Open Access

ARTICLE

Sajib Sarker, Ling Tan^*, Wenjie Ma, Shanshan Rong, Osibo Benjamin Kwapong, Oscar Famous Darteh
Journal on Internet of Things, Vol.3, No.2, pp. 39-51, 2021, DOI:10.32604/jiot.2021.014877
Abstract The novel coronavirus 2019 (COVID-19) rapidly spreading around the world and turns into a pandemic situation, consequently, detecting the coronavirus (COVID-19) affected patients are now the most critical task for medical specialists. The deficiency of medical testing kits leading to huge complexity in detecting COVID-19 patients worldwide, resulting in the number of infected cases is expanding. Therefore, a significant study is necessary about detecting COVID-19 patients using an automated diagnosis method, which hinders the spreading of coronavirus. In this paper, the study suggests a Deep Convolutional Neural Network-based multi-classification framework (COVMCNet) using eight different pre-trained architectures such as VGG16, VGG19,… More >

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Open Access

ARTICLE

Jesus Hamilton Ortiz¹, Javier Ferney Castillo García², Osamah Ibrahim Khalaf³, Fernando Velez Varela^2,*, Pedro Jefferson Barragan Baron², Jhon Hadder Guzmán Atehortúa²
Journal on Internet of Things, Vol.3, No.2, pp. 53-63, 2021, DOI:10.32604/jiot.2021.014736
Abstract This work shows the development of a module that performs measurements of electrical variables in a low voltage power transformer. These variables are sent by means of the IEEE802.11 standard, connecting to a database stored in the cloud; associating with the meter IoT concepts, this to allow a client to perform an analysis, monitoring and management of their electrical network. For the construction of this module, non-invasive current sensors connected to a three-phase meter are used and a communication card is used that allows data to be extracted from the meter and sent to the cloud database. This module, to… More >

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ARTICLE

Zejun Yang¹, Denghui Xia¹, Jin Liu¹, Chao Zheng², Yanzhen Qu^1,3,4, Yadang Chen¹, Chengjun Zhang^1,2,3,*
Journal on Internet of Things, Vol.3, No.2, pp. 65-76, 2021, DOI:10.32604/jiot.2021.015401
Abstract Collaborative filtering algorithms (CF) and mass diffusion (MD) algorithms have been successfully applied to recommender systems for years and can solve the problem of information overload. However, both algorithms suffer from data sparsity, and both tend to recommend popular products, which have poor diversity and are not suitable for real life. In this paper, we propose a user internal similarity-based recommendation algorithm (UISRC). UISRC first calculates the item-item similarity matrix and calculates the average similarity between items purchased by each user as the user’s internal similarity. The internal similarity of users is combined to modify the recommendation score to make… More >

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Benjamin Kwapong Osibo¹, Chengbo Zhang¹, Changsen Xia¹, Guanzhe Zhao², Zilong Jin^1,3,*
Journal on Internet of Things, Vol.3, No.2, pp. 77-86, 2021, DOI:10.32604/jiot.2021.017943
Abstract Modern vehicles are equipped with sensors, communication, and computation units that make them capable of providing monitoring services and analysis of real-time traffic information to improve road safety. The main aim of communication in vehicular networks is to achieve an autonomous driving environment that is accident-free alongside increasing road use quality. However, the demanding specifications such as high data rate, low latency, and high reliability in vehicular networks make 5G an emerging solution for addressing the current vehicular network challenges. In the 5G IoV environment, various technologies and models are deployed, making the environment open to attacks such as Sybil,… More >

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