Contemporary research trends in response robotics

Dadvar, Mehdi; Habibian, Soheil

doi:10.1186/s40648-022-00221-z

Cited by 3 publications

(2 citation statements)

References 58 publications

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“…All the agenda mentioned above of disaster management is fulfilled using various technologies viz. GIS [9], remote sensing [10], early warning system [11], unmanned aerial vehicles (drones) [12], big data analytics [13], Artificial Intelligence [14], Mobile applications [15], robotics [16], blockchain technology [17], satellite communications [18]. It was also noted that the involvement of machine learning and artificial intelligence is slowly increasing in its pace, contributing towards optimizing the strategies of responses by predicting disasters and identifying patterns.…”

Section: Introductionmentioning

confidence: 99%

Exhaustive Insights Towards Social-Media Driven Disaster Management Approaches

Krishnappa,

Saraswathi,

Chelliah

2024

ijacsa

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The manuscript presents discussion about the disaster management approaches using social media. It is noted that rising popularity of social media has been witnessed to significantly contribute towards information propagation and community participation to deal with the event of disaster. Different from conventional disaster management policies, the scope of inclusion of social media-based approaches are quite novel and yet promising. However, the problem is towards unclear information about the effectivity of such schemes. Hence, this manuscript contributes towards bridging this information gap by carrying out an exhaustive and systematic review of existing methodology frequently adopted towards disaster management using social media viz. early warning methods, information dissemination methods, crisis mapping method, and predictive approach, where Artificial Intelligence was noted to be quite dominant scheme. The contributory findings of this review study contribute towards clear visualization of updated research trends, critical learning outcomes associated with identified research gap with illustrated discussion of the reviewed articles. A clear and informative study findings contributes towards future researchers. The result of review has also answered the formed research question to give potential insight towards existing system. The result of the review finds that existing approaches has both beneficial aspect and limitation associated with complex learning approaches, higher infrastructural cost, model complexities, security threats, higher resource dependencies.

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Section: Introductionmentioning

confidence: 99%

Exhaustive Insights Towards Social-Media Driven Disaster Management Approaches

Krishnappa,

Saraswathi,

Chelliah

2024

ijacsa

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“…In recent decades, many research have been conducted on automation of tasks employing robots [9][10][11][12], including robotic platforms automation of welding operation to accelerate the process and reduce human error. As an instance, Figure 1 shows a robotic digital X-ray photographer by Stanley Oil and Gas.…”

Section: Introductionmentioning

confidence: 99%

Real‐Time Explainable Multiclass Object Detection for Quality Assessment in 2‐Dimensional Radiography Images

Naddaf-Sh

Zargarzadeh

et al. 2022

Complexity

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Quality inspection and defect detection play a critical role in infrastructure safety and integrity specially when it comes to aging infrastructure mostly owned by governments around the world. One of the prevalent inspections performed in the industry is nondestructive testing (NDT) using radiography imaging. Growing demand, shortage of experts, diversity of required skills, and specific regional standards with a time-limited requirement of inspection results make automated inspection an urgent need. Therefore, utilizing artificial intelligence- (AI-) based tools as an assistive technology has become a trend for industrial applications, which automates repeated tasks and provides increased confidence before and during the inspection operation. Most of the works in quality assessment are focused on the classification of few categories of defects and mostly performed on public or noncomprehensive research datasets. In this work, a scalable, efficient, and real-time deep learning family of models for detection and classification of 10 various categories of weld characteristics on a real-world industrial dataset is presented. The models are evaluated and compared against each other, various critical hyperparameters and components are optimized, and local explainability of models is discussed. Additionally, AutoAugment for object detection and various techniques are utilized and investigated. The best performance for object detection and classification for 10 class models is reached by mean average precision of 72.4% and top-1 accuracy of 90.2%, respectively. Also, the fastest object detection model is able to evaluate a full 15360 × 1024 pixels weld image in 0.39 seconds. Finally, the proposed models are deployable on edge-devices to perform as assistant to NDT experts or auditing professionals.

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Mapping of the selected literature on robotic technology applications in libraries based on Scopus database: a subjective computational review

Basumatary,

Yuvaraj,

Verma

et al. 2023

LHT

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PurposeAdopting and implementing robotic technology applications in the library is a significant technological up-gradation today. The purpose of this study was to evaluate selected literature focused mainly on robotics technology applications in the field of libraries and to assess the online social attention to research publications.Design/methodology/approachThe study employed Scientometric and altmetric tools to evaluate the research publications. The bibliographic data of research publications were downloaded from Scopus database and scrutinized one by one and 71 articles were selected which mainly focused on robotic technology in libraries. Altmetric data were collected from the Dimensions.ai database. The analysis was performed using MS Excel, Tableau, Biblioshiny, VOSviewer and SPSS software.FindingsResearch on robotic technology in the field of libraries has been experiencing a gradual increase, marked by an annual growth rate of 12.93%. The United States has prominently led the way as the most active participant and collaborator in this advancement. Among the various journals, Library Hi Tech has notably stood out as a significant contributor to this field. However, the research articles have garnered limited social attention and impact. Furthermore, the patterns of authorship collaboration have demonstrated relatively modest levels within the field, and a weak correlation has been observed between the social attention received and the Scopus citation metrics of the publications.Practical implicationsThe research needs to be disseminated more through various social media platforms to increase its visibility. Sharing research information through social media can bridge the gap between academia and society. The findings of this study can serve as a valuable reference for researchers and policymakers.Originality/valueThis study presents a Scientometric analysis of the selected published literature on robotics technology applications in the field of libraries, highlighting the progress and development of worldwide research in this area.

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Contemporary research trends in response robotics

Cited by 3 publications

References 58 publications

Exhaustive Insights Towards Social-Media Driven Disaster Management Approaches

Exhaustive Insights Towards Social-Media Driven Disaster Management Approaches

Real‐Time Explainable Multiclass Object Detection for Quality Assessment in 2‐Dimensional Radiography Images

Mapping of the selected literature on robotic technology applications in libraries based on Scopus database: a subjective computational review

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