Neuro-Dominating set scheme for a fast and efficient robot deployment in internet of robotic things

Razafimandimby, Cristanel; Loscrì, Valeria; Vegni, Anna Maria; Benslimane, Abderrahim

doi:10.1016/j.adhoc.2018.08.016

Cited by 5 publications

(6 citation statements)

References 47 publications

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“…Recent research is now beginning to shift, from the IoT paradigm to just being passive so far, to then add an active role to IoT devices using robots. ABI research introduces a new concept called Internet of Robotic Things (IoRT) as a set of intelligent devices that can monitor events, integrate sensor data from various sources, use local intelligence and then distribute it to determine the best actions, ultimately acting to control or manipulate objects in physical world (Razafimandimby et al., 2019). An interesting vision for the IoT is a group of flying robots (robot bees) that can provide enormous collective intelligence to gather information.…”

Section: Resultsmentioning

confidence: 99%

Knowledge growth and development: internet of things (IoT) research, 2006–2018

Dachyar

Zagloel

Saragih

2019

Heliyon

101

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The term "Internet of Things" first appeared in publication paper since 2006, describing the paradigm of evolution concept that brought about by the presence of internet technology (Vermesan and Friess, 2015) which is very important in contemporary circumstances. This study conducted an in-depth analysis of the research material written on 26420 papers which focused on the published Internet of Things (IoT) research, starting from the firstly year IoT keyword appeared in 2006 until 2018. The selected paper is a combination of various disciplines and publications which are all indexed by Scopus wherein the article discusses IoT. IoT articles are classified using key attributes in sequence: the methodology used, general knowledge and applied concepts, and various general exploration topics. By using the Scientometrics method, this method will group the overall terms that appear frequently from the Scopus paper database according to keywords, titles, and abstracts. The resulting data is then studied to understand and distinguish trends that occur in the time span along with the general characteristics of the paper, in the mathematics visual scheme. All various issues that are considered in the paper's methodology selection, their studied and services innovations, and continuing discoveries on the characteristics, concepts, and processes applied to IoT success. Although it only involves scopus indexed paper, this study found a remarkable increase in the number of articles on IoT in each category of the paper. This study also reveals the direction of the regular discipline of knowledge. The use of the Scientometrics method makes the analysis able to focus on the movement of characteristics and IoT themes to researcher's direction that has not found at this time, as a comprehensive guide to further research and industry strategy that is more directed on concepts that support the 4th industrial revolution.

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Section: Resultsmentioning

confidence: 99%

Knowledge growth and development: internet of things (IoT) research, 2006–2018

Dachyar

Zagloel

Saragih

2019

Heliyon

101

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“…[ [41][42][43][44][45][46][47][48][49][50][51][52] Autonomous robots and mobile context awareness systems deploy sensor devices, machine learning algorithms, and convolutional neural networks as regards acoustic environment recognition. Connected IoRT mobile devices and collaborative robots gather and sense data from the surrounding environment across fog and cloud computing networks.…”

Section: Methodsmentioning

confidence: 99%

“…Cloud computing machines, machine learning and remote sensing algorithms, and cyber-physical production systems [41][42][43][44] facilitate data transfer and object manipulation across intelligent simulation environments and smart factories [45][46][47][48] by integrating embedded IoRT-based sensors, thus optimizing productivity and efficiency. Data mining and context recognition tools enhance sensing and actuation capabilities of robotic networks [49][50][51][52] as autonomous agents.…”

Section: Introductionmentioning

confidence: 99%

Remote Big Data Management Tools, Sensing and Computing Technologies, and Visual Perception and Environment Mapping Algorithms in the Internet of Robotic Things

et al. 2022

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The purpose of our systematic review was to inspect the recently published research on Internet of Robotic Things (IoRT) and harmonize the assimilations it articulates on remote big data management tools, sensing and computing technologies, and visual perception and environment mapping algorithms. The research problems were whether robotic manufacturing processes and industrial wireless sensor networks shape IoRT and lead to improved product quality by use of remote big data management tools, whether IoRT devices communicate autonomously regarding event modeling and forecasting by leveraging machine learning and clustering algorithms, sensing and computing technologies, and image processing tools, and whether smart connected objects, situational awareness algorithms, and edge computing technologies configure IoRT systems and cloud robotics in relation to distributed task coordination through visual perception and environment mapping algorithms. A Shiny app was harnessed for Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines to configure the flow diagram integrating evidence-based gathered and processed data (the search outcomes and screening procedures). A quantitative literature review of ProQuest, Scopus, and the Web of Science databases was carried out throughout June and October 2022, with search terms including “Internet of Robotic Things” + “remote big data management tools”, “sensing and computing technologies”, and “visual perception and environment mapping algorithms”. Artificial intelligence and intelligent workflows by use of AMSTAR (Assessing the Methodological Quality of Systematic Reviews), Dedoose, DistillerSR, and SRDR (Systematic Review Data Repository) have been deployed as data extraction tools for literature collection, screening, and evaluation, for document flow monitoring, for inspecting qualitative and mixed methods research, and for establishing robust outcomes and correlations. For bibliometric mapping by use of data visualization, Dimensions AI was leveraged and with regards to layout algorithms, VOSviewer was harnessed.

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“…Recall that D ⊆ V (G) is a dominating set of a graph G if every vertex of V (G) \ D has a neighbor in D. The domination problem is a classic problem in graphs having many relevant applications, such as in communication and computer networks [20] (especially playing an important role as the backbone of the wireless design [3,16]), influence analysis in social medias [1], and topics regarding Internet of Robotic Things [17]. It can be stated as:…”

Section: Introductionmentioning

confidence: 99%

Expanded-clique graphs and the domination problem

Dourado¹,

Oliveira²,

Ponciano³

et al. 2022

Preprint

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Given a graph G and a function f :In this work, we present two characterizations of the expanded-clique graphs. One of them leads to a linear-time algorithm of recognition. We show that given an expanded-graph H, the domination number of H plus the 2-independence number of the root G of H is equal to |V (G)|. We also show that the domination problem is NP-complete for some subclasses of the expanded-clique graphs.

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Neuro-Dominating set scheme for a fast and efficient robot deployment in internet of robotic things

Cited by 5 publications

References 47 publications

Knowledge growth and development: internet of things (IoT) research, 2006–2018

Knowledge growth and development: internet of things (IoT) research, 2006–2018

Remote Big Data Management Tools, Sensing and Computing Technologies, and Visual Perception and Environment Mapping Algorithms in the Internet of Robotic Things

Expanded-clique graphs and the domination problem

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