Narrow Field Of View Research Articles

Vessel-based hybrid optic disk segmentation applied to mobile phone camera retinal images.

Precise detection of the optic disk (OD) is an important task in the diagnosis of diabetic retinopathy. To manage the massive diabetic population, there is a significant demand for efficient and remote retinal imaging techniques. In this regard, the use of handheld mobile cameras attached to a smartphone is a promising approach. However, smartphone retinal images are often of low quality, compared to those obtained on standard equipment. They also have a narrow field of view and an incomplete/unbalanced vessel structure. Hence, we propose a new, fully automatic hybrid method for OD localization (HLM). It is designed for and verified on mobile camera/smartphone retinal images. The HLM analyzes the vessel structure and finds the OD locations by using the exclusion method when an image has a complete vessel system, and a newly proposed line detection method, otherwise. For OD segmentation, an active contour model followed by the circle fitting approach is integrated into the HLM. The proposed method was tested on three mobile camera datasets and four datasets obtained by standard equipment. For mobile camera datasets, the HLM achieves an average accuracy of 98% for OD localization. The segmentation routine obtains an average precision of 92.64% and an average recall of 82.38%. Testing against the recent state-of-the-art methods on the standard datasets shows comparable performance. The proposed framework for OD localization and segmentation designed for and verified on mobile camera retinal datasets and standard datasets. (EM - "Exclusion Method", LDM - "Line Detection Method", OD - "Optic Disk" and PPV - "Positive Predictive Value").

Multi-scale reconstruction of porous media from low-resolution core images using conditional generative adversarial networks

Various rocks such as carbonate, coal or shale contain both micro- and macro-pores. To accurately predict the fluid flow and mechanical properties of these porous media, a multi-scale characterization of the pore space is of key importance. Hybrid superposition methods perform well in such multi-scale reconstructions, however, input images with two resolutions (high and low) and different reconstruction methods are required. In addition, the superposition algorithms are complex and human factors can introduce serious bias. Here we thus propose an effective approach based on conditional generative adversarial network (cGAN) for efficient and reliable multi-scale digital rock reconstruction based only on low-resolution core images. High-resolution core images with narrow field of view (FOV) and their corresponding large structure images were thus used to train the cGAN model. The model was validated with real sample images, and the model-generated images exhibited great agreement with the real pore structures. We also demonstrate that the proposed method can generate images independent of the structure size to some extent. This work provides an advanced image-generating model based on deep learning, and therefore aids in better and wider pore-scale characterization and process modeling, to improve understanding of subsurface science and engineering processes.

Additively Manufactured Amplitude Tapered Slotted Waveguide Array Antenna With Horn Aperture for 77 GHz

In this work, a combined frontend of horn and slotted waveguide array antenna serving as feeding subsystem is presented. This setup allows to implement an amplitude taper in one plane while using the horn aperture to shape the far field radiation characteristics in the perpendicular plane independently and tailored to the individual demand of the application. Moreover, the feeding system is implemented as a loop resulting in a standing wave distribution for a wide frequency range in order to increase the antenna bandwidth. Two specimens with different horn apertures are additively manufactured in slotted waveguide technology from UV curable photopolymer resin using a digital light processing 3D printer and subsequently metal coated by electroless silver plating. A relatively large bandwidth of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{B}_{-10\text {dB}} = 7.2$ </tex-math></inline-formula> GHz and a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{B}_{-15\,\text {dB}}$ </tex-math></inline-formula> of 4.9 GHz is achieved in measurements indicating a relative bandwidth of 9 % and 6 % respectively. Antenna Gain is characterized as 17.5 and 20.17 dBi in measurements while maintaining a sidelobe level of 20–22.5 dB at 77 GHz and exhibiting a radiation efficiency of 78.9 and 79.4 %. The proposed antenna architecture provides a flexible approach for beam shaping in applications where azimuth and elevation planes exhibit different or contrary requirements, e.g. broad vs. narrow field of view - especially suitable for automotive MIMO-radar sensors.

Confocal laser endomicroscopy in gastro-intestinal endoscopy: technical aspects and clinical applications.

Confocal laser endomicroscopy (CLE) is an advanced endoscopic imaging technology that provides a magnified, cellular level view of gastrointestinal epithelia. In conjunction with topical or intravenous fluorescent dyes, CLE allows for an "optical biopsy" for real-time diagnosis. Two different CLE system have been used in clinical endoscopy, probe-based CLE (pCLE) and endoscope-based CLE (eCLE). Using pCLE, the device can be delivered: (I) into the luminal gastrointestinal tract through the working channel of standard endoscopes; (II) into extraluminal cystic and solid parenchymal lesions through an endoscopic ultrasound (EUS) needle; or (III) into the biliary system through an endoscopic retrograde cholangiopancreatography (ERCP) accessory channel. With eCLE, the probe is directly integrated into the tip of a conventional endoscope, however, these endoscopes are no longer commercially available. CLE has moderate to high diagnostic accuracy for neoplastic and inflammatory conditions through the gastrointestinal tract including: oesophageal, gastric and colonic neoplasia, pancreatic cysts and solid lesions, malignant pancreatobiliary strictures and inflammatory bowel disease. Some studies have demonstrated the diagnostic benefit of CLE imaging when combined with either conventional white light endoscopy or advanced imaging technologies. Therefore, optical biopsies using CLE can resolve diagnostic dilemmas in some cases where conventional imaging fails to achieve conclusive results. CLE could also reduce the requirement for extensive tissue sampling during surveillance procedures. In the future, CLE in combination with molecular probes, could allow for the molecular characterization of diseases and assess response to targeted therapy. However, the narrow field of view, high capital costs and specialized operator training requirements remain the main limitations. Future multi-center, randomized trials with a focus on conventional diagnostic applications, cost-effectiveness and standardized training will be required for definitive evidence. The objective of this review is to evaluate the technical aspects and current applications of CLE in patients with gastrointestinal and pancreatobiliary diseases and discuss future directions for this technique.

Autonomous Patrol Robot using Solid-State LiDAR with Narrow FoV

Autonomous Patrol Robot using Solid-State LiDAR with Narrow FoV

Angular responsivity of ground and space-based direct solar irradiance radiometers

The angular response setup of PMOD/WRC was modified to facilitate measurements of the narrow field of view of radiometers for direct solar irradiance. First, The pointing of the JTSIM-DARA radiometer was measured four times during its construction in the optic laboratory of PMOD/WRC. The final offset of the pointing before shipping relative to the optical axis, defined by a removable alignment cube, is 1.07° / 0.67° (β/γ-axis) for the four-quadrant sensor and 0.095°/-0.017° for the radiometer cavity A. Next to JTSIM-DARA the DARA for the occulter of the satellite Proba-3 was characterised at PMOD/WRC. First tests of the pointing have been carried out and the final pointing characterization will be carried out in summer 2021. Finally, the angular response setup was also used the angular responsivity of solar direct irradiance filter radiometers. The first test was carried out using Precision Filter Radiometer (PFR) F-064.

Application of robotic technologies in lower gastrointestinal tract endoscopy: A systematic review

BACKGROUNDConventional optical colonoscopy is considered the gold standard investigation for colorectal tract pathology including colorectal malignancy, polyps and inflammatory bowel disease. Inherent limitations exist with current generation endoscopic technologies, including, but not limited to, patient discomfort, endoscopist fatigue, narrow field of view and missed pathology behind colonic folds. Rapid developments in medical robotics have led to the emergence of a variety of next-generation robotically-augmented technologies that could overcome these limitations.AIMTo provide a comprehensive summary of recent developments in the application of robotics in lower gastrointestinal tract endoscopy.METHODSA systematic review of the literature was performed from January 1, 2000 to the January 7, 2021 using EMBASE, MEDLINE and Cochrane databases. Studies reporting data on the use of robotic technology in ex vivo or in vivo animal and human experiments were included. In vitro studies (studies using synthetic colon models), studies evaluating non-robotic technology, robotic technology aimed at the upper gastrointestinal tract or paediatric endoscopy were excluded. System ergonomics, safety, visualisation, and diagnostic/therapeutic capabilities were assessed.RESULTSInitial literature searching identified 814 potentially eligible studies, from which 37 were deemed suitable for inclusion. Included studies were classified according to the actuation modality of the robotic device(s) as electromechanical (EM) (n = 13), pneumatic (n = 11), hydraulic (n = 1), magnetic (n = 10) and hybrid (n = 2) mechanisms. Five devices have been approved by the Food and Drug Administration, however most of the technologies reviewed remain in the early phases of testing and development. Level 1 evidence is lacking at present, but early reports suggest that these technologies may be associated with improved pain and safety. The reviewed devices appear to be ergonomically capable and efficient though to date no reports have convincingly shown diagnostic or therapeutic superiority over conventional colonoscopy. CONCLUSIONSignificant progress in robotic colonoscopy has been made over the last couple of decades. Improvements in design together with the integration of semi-autonomous and autonomous systems over the next decade will potentially result in robotic colonoscopy becoming more commonplace.

EVALUATION OF THE EFFICIENCY OF ADAPTIVE MONITORING GROUND SURFACES WHEN FLYING ABOVE CUMULUS CLOUDS ONBOARD OPTICAL-ELECTRONIC SYSTEMS

The spatial structure of the cloud cover located between the aircraft and the Earth’s surface strongly affects the result of monitoring of the Earth’s surface by Multi-Spectral Optical Electronic System of aircraft. The method of adaptive scanning of Earth’s surface was proposed in previous work to solve the above problem. This article is a continuation of previous work. There is the calculation of the efficiency of the proposed adaptive monitoring in this article. The calculation is carried out for the cases, when the rate of change of the position of the narrow field of view has no mechanical restrictions. The ratio of the area of unseen underlying surface to the whole area of underlying surface is taken as the loss function for calculation of the efficiency of monitoring. This loss function allows us to calculate the efficiency of monitoring as the calculation of restrictions of the duration of optical contact with the object. The calculation is carried out with a known mathematical expectation of the distance between the centers of adjacent (neighboring) clouds. Estimates of the corresponding mathematical expectations are taken for a given lateral displacement of the sought object, the flight altitude of the aircraft and the statistical characteristics of spatial structure of the cloud. This data is taken from meteorological reference books. The analytical expressions and the calculations, which are given in this article, can be used as a basis for development of the algorithms of the adaptive control of the orientation of a narrow field of view for Multi-Spectral Optical Electronic System.

Simultaneous ALMA–Hinode–IRIS Observations on Footpoint Signatures of a Soft X-Ray Loop-like Microflare

Abstract Microflares have been considered to be among the major energy input sources to form active solar corona. To investigate the response of the low atmosphere to events, we conducted an Atacama Large Millimeter/submillimeter Array (ALMA) observation at 3 mm, coordinated with Interface Region Imaging Spectrograph (IRIS) and Hinode observations, on 2017 March 19. During the observations, a soft X-ray loop-type microflare (active region transient brightening) was captured using the Hinode X-ray telescope in high temporal cadence. A brightening loop footpoint is located within narrow fields of view of ALMA, IRIS slit-jaw imager, and Hinode spectropolarimeter. Counterparts of the microflare at the footpoint were detected in Si iv and ALMA images, while the counterparts were less apparent in C ii and Mg ii k images. Their impulsive time profiles exhibit the Neupert effect pertaining to soft X-ray intensity evolution. The magnitude of thermal energy measured using ALMA was approximately 100 times smaller than that measured in the corona. These results suggest that impulsive counterparts can be detected in the transition region and upper chromosphere, where the plasma is thermally heated via impinging nonthermal particles. Our energy evaluation indicates a deficit of accelerated particles that impinge the footpoints for a small class of soft X-ray microflares. The footpoint counterparts consist of several brightening kernels, all of which are located in weak (void) magnetic areas formed in patchy distribution of strong magnetic flux at the photospheric level. The kernels provide a conceptual image in which the transient energy release occurs at multiple locations on the sheaths of magnetic flux bundles in the corona.

Image-based shading correction for narrow-FOV truncated pelvic CBCT with deep convolutional neural networks and transfer learning.

Purpose: Cone beam computed tomography (CBCT) is a standard solution for in‐room image guidance for radiation therapy. It is used to evaluate and compensate for anatomopathological changes between the dose delivery plan and the fraction delivery day. CBCT is a fast and versatile solution, but it suffers from drawbacks like low contrast and requires proper calibration to derive density values. Although these limitations are even more prominent with in‐room customized CBCT systems, strategies based on deep learning have shown potential in improving image quality. As such, this article presents a method based on a convolutional neural network and a novel two‐step supervised training based on the transfer learning paradigm for shading correction in CBCT volumes with narrow field of view (FOV) acquired with an ad hoc in‐room system. Methods: We designed a U‐Net convolutional neural network, trained on axial slices of corresponding CT/CBCT couples. To improve the generalization capability of the network, we exploited two‐stage learning using two distinct data sets. At first, the network weights were trained using synthetic CBCT scans generated from a public data set, and then only the deepest layers of the network were trained again with real‐world clinical data to fine‐tune the weights. Synthetic data were generated according to real data acquisition parameters. The network takes a single grayscale volume as input and outputs the same volume with corrected shading and improved HU values. Results: Evaluation was carried out with a leave‐one‐out cross‐validation, computed on 18 unique CT/CBCT pairs from six different patients from a real‐world dataset. Comparing original CBCT to CT and improved CBCT to CT, we obtained an average improvement of 6 dB on peak signal‐to‐noise ratio (PSNR), +2% on structural similarity index measure (SSIM). The median interquartile range (IQR) Hounsfield unit (HU) difference between CBCT and CT improved from 161.37 (162.54) HU to 49.41 (66.70) HU. Region of interest (ROI)‐based HU difference was narrowed by 75% in the spongy bone (femoral head), 89% in the bladder, 85% for fat, and 83% for muscle. The improvement in contrast‐to‐noise ratio for these ROIs was about 67%. Conclusions: We demonstrated that shading correction obtaining CT‐compatible data from narrow‐FOV CBCTs acquired with a customized in‐room system is possible. Moreover, the transfer learning approach proved particularly beneficial for such a shading correction approach.

Does overlay field of view in head-mounted displays affect spatial memorization?

One of the main targets of criticism of head-mounted displays (HMDs) is the field of view (FOV) size, whether in virtual or augmented reality. This limitation is prominent with optical see-through head-mounted displays (OST-HMD), as those with narrow overlay FOV (OFOV) sizes only provide a small window to view virtual objects. We investigated if restricting this OFOV negatively affects a user’s ability to memorize spatial locations in a simulation of a work environment, and consequently, long-term memory transfer to an equivalent scenario in the real world two days later. To find empirical evidence, we conducted a within-subjects experiment with 18 participants performing in three phases with an OST-HMD, simulated on an immersive HMD. For each phase, they viewed the training scenario with a different OFOV size of the augmentable area (30°, 70°, 110° diagonal). Results from recall tests showed that smaller OFOV size did not significantly affect user’s performance on both short-term and transfer tests, but HMD data revealed that users rotated their heads less with a 110° OFOV. We also found that proximity of objects to memorize had an interaction effect with smaller OFOV sizes. Our findings could have implications on the design and HMD choices of augmented training.

Occlusion-capable see-through display without the screen-door effect using a photochromic mask.

Conventional occlusion-capable see-through display systems have many practical limitations such as the form factor, narrow field of view, screen-door effect, and diffraction of a real scene. In this Letter, we propose an occlusion-capable see-through display using lens arrays and a photochromic plate. By imaging the occlusion mask on the photochromic plate with near-UV light, the visible light transmittance of the plate changes. Since no black matrix lies on the photochromic plate, our system provides a clear real scene view without the grid structure of the pixels and can prevent diffraction defects of the real scene. We also alleviate the drawback of a narrow field of view using the lens arrays for a reduced form factor.

A-145 Tunnel Vision: A Novel Investigation of the Effect of Depression on Field of View

Abstract Objective This study examined the effects of depression on field of view and memory as it relates to cognitive remittance of depression. Depressed individuals possess a negativity bias producing a narrowed field of view, attentional bias, and enhanced memory for negative emotional information. Methods The study investigated whether formerly depressed (remitted) individuals are truly cognitively remitted and display the same emotional and attention inhibitions and memory as depressed individuals, specifically under a negatively mood induced state. Female participants aged 39–85 were grouped into non-depressed (healthy) and remitted categories. The study followed a 3-day testing procedure which included diagnostic verification on the first day, and eye-tracking methods on the second and third day looking at a series of emotionally valenced images. The study employed a 2 x 3 x 2 mixed model ANOVA. Results Results suggested that remitted individuals possess a narrower field of view, especially when subjected to a negative mood induction as seen in Figure 1. Results also suggested that a negative mood induction results in greater visual exploration (attention) to negatively valenced information for formerly depressed individuals. Results showed that remitted individuals continued to demonstrate significantly different viewing patterns (i.e., saccade amplitudes and number of fixations) to emotionally valenced information under a negative mood induction but, this did not impact recognition memory. Conclusion Taken together, the results of the study support the idea that formerly depressed individuals experience a perceptual and cognitive tunnel vision that elaborates on their inhibited negative cognitive schemas and puts them at risk for relapse into further episodes of depression.

Rinegan: A Scalable Image Processing Architecture for Large Scale Surveillance Applications.

Image processing is widely used in intelligent robots, significantly improving the surveillance capabilities of smart buildings, industrial parks, and border ports. However, relying on the camera installed in a single robot is not enough since it only provides a narrow field of view as well as limited processing performance. Specially, a target person such as the suspect may appear anywhere and tracking the suspect in such a large-scale scene requires cooperation between fixed cameras and patrol robots. This induces a significant surge in demand for data, computing resources, as well as networking infrastructures. In this work, we develop a scalable architecture to optimize image processing efficacy and response rate for visual ability. In this architecture, the lightweight pre-process and object detection functions are deployed on the gateway-side to minimize the bandwidth consumption. Cloud-side servers receive solely the recognized data rather than entire image or video streams to identify specific suspect. Then the cloud-side sends the information to the robot, and the robot completes the corresponding tracking task. All these functions are implemented and orchestrated based on micro-service architecture to improve the flexibility. We implement a prototype system, called Rinegan, and evaluate it in an in-lab testing environment. The result shows that Rinegan is able to improve the effectiveness and efficacy of image processing.

Visualization of Arabidopsis root system architecture in 3D by refraction-contrast X-ray micro-computed tomography.

Plant roots change their morphological traits in order to adapt themselves to different environmental conditions, resulting in the alteration of the root system architecture. To understand this mechanism, it is essential to visualize the morphology of the entire root system. To reveal effects of long-term alteration of gravity environment on root system development, we have performed an experiment in the International Space Station using Arabidopsis plants and obtained dried root systems grown in rockwool slabs. The X-ray computed tomography (CT) technique using industrial X-ray scanners has been introduced to visualize the root system architecture of crop species grown in soil in 3D non-invasively. In the case of the present study, however, the root system of Arabidopsis is composed of finer roots compared with typical crop plants and rockwool is also composed of fibers having similar dimension to that of the roots. A higher spatial resolution imaging method is required for distinguishing roots from rockwool. Therefore, in the present study, we tested refraction-contrast X-ray micro-CT using coherent X-ray optics available at the beamline of the synchrotron radiation facility SPring-8 for bio-imaging. We have found that a wide field of view but with low resolution obtained at the experimental Hutch 3 of this beamline provided an overview map of the root systems, while a narrow field of view but with high resolution obtained at the experimental Hutch 1 provided an extended architecture of the secondary roots, by a clear distinction between roots and individual rockwool fibers, resulting in the successful tracing of these roots from their basal regions.

Sensor-Level Mosaic of Multistrip KOMPSAT-3 Level 1R Products

High-resolution satellite images such as KOMPSAT-3 data provide detailed geospatial information over interest areas that are evenly located in an inaccessible area. The high-resolution satellite cameras are designed with a long focal length and a narrow field of view to increase spatial resolution. Thus, images show relatively narrow swath widths (10–15 km) compared to dozens or hundreds of kilometers in mid-/low-resolution satellite data. Therefore, users often face obstacles to orthorectify and mosaic a bundle of delivered images to create a complete image map. With a single mosaicked image at the sensor level delivered only with radiometric correction, users can process and manage simplified data more efficiently. Thus, we propose sensor-level mosaicking to generate a seamless image product with geometric accuracy to meet mapping requirements. Among adjacent image data with some overlaps, one image is the reference, whereas the others are projected using the sensor model information with shuttle radar topography mission. In the overlapped area, the geometric discrepancy between the data is modeled in spline along the image line based on image matching with outlier removals. The new sensor model information for the mosaicked image is generated by extending that of the reference image. Three strips of KOMPSAT-3 data were tested for the experiment. The data showed that irregular image discrepancies between the adjacent data were observed along the image line. This indicated that the proposed method successfully identified and removed these discrepancies. Additionally, sensor modeling information of the resulted mosaic could be improved by using the averaging effects of input data.

A PORTABLE OPTO-ACOUSTIC SURVEY SOLUTION FOR MAPPING OF UNDERWATER TARGETS

Abstract. During underwater investigations, whatever the mission objective and the type of vehicle, obstacles detection and avoidance are essential tasks. They can either represent a target of interest that is the object of the mission or, on the contrary, represent obstacles that can hinder or affect the navigation of the vehicle. The underwater optical cameras that are usually fitted to underwater vehicles only offer a narrow field of view. The absorption of electromagnetic waves in the first few meters and the diffusion of light by the particles limit the use of these sensors to only a few meters range. The use of acoustic sensors, such as the forward looking sonar (FLS), is then necessary to enlarge the volume in which a target can be detected during the progression of the vehicle. Traditionally, sonars featured mechanical rotating parts, but lately bidirectional forward looking sonar, which directly produces a 2D image of the area, are becoming more and more common. Although these sonars can operate at frequency higher than 1MHz, their spatial resolution remains much lower if compared to current optical sensors and can be insufficient to identify and characterize a target. The combination of these two sensors in an operational scenario is essential to take advantage of each technology. In this paper we describe a low cost, multi-sensor, underwater survey solution for the identification, tracking, and 3D mapping of targets. After a description of the architecture of the opto-acoustics data acquisition and processing platform, we will focus on the calibration of the rigid transformation between the two sensors.

Google Glass-Supported Cooperative Training for Health Professionals: A Case Study Based on Using Remote Desktop Virtual Support

PurposeObservation of medical trainees’ care performance by experts can be extremely helpful for ensuring safety and providing quality care. The advanced technology of smart glasses enables health professionals to video stream their operations to remote supporters for collaboration and cooperation. This study monitored the clinical situation by using smart glasses for remote cooperative training via video streaming and clinical decision-making through simulation based on a scenario of emergency nursing care for patients with arrhythmia.Participants and MethodsThe clinical operations of bedside trainees, who is Google Glass Enterprise Edition 2(Glass EE2) wearers, were live streamed via their Google Glasses, which were viewed at a remote site by remote supporters via a desktop computer. Data were obtained from 31 nursing students using eight essay questions regarding their experience as desktop-side remote supporters.ResultsMost of the participants reported feeling uneasy about identifying clinical situations (84%), patients’ condition (72%), and trainees’ performance (69%). The current system demonstrated sufficient performance with a satisfactory level of image quality and auditory communication, while network and connectivity are areas that require further improvement. The reported barriers to identifying situations on the remote desktop were predominantly a narrow field of view and motion blur in videos captured by Glass EE2s, and using the customized mirror mode.ConclusionThe current commercial Glass EE2 can facilitate enriched communication between remotely located supporters and trainees by sharing live videos and audio during clinical operations. Further improvement of hardware and software user interfaces will ensure better applicability of smart glasses and video streaming functions to clinical practice settings.

The Automatic Observation Management System of the GWAC Network. I. System Architecture and Workflow

The Ground Wide Angle Camera Network (GWAC-N) is a network of robotic multi-aperture, multiple field-of-view (FoV) optical telescopes. The main contingent of GWAC-N instruments are provided by the Ground Wide Angle Cameras Array (GWAC-A), and additional, narrower FoV telescopes are utilized to provide fast multi-band follow-up capabilities. The primary scientific goal of the GWAC-N is to search for optical counterparts of gamma-ray bursts that will be detected by the Space Variable Object Monitor (SVOM) satellite. The GWAC-N performs many additional observing tasks including follow-up of Target of Opportunities (ToO) targets and the detection (and monitoring) of variable objects and optical transients. To handle these use cases (and to allow for extensibility), we have designed ten observation modes and 175 observation strategies, including a joint strategy with multiple GWAC-N telescopes for the follow-up of gravitational wave (GW) events. To perform these observations, we develop an Automatic Observation Management (AOM) system capable of performing object management, dynamic scheduling, automatic broadcasting across the network, and image handling. The AOM system combines the individual telescopes which comprise the GWAC-N into a network and smoothly organizes all associated operations, completely meeting the requirements dictated by GWAC-N. With its modular design, the AOM is scientifically and technically viable for other general-purpose telescope networks. As the GWAC-N extends and evolves, the AOM will greatly enhance its discovery potential. In this first paper of a series, we present the scientific goals of the GWAC-N and detail the hardware, software, and workflow developed to achieve these goals. The structure, technical design, implementation, and performance of the AOM system are also described in detail. We conclude with a summary of the current status of the GWAC-N and our near-future development plan.

Fusion of 4D Point Clouds From a 2D Profilometer and a 3D Lidar on an Excavator

The research aimed to integrate a solid-state 2D-pulsed time-of-flight (TOF) flash Lidar profilometer and a mechanically scanning 3D Lidar in order to monitor the 4D (3D + signal intensity) environment at a construction site from an excavator. Utilizing the excavator's GNSS and IMU sensor data enables to fuse the profilometer and 3D Lidar point clouds into the same coordinate system. Both measurement devices have quite a narrow field of view, but the overall viewing angle is expanded due to the movement of the excavator boom and rotation of the excavator cab. The major advantage of this combination method is that the profilometer provides centimetre-accurate details of the worksite within a range of approximately 1-10 m, while the commercial 3D Lidar scanner provides a larger scale (roughly 1-64 m) description of the worksite with an accuracy of ±6 cm. Additionally, the profilometer's intensity information can be used to identify people on the basis of varying reflective vest patterns. The experimental results indicate that our combination system can accurately build a quality 4D point cloud map better than either individual device on its own. The combination of Lidars could prove to be an interesting tool, with the potential to improve construction site management processes.