What are IoT systems for real? An experts’ survey on software engineering aspects

Reggio, Gianna; Leotta, Maurizio; Cerioli, Maura; Spalazzese, Romina; Alkhabbas, Fahed

doi:10.1016/j.iot.2020.100313

Cited by 29 publications

(8 citation statements)

References 13 publications

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“…The Internet of Things (IoT) is the next generation of Internet technology that uses smart devices to connect the physical world and cyberspace [1]. IoT systems are becoming more pervasive, and their widespread adoption has had a significant impact on all aspects of life for billions of people in just a few years [2]. The Global Standards Initiative on the Internet of Things defines the IoT as "the global infrastructure for the information society that can facilitate interconnecting all types of objects, such as physical and virtual things based on the presented telecommunication protocols and technologies" [3] (p. 914).…”

Section: Introductionmentioning

confidence: 99%

Critical Factors Influencing Pre-Service Teachers’ Use of the Internet of Things (IoT) in Classrooms

Al-Abdullatif

Al-Dokhny

Drwish

2022

Int. J. Interact. Mob. Technol.

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This This study aims to explore the factors that influence pre-service teachers' decisions to use the Internet of Things (IoT) in a classroom setting as a digital system to enhance their teaching and learning. To achieve this aim, the technology acceptance model (TAM) is used to investigate the effects of using the IoT in an e-learning environment on pre-service teachers’ perceived usefulness, perceived ease of use, attitudes toward using IoT, and the influence of such attitudes on students’ behavior. Forty-seven final-year pre-service teaching students were selected to participate by purposeful sampling. A quantitative approach via regression analysis was conducted to analyze the collected data. The results showed that the TAM-related factors of perceived usefulness and perceived ease of use significantly contributed to pre-service teachers’ intentions to use the IoT in classrooms. However, their intention to use the IoT was not influenced by their attitude toward it. Implications and recommendations for future work are suggested as a result of this study.

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Section: Introductionmentioning

confidence: 99%

Critical Factors Influencing Pre-Service Teachers’ Use of the Internet of Things (IoT) in Classrooms

Al-Abdullatif

Al-Dokhny

Drwish

2022

Int. J. Interact. Mob. Technol.

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“…According to its definition, the Internet of Things is expansive. A few of the most popular IoT systems applications include intelligent industrial, smart city, smart building, smart home, intelligent transportation, healthcare, vehicle, and wearable devices [22].…”

Section: Literature Review and Establishment Of Research Hypothesesmentioning

confidence: 99%

Do People Prefer Cars That People Don’t Drive? A Survey Study on Autonomous Vehicles

Meidutė‐Kavaliauskienė

Yıldız

Çiğdem

et al. 2021

Energies

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Only recently, smart cities are taking shape, thanks to the rapid development of Internet of Things (IoT), cloud computing, and other similar technologies. Given the high demands placed on advanced technologies such as autonomous driving, cloud data services, and high-precision sensors, smart cities are creating an intelligent transportation environment conducive to the introduction of autonomous vehicles (AVs). In this context, the use of AVs in transportation is also considered a form of transportation innovation. As a result, AVs are considered more favorable to people interested in new technologies because they appear to be technologically superior. Their association with the most up-to-date technology can serve as a symbol for those who wish to demonstrate their interest in new technologies through their appearance. The positive image of technological innovation projected by AVs may influence their acceptance among technology enthusiasts to a significant degree. In this context, this study investigates the effects of perceived advantage, perceived risk, and perceived safety on the intention to use autonomous vehicles. For this purpose, data were collected from vehicle users living in Turkey by survey method. Secondly, factor analyses and regression analyses were performed with the data set obtained from 611 participants. As a result of the analyses, it has been determined that the perceived advantage and perceived security increase the intention to use autonomous vehicles. In contrast, the perceived risk reduces this intention to use. According to these results, recommendations were made to the companies about the level of acceptance of this technology by the users to assess their investments in autonomous vehicles better.

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“…COVID has created or expanded digital technology applications and use cases, proving to be a catalyst for digital transformation [ 3 ]. Companies have had to adapt as a result, individuals and governments to adapt/change their views and priorities on ethical/societal problems [ 4 ]. Because IoT penetration has been slower than projected in several sectors, numerous of the problems have been caused, and in the result of this, these problems must resolved or minimized.…”

Section: Introductionmentioning

confidence: 99%

Enabling image optimisation and artificial intelligence technologies for better Internet of Things framework to predict COVID

2022

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Sensor technology advancements have provided a viable solution to fight COVID and to develop healthcare systems based on Internet of Things (IoTs). In this study, image processing and Artificial Intelligence (AI) are used to improve the IoT framework. Computed Tomography (CT) image‐based forecasting of COVID disease is among the important activities in medicine for measuring the severity of variability in the human body. In COVID CT images, the optimal gamma correction value was optimised using the Whale Optimisation Algorithm (WOA). During the search for the optimal solution, WOA was found to be a highly efficient algorithm, which has the characteristics of high precision and fast convergence. Whale Optimisation Algorithm is used to find best gamma correction value to present detailed information about a lung CT image, Also, in this study, analysis of important AI techniques has been done, such as Support Vector Machine (SVM) and Deep‐Learning (Deep‐Learning (DL)) for COVID disease forecasting in terms of amount of data training and computational power. Many experiments have been implemented to investigate the optimisation: SVM and DL with WOA and without WOA are compared by using confusion matrix parameters. From the results, we find that the DL model outperforms the SVM with WOA and without WOA.

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What are IoT systems for real? An experts’ survey on software engineering aspects

Cited by 29 publications

References 13 publications

Critical Factors Influencing Pre-Service Teachers’ Use of the Internet of Things (IoT) in Classrooms

Critical Factors Influencing Pre-Service Teachers’ Use of the Internet of Things (IoT) in Classrooms

Do People Prefer Cars That People Don’t Drive? A Survey Study on Autonomous Vehicles

Enabling image optimisation and artificial intelligence technologies for better Internet of Things framework to predict COVID

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