Summary

With the growth of satellite and airborne-based platforms, remote sensing is gaining increasing attention in recent decades. Every day, sensors acquire data with different modalities and several resolutions. Leveraging on their complementary properties is a key scientific challenge, usually called remote sensing data fusion. Data fusion can be performed at three different processing levels: 1) pixel-based or raw level; 2) object-based or feature level; 3) decision level. Fusion at pixel level is often called image fusion. It means fusion at the lowest processing level referring to the merging of digital numbers or measured physical quantities. It uses co-registered raster data acquired by different sources. The co-registration step is of crucial importance because misregistration usually causes evident artifacts. Fusion at feature level requires the extraction of objects recognized in several sources of data. This is the goal of this entry collection, which will focus both on methodological and practical aspects of remote sensing data fusion.

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Topic Review
Flying Ad Hoc Network
Unmanned aerial vehicles (UAVs), or drones, have made them able to communicate and collaborate, forming flying ad hoc networks (FANETs). FANETs are becoming popular in many application domains, including precision agriculture, goods delivery, construction, environment and climate monitoring, and military surveillance. These interesting new avenues for the use of UAVs are motivating researchers to rethink the existing research on FANETs. 
  • 1.0K
  • 01 Dec 2022
Topic Review
Artificial Intelligence in Archaeology
Artificial Intelligence (AI), due to its increasingly powerful predictive capabilities, is showing an increasing trend in attracting widespread interest in many sciences. Archaeologists now can more fully exploit the knowledge from an extensive amount of archaeological data with the use of artificial intelligence in such a way as to make decisions related to appropriate strategies for the preservation and protection of archaeological elements, as well as to decide on the most ideal point excavation in a complex cultural landscape. 
  • 5.2K
  • 30 Nov 2022
Topic Review Video
3D Visualisation in Railway Tunnel SubSurface Inspection
Railway Tunnel SubSurface Inspection (RTSSI) is essential for targeted structural maintenance. ‘Effective’ detection, localisation and characterisation of fully concealed features (i.e., assets, defects) is the primary challenge faced by RTSSI engineers, particularly in historic masonry tunnels. Clear conveyance and communication of gathered information to end-users poses the less frequently considered secondary challenge.
  • 1.1K
  • 22 Nov 2022
Topic Review
Vision-Based Structural Vibration Tracking Using a Digital Camera
Computer-vision-based target tracking can be applied to structural vibration monitoring, but current target tracking methods suffer from noise in digital image processing. A new target-tracking method based on the sparse optical flow technique is introduced to improve the accuracy in tracking the target, especially when the target has a large displacement. The proposed method utilizes the ORB technique to maintain a variety of keypoints and combines the multi-level strategy with a sparse optical flow algorithm to search the keypoints with a large motion vector for tracking. Then, an outlier removal method based on Hamming distance and interquartile range (IQR) score is introduced to minimize the error. The proposed target tracking method is verified through a lab experiment---a three-story shear building structure subjected to various harmonic excitations. It is compared with existing sparse optical flow-based target tracking methods and target tracking methods based on three other types of techniques, i.e., feature matching, dense optical flow, and template matching. The results show that the performance of target tracking is greatly improved through the use of a multi-level strategy and the proposed outlier removal method. The proposed sparse optical flow-based target tracking method achieves the best accuracy compared to other existing target tracking methods.
  • 669
  • 01 Dec 2022
Topic Review
Industry 4.0 in Medium-Sized Enterprises
Industry 4.0 (I4.0) is a broad term increasingly used across industries to refer to organisational, social and economic changes that result from the intensive use of digital technologies. It generally implies the adoption of a series of practices that rely heavily on the Internet and other technologies to share and analyse data, most notably, the Internet of Things (IoT), cloud computing and artificial intelligence (AI). I4.0 data-driven processes are touted to enhance productivity and expand supply and value chains in new product development. In manufacturing, I4.0 practices include collecting and sharing data using sensors in interconnected devices and using digital technologies for processing and analysing data to take new actions. 
  • 929
  • 17 Nov 2022
Topic Review
Mobile Robot Path Planning
One of the most significant processes in the autonomous navigation is path planning. Path planning involves the determination of a possible path for a mobile robot to move from a start to a target location in a particular environment while considering optimization parameters like path distance, time and path smoothness. Mobile robot path planning is a subcategory of trajectory planning.
  • 1.1K
  • 21 Nov 2022
Topic Review
Quantum Computing Supremacy in the Internet of Things
The Internet of Things (IoT) strongly influences the world economy; this emphasizes the importance of securing all four aspects of the IoT model: sensors, networks, cloud, and applications. Considering the significant value of public-key cryptography threats on IoT system confidentiality, it is vital to secure it. One of the potential candidates to assist in securing public key cryptography in IoT is quantum computing. Although the notion of IoT and quantum computing convergence is not new, it has been referenced in various works of literature and covered by many scholars. Quantum computing eliminates most of the challenges in IoT.
  • 2.0K
  • 16 Nov 2022
Topic Review
Computer Vision and Convolutional Neural Networks
Computer vision (CV) combined with a deep convolutional neural network (CNN) has emerged as a reliable analytical method to effectively characterize and quantify high-throughput phenotyping of different grain crops, including rice, wheat, corn, and soybean. In addition to the ability to rapidly obtain information on plant organs and abiotic stresses, and the ability to segment crops from weeds, such techniques have been used to detect pests and plant diseases and to identify grain varieties. The development of corresponding imaging systems to assess the phenotypic parameters, yield, and quality of crop plants will increase the confidence of stakeholders in grain crop cultivation, thereby bringing technical and economic benefits to advanced agriculture.
  • 1.7K
  • 14 Nov 2022
Topic Review
Optical Fiber Sensors and Sensing Networks
Optical fiber sensors present several advantages in relation to other types of sensors. These advantages are essentially related to the optical fiber properties, i.e., small, lightweight, resistant to high temperatures and pressure, electromagnetically passive, among others. Sensing is achieved by exploring the properties of light to obtain measurements of parameters, such as temperature, strain, or angular velocity. In addition, optical fiber sensors can be used to form an Optical Fiber Sensing Network (OFSN) allowing manufacturers to create versatile monitoring solutions with several applications, e.g., periodic monitoring along extensive distances (kilometers), in extreme or hazardous environments, inside structures and engines, in clothes, and for health monitoring and assistance.
  • 1.4K
  • 03 Nov 2022
Topic Review
Microwave SINIS Detectors
Among cryogenic microwave detectors and bolometers, the superconductor–insulator–normal metal–insulator–superconductor (SINIS) detectors are promising candidates for practical applications due to their wide dynamic range, low requirements for temperature stabilization, lack of upper limit for signal frequency, and immunity to vibrations and magnetic fields compared to competing cryogenic detectors such as transition edge sensors, kinetic inductance detectors, hot electron detectors, and SIS detectors.
  • 729
  • 27 Oct 2022
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