Problems and Prospects of Internet of Things to the Automobile Industry in Nigeria

Mustapha, Aliyu; Abubakar, Abdullahi; Ahmed, Haruna Dokoro; Ndakara, Isah Abubakar; Abubakar, Ibrahim Ahmad; Egigogo, Abdullahi Raji; Abdulkadir, M.

doi:10.1109/nigeriacomputconf45974.2019.8949649

Cited by 4 publications

(2 citation statements)

References 1 publication

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“…Te application of IoT in business provides many benefts such as the following: efective management of work, increased productivity and business efciency, creation of new business models and revenue streams, increased safety at work, improved staf productivity and reduction of human labor easily and seamlessly, and connection of the physical business world with the digital world to achieve the set values and goals faster. IoT is applied in many areas such as manufacturing [31], logistics and supply chains [32,33], automotive industry [34], trade [35], construction industry [36], health care [37], and "smart houses" [38]. Technologies that are often implemented in the IoT domain are machine-to-machine (M2M) communication and radio frequency identifcation (RFID) [39].…”

Section: Related Workmentioning

confidence: 99%

A Novel Hybrid Model for the Evaluation of Industry 4.0 Technologies’ Applicability in Logistics Centers

Miškić

Tadić

Stević

et al. 2023

Journal of Mathematics

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The application of Industry 4.0 (I4.0) in the field of logistics leads to the emergence and development of the concept of logistics 4.0. Many I4.0 technologies have been applied in the field of logistics. The goal of this research is to analyze the applicability of nine key I4.0 technologies in logistics centers (LC). For this purpose, an integrated MEREC (MEthod based on the Removal Effects of Criteria)—fuzzy MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) model was developed. The applicability of nine I4.0 technologies was evaluated based on 15 subcriteria within three main groups of criteria, namely, technological, social and political, and economic and operative. Using the MEREC method, the weight values of the criteria and subcriteria were determined, while the technologies were ranked using the fuzzy MARCOS method. Based on the results obtained by applying this integrated MCDM (multicriteria decision-making) model, CC was identified as the best alternative, i.e., the technology that is most applicable in logistics centers, followed by IoT and big data. An analysis of the sensitivity of the obtained results to the change in the importance of the criteria was carried out, which shows certain changes in the ranking when the importance of the most important criterion changes.

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Section: Related Workmentioning

confidence: 99%

A Novel Hybrid Model for the Evaluation of Industry 4.0 Technologies’ Applicability in Logistics Centers

Miškić

Tadić

Stević

et al. 2023

Journal of Mathematics

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“…Technical Vocational Education and Training (TVET) is a field which persistently needs to be assessed to track the swift rate of development in the labour force. An essential component that has fundamentally changed the way TVET education is carried out is technology; such technologies include, among others, mobile gadgets (smartphones), remote access systems and teleconference [1]. These technologies are used in teaching and learning processes, however, in addition to practically echoing in the learning process in real setting generate an enormous amount of new data that are devastated as conventional learning methods are not capable of processing them.…”

Section: Introductionmentioning

confidence: 99%

Application of Big Data Analytics for Improving Learning Process in Technical Vocational Education and Training

Mustapha

Abubakar

Ahmed

et al. 2021

Communications in Computer and Information Science

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The study identifies the application of big data analytics for improving learning process in Technical Vocational Educational and Training (TVET) in Nigeria. Two research questions were answered. The descriptive survey design was employed and the target population was made up of experts in TVET. A structured questionnaire titled "Big Data Analytics in Technical Vocational Education and Training" (BDATVET) is the tool used for data compilation. BDATVET was subjected to face and content validation by three experts, two in TVET and one in Education Technology. Cronbach Alpha was used to determine the reliability coefficient of the questionnaire and it was found to be 0.81. The data collected from the respondents were analyzed using mean and standard deviation. The findings on the problems of big data include among others security, availability and stability of internet network service. The Findings related to the prospects include among others, allows a teacher measuring, monitoring, and responding, in realtime to a student's understanding of the material. Based on the findings, it was recommended among others that the stakeholders in TVET need to uphold the fundamental security of their data and who may access information about their competencies.

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Machine learning for Internet of things: A Recapitulation

Gangal

Johri

Kumar

2021

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)

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Problems and Prospects of Internet of Things to the Automobile Industry in Nigeria

Cited by 4 publications

References 1 publication

A Novel Hybrid Model for the Evaluation of Industry 4.0 Technologies’ Applicability in Logistics Centers

A Novel Hybrid Model for the Evaluation of Industry 4.0 Technologies’ Applicability in Logistics Centers

Application of Big Data Analytics for Improving Learning Process in Technical Vocational Education and Training

Machine learning for Internet of things: A Recapitulation

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