Retracted: Analysis and Data Mining of Students' Consumption Behavior Based on a Campus Card System

Jiang, Tongjun; Cao, Jun; Su, Dan; Yang, Xianglai

doi:10.1109/icscse.2017.22

Cited by 11 publications

(7 citation statements)

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“…Instead of a smart card, the latest developments suggested the use of the Near-Field Communications (NFC) interface of a smartphone to provide the mentioned smart campus applications [115]. Due to the multiple potential applications of smart cards, some authors also proposed to mine the data collected from the student transactions to infer their behavior [116,117].…”

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confidence: 99%

Towards Next Generation Teaching, Learning, and Context-Aware Applications for Higher Education: A Review on Blockchain, IoT, Fog and Edge Computing Enabled Smart Campuses and Universities

2019

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Smart campuses and smart universities make use of IT infrastructure that is similar to the one required by smart cities, which take advantage of Internet of Things (IoT) and cloud computing solutions to monitor and actuate on the multiple systems of a university. As a consequence, smart campuses and universities need to provide connectivity to IoT nodes and gateways, and deploy architectures that allow for offering not only a good communications range through the latest wireless and wired technologies, but also reduced energy consumption to maximize IoT node battery life. In addition, such architectures have to consider the use of technologies like blockchain, which are able to deliver accountability, transparency, cyber-security and redundancy to the processes and data managed by a university. This article reviews the state of the start on the application of the latest key technologies for the development of smart campuses and universities. After defining the essential characteristics of a smart campus/university, the latest communications architectures and technologies are detailed and the most relevant smart campus deployments are analyzed. Moreover, the use of blockchain in higher education applications is studied. Therefore, this article provides useful guidelines to the university planners, IoT vendors and developers that will be responsible for creating the next generation of smart campuses and universities.

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confidence: 99%

Towards Next Generation Teaching, Learning, and Context-Aware Applications for Higher Education: A Review on Blockchain, IoT, Fog and Edge Computing Enabled Smart Campuses and Universities

2019

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“…Data mining involves discovering valuable information, knowledge and pattern behind a large volume of data using machine learning to make decisions and measure performance (Qin and Chi, 2020;Vivi et al, 2015;Jiang et al, 2017). Most university campuses use data mining to assess student's grades, evaluate student's involvement in class activities, library usage, and campus applications.…”

Section: Continuous Improvement Of the Smart Campusmentioning

confidence: 99%

A Systems Thinking Model for Transitioning Smart Campuses to Cities

Omotayo

Awuzie

Ajayi

et al. 2021

Front. Built Environ.

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The contribution of smart campuses to smart cities’ development and vice versa has been elucidated in extant literature. The micro-transfer of smart technologies and probable procurement and contracting models remain critical for such contributions to take place. This study used a systems thinking approach to establish the interrelationships existing between smart campus technologies which can be scaled towards the development of smart cities and assess the critical failure factors negating the micro-transfer of these technologies to smart city development initiatives in developing countries. To achieve its objective, the study adopted a phenomenological research design wherein qualitative data was elicited from a purposively selected sample of seven interviewees in South African Universities. The next phase of the analysis involved a thematic approach for the production of a causal loop diagram (CLD) reflecting the interrelationships between the abovementioned facets and the associated impact on the transference of knowledge and technologies from smart campuses to smart cities. This CLD was subsequently validated by a cohort of five experts. Findings from the validation phase were incorporated in an improved CLD which provided different archetypes for engendering successful transference. This study holds salient implications for universities, cities and other stakeholders seeking to engage in a quadruple helix innovative arrangement for smart campus/city development. This study concluded that smart campuses could act as living labs for future smartness of cities globally. Government funding and willingness to produce smart cities from campuses is a fundamental feature of creating smart infrastructure in cities.

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“…The data used in existing research includes student's basic personal information, family situation information, consumption records, and based on them, two kinds of the features are extracted [16][17][18][19][20]. One kind is the personal and family features including gender, family annual income, etc.…”

Section: Related Workmentioning

confidence: 99%