the Brahmaputra alluvial plain in the northeast of India. Full article
(This article belongs to the Topic UAV Remote Sensing of Cyber-Physical System)
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15 pages, 13516 KiB  
Article
Performance Evaluation of a Quadcopter by an Optimized Proportional–Integral–Derivative Controller
by Joy Iong-Zong Chen and Hsin-Yu Lin
Appl. Sci. 2023, 13(15), 8663; https://doi.org/10.3390/app13158663 - 27 Jul 2023
Cited by 1 | Viewed by 1199
Abstract
This paper presents an analysis of a quadcopter’s stability and its sensors’ data reading using an IMU (inertial measurement unit). Firstly, the angular velocity and acceleration data are read by an Stm® development board embedded with an Stm32f401ccu6 microcontroller. The altitude of [...] Read more.
This paper presents an analysis of a quadcopter’s stability and its sensors’ data reading using an IMU (inertial measurement unit). Firstly, the angular velocity and acceleration data are read by an Stm® development board embedded with an Stm32f401ccu6 microcontroller. The altitude of the measurement instrument platform was determined using an MS5611 barometric pressure sensor combined with a temperature sensor. The quadcopter’s control was achieved by connecting a brushless DC motor to the Stm® board, which received four PWM (pulse-width modulation) signals via the output port. An electronic governor was utilized to control the brushless DC motor, while a pre-existing remote control was designated as the transmitter. The quadcopter receiver received a 2.4 GHz signal from the transmitter using the BLE (Bluetooth low-energy) protocol, which was used to ensure the simultaneous operation of the four brushless DC motors. Finally, a PID (proportional–integral–derivative) controller was employed for parameter adjustment. The collected PID parameter program was developed in the Simulink software as a simulation platform, allowing for the execution of the Simulink model on the Stm® MCU. The Stm® module facilitates monitoring of the performance of the UAV (unmanned aerial vehicle) and enables immediate parameter adjustments to ensure flight stability. This research aims to reduce calculation errors in sensor and controller usage and improve the efficacy of the remote machine module for future industrial applications. Full article
(This article belongs to the Topic UAV Remote Sensing of Cyber-Physical System)
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