Smart Campus: Trends in cybersecurity and future development

Smart Campus is an entity of any kind that uses technology and infrastructure to support and improve its processes, so people can use them better. This paper reviews the literature to contextualize the Internet of Things and its vital importance for the Smart Campus, as well as its relationship with the concepts of cybersecurity and wireless sensor network. We describe the various interrelationships, tendencies, and future development of a Smart Campus, as well as the differences and similarities with the emerging concept of Smart University. This review revealed that the Internet of Things is involved in all fields and can influence and improve the university’s processes to contribute to decision-making, technological development, and academic learning. To conclude, Smart University focuses on improving the infrastructure of universities through technology, with the main purpose of enhancing the quality of the education provided by institutions.

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Application of the Internet of Things through a Network of Wireless Sensors in a Coffee Crop for Monitoring and Control its Environmental Variables

TecnoLógicas ◽

10.22430/22565337.1485 ◽

2019 ◽

Vol 22 (46) ◽

pp. 155-170

Author(s):

William Ruíz Martínez ◽

Yesid Díaz-Gutiérrez ◽

Roberto Ferro-Escobar ◽

Luis Pallares

Keyword(s):

Internet Of Things ◽

Environmental Variables ◽

Wireless Sensor ◽

The Internet ◽

Monitoring And Control ◽

Technological Tool ◽

Coffee Cultivation ◽

And Control ◽

The Internet Of Things

This article presents the application of the Internet of things (IoT), as a technological tool for the development of a wireless sensor network with the aim of monitoring and controlling a series of environmental variables affecting the cultivation of coffee and its final quality. The logical and physical design of the network and its devices was carried out, the sensors network was configured in a given field and the information of certain environmental variables was collected to be compared with a series of parameters already established. This procedure will allow the coffee growers to observe the behavior of these variables over time and set the generation of alerts or warnings when these measures are outside the established ranges. The study determined that the management of coffee cultivation is quite complex due to the large number of varieties found, the terrain and environmental variables affecting the production process and the final quality of the grain. It was also determined that the development and implementation of wireless sensor networks is possible today due to factors such as the reduction of device costs and the use of open source software, avoiding additional licensing values. Finally, based on the parameters analyzed, it was possible to establish that one of the main problems in coffee crops is the intense humidity that, in practice, can affect the performance of the sensors and their measurements.

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Review of the Current State and Future Development in Standardising Artificial Lighting

Light & Engineering ◽

10.33383/2019-011 ◽

2019 ◽

pp. 4-44 ◽

Cited By ~ 1

Author(s):

Peter Thorns

Keyword(s):

Internet Of Things ◽

Future Development ◽

Best Practice ◽

The Internet ◽

Artificial Lighting ◽

Current State ◽

Internal Structures ◽

European Regulations ◽

The Internet Of Things

This paper discusses the organisations involved in the development of application standards, European regulations and best practice guides, their scope of work and internal structures. It considers their respective visions for the requirements for future standardisation work and considers in more detail those areas where these overlap, namely human centric or integrative lighting, connectivity and the Internet of Things, inclusivity and sustainability.

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A Bi-feedback System of Wireless Sensor Network Event Detection in the Internet of Things

Chinese Journal of Computers ◽

10.3724/sp.j.1016.2013.00506 ◽

2014 ◽

Vol 36 (3) ◽

pp. 506-520

Author(s):

Jing YANG ◽

Yu XIN ◽

Zhi-Qiang XIE

Keyword(s):

Wireless Sensor Network ◽

Internet Of Things ◽

Sensor Network ◽

Event Detection ◽

Feedback System ◽

Wireless Sensor ◽

The Internet ◽

The Internet Of Things ◽

Network Event

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A Systematic Literature Review of Supply Chain Decision Making supported by the Internet of Things and Big Data Analytics

Computers & Industrial Engineering ◽

10.1016/j.cie.2020.107076 ◽

2020 ◽

pp. 107076

Author(s):

Martijn Koot ◽

Martijn R.K. Mes ◽

Maria E. Iacob

Keyword(s):

Decision Making ◽

Big Data ◽

Supply Chain ◽

Internet Of Things ◽

Literature Review ◽

Systematic Literature Review ◽

Data Analytics ◽

Big Data Analytics ◽

The Internet ◽

The Internet Of Things

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A Fog Computing Framework for Quality of Service Optimisation in the Internet of Things (IoT) Ecosystem

2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC) ◽

10.1109/imitec50163.2020.9334083 ◽

2020 ◽

Author(s):

William Tichaona Vambe ◽

Khulumani Sibanda

Keyword(s):

Quality Of Service ◽

Internet Of Things ◽

Fog Computing ◽

The Internet ◽

Computing Framework ◽

The Internet Of Things

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An Overview of Periodic Wireless Sensor Networks to The Internet of Things

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/928/3/032055 ◽

2020 ◽

Vol 928 ◽

pp. 032055

Author(s):

Ali Kadhum M. Al-Qurabat ◽

Suha Abdulhussein Abdulzahra

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Internet Of Things ◽

Wireless Sensor ◽

The Internet ◽

The Internet Of Things

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Problems of Powering End Devices in Wireless Networks of the Internet of Things

Energies ◽

10.3390/en14092417 ◽

2021 ◽

Vol 14 (9) ◽

pp. 2417

Author(s):

Andrzej Michalski ◽

Zbigniew Watral

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Internet Of Things ◽

Radio Frequency Identification ◽

Wireless Sensor ◽

Alternative Possibilities ◽

The Internet ◽

Power Sources ◽

Wide Range ◽

The Internet Of Things

This article presents the problems of powering wireless sensor networks operating in the structures of the Internet of Things (IoT). This issue was discussed on the example of a universal end node in IoT technology containing RFID (Radio Frequency Identification) tags. The basic methods of signal transmission in these types of networks are discussed and their impact on the basic requirements such as range, transmission speed, low energy consumption, and the maximum number of devices that can simultaneously operate in the network. The issue of low power consumption of devices used in IoT solutions is one of the main research objects. The analysis of possible communication protocols has shown that there is a possibility of effective optimization in this area. The wide range of power sources available on the market, used in nodes of wireless sensor networks, was compared. The alternative possibilities of powering the network nodes from Energy Harvesting (EH) generators are presented.

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A Novel Bioinspired Multiobjective Optimization Algorithm for Designing Wireless Sensor Networks in the Internet of Things

Journal of Sensors ◽

10.1155/2015/192194 ◽

2015 ◽

Vol 2015 ◽

pp. 1-16 ◽

Cited By ~ 4

Author(s):

Jun Huang ◽

Liqian Xu ◽

Cong-cong Xing ◽

Qiang Duan

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Internet Of Things ◽

Multiobjective Optimization ◽

Optimization Algorithm ◽

Chaotic Behavior ◽

Ant Colony ◽

Wireless Sensor ◽

The Internet ◽

The Internet Of Things

The design of wireless sensor networks (WSNs) in the Internet of Things (IoT) faces many new challenges that must be addressed through an optimization of multiple design objectives. Therefore, multiobjective optimization is an important research topic in this field. In this paper, we develop a new efficient multiobjective optimization algorithm based on the chaotic ant swarm (CAS). Unlike the ant colony optimization (ACO) algorithm, CAS takes advantage of both the chaotic behavior of a single ant and the self-organization behavior of the ant colony. We first describe the CAS and its nonlinear dynamic model and then extend it to a multiobjective optimizer. Specifically, we first adopt the concepts of “nondominated sorting” and “crowding distance” to allow the algorithm to obtain the true or near optimum. Next, we redefine the rule of “neighbor” selection for each individual (ant) to enable the algorithm to converge and to distribute the solutions evenly. Also, we collect the current best individuals within each generation and employ the “archive-based” approach to expedite the convergence of the algorithm. The numerical experiments show that the proposed algorithm outperforms two leading algorithms on most well-known test instances in terms of Generational Distance, Error Ratio, and Spacing.

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