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

[Abstract] 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.Xunta de Galicia; ED431C 2016-045Xunta de Galicia; ED431G/01Agencia Estatal de Investigación de España; TEC2016-75067-C4-1-

Design and experimental validation of a LoRaWAN fog computing based architecture for IoT enabled smart campus applications

A smart campus is an intelligent infrastructure where smart sensors and actuators collaborate to collect information and interact with the machines, tools, and users of a university campus. As in a smart city, a smart campus represents a challenging scenario for Internet of Things (IoT) networks, especially in terms of cost, coverage, availability, latency, power consumption, and scalability. The technologies employed so far to cope with such a scenario are not yet able to manage simultaneously all the previously mentioned demanding requirements. Nevertheless, recent paradigms such as fog computing, which extends cloud computing to the edge of a network, make possible low-latency and location-aware IoT applications. Moreover, technologies such as Low-Power Wide-Area Networks (LPWANs) have emerged as a promising solution to provide low-cost and low-power consumption connectivity to nodes spread throughout a wide area. Specifically, the Long-Range Wide-Area Network (LoRaWAN) standard is one of the most recent developments, receiving attention both from industry and academia. In this article, the use of a LoRaWAN fog computing-based architecture is proposed for providing connectivity to IoT nodes deployed in a campus of the University of A Coruña (UDC), Spain. To validate the proposed system, the smart campus has been recreated realistically through an in-house developed 3D Ray-Launching radio-planning simulator that is able to take into consideration even small details, such as traffic lights, vehicles, people, buildings, urban furniture, or vegetation. The developed tool can provide accurate radio propagation estimations within the smart campus scenario in terms of coverage, capacity, and energy efficiency of the network. The results obtained with the planning simulator can then be compared with empirical measurements to assess the operating conditions and the system accuracy. Specifically, this article presents experiments that show the accurate results obtained by the planning simulator in the largest scenario ever built for it (a campus that covers an area of 26,000 m2), which are corroborated with empirical measurements. Then, how the tool can be used to design the deployment of LoRaWAN infrastructure for three smart campus outdoor applications is explained: a mobility pattern detection system, a smart irrigation solution, and a smart traffic-monitoring deployment. Consequently, the presented results provide guidelines to smart campus designers and developers, and for easing LoRaWAN network deployment and research in other smart campuses and large environments such as smart cities.This work has been funded by the Xunta de Galicia (ED431C 2016-045, ED431G/01), the Agencia Estatal de Investigación of Spain (TEC2016-75067-C4-1-R) and ERDF funds of the EU (AEI/FEDER, UE)

Smart campuses : extensive review of the last decade of research and current challenges

Novel intelligent systems to assist energy transition and improve sustainability can be deployed at different scales, ranging from a house to an entire region. University campuses are an interesting intermediate size (big enough to matter and small enough to be tractable) for research, development, test and training on the integration of smartness at all levels, which has led to the emergence of the concept of “smart campus” over the last few years. This review article proposes an extensive analysis of the scientific literature on smart campuses from the last decade (2010-2020). The 182 selected publications are distributed into seven categories of smartness: smart building, smart environment, smart mobility, smart living, smart people, smart governance and smart data. The main open questions and challenges regarding smart campuses are presented at the end of the review and deal with sustainability and energy transition, acceptability and ethics, learning models, open data policies and interoperability. The present work was carried out within the framework of the Energy Network of the Regional Leaders Summit (RLS-Energy) as part of its multilateral research efforts on smart region

Interoperability in IoT

Interoperability refers to the ability of IoT systems and components to communicate and share information among them. This crucial feature is key to unlock all of the IoT paradigm´s potential, including immense technological, economic, and social benefits. Interoperability is currently a major challenge in IoT, mainly due to the lack of a reference standard and the vast heterogeneity of IoT systems. IoT interoperability has also a significant importance in big data analytics because it substantively eases data processing. This chapter analyzes the critical importance of IoT interoperability, its different types, challenges to face, diverse use cases, and prospective interoperability solutions. Given that it is a complex concept that involves multiple aspects and elements of IoT, for a deeper insight, interoperability is studied across different levels of IoT systems. Furthermore, interoperability is also re-examined from a global approach among platforms and systems.González-Usach, R.; Yacchirema-Vargas, DC.; Julián-Seguí, M.; Palau Salvador, CE. (2019). Interoperability in IoT. Handbook of Research on Big Data and the IoT. 149-173. http://hdl.handle.net/10251/150250S14917

Engineering and Technology Careers Fair 2016

Guide to the companies attending the FPSE Careers Fair with stand pla

Sensing and Measuring the Environment Workshop as Exposure to Engineering Technology for High School Students in a Summer Residential Camp

Summer programs are the latest trend in extracurricular STEM education programs offered by universities. Efforts are made towards residential summer programs, which have the ability to expose students not only to specially designed STEM activities but to the university campus environment and student life, as well. These types of programs are expected to have better success in getting students engaged and to capture their interest in STEM fields. This paper presents one example of designing and implementing a summer residential workshop in order to expose high school students to the field of engineering technology, specifically to electrical circuits, electrical prototyping, microprocessor based design, sensing and measuring the environment, and the Internet of Things. The camp includes other workshops that are focusing on other areas of STEM, specifically science and mathematics. The paper presents the workshop setting, the activities organized, and the feedback received from students

Remote health monitoring system for the elderly based on mobile computing and IoT

This document presents the work done in the Master’s thesis in Telecommunications and Computer Engineering and describes the development, implementation and subsequent of a Remote Health Monitoring System for the Elderly based on Mobile Computing and IoT. Due to increasing technological innovation over the last decades, the average life expectancy of humans is increasing year-by-year. Although this is an excellent step forward for humanity, it has led older population to being more prone to illness and accidents such as falls. In this work a study is made on the existing literature in nonintrusive remote health monitoring systems, towards the design and implementation of an IoT system capable of identifying falls and monitor cardiac data. A Systematic Literature Review (SLR) method was considered, taking into account the existing literature on remote health monitoring systems, fall detection algorithms and IoT. The Design Science Research (DSR) methodology was used to seek to enhance technology and science knowledge about this dissertation’s topic, through the creation of an innovative artifact. The system includes a smart watch (LILYGO T-WATCH-2020-V2), programmable in C under Arduino IDE to detect falls and a photoplethysmography monitoring unit (PPG) based on a Onyx 9560 Bluetooth oximeter, capable of measuring the user’s blood oxygen percentage (SpO2) and heart rate, in real time. It also provides remote monitoring through a user-friendly website to visualize live data about the health status of the user. The system was tested in volunteers to show the effectiveness of remote health monitoring systems for the elderly population.Este documento apresenta o trabalho realizado na tese de Mestrado em Engenharia de Telecomunicações e Informática e descreve o desenvolvimento, implementação e validação de um Sistema de Monitorização Remota da Saúde para Idosos. Devido à crescente inovação tecnológica ao longo dos anos, a esperança média de vida dos seres humanos está a aumentar anualmente. Embora seja um excelente passo em frente para a humanidade, tem levado à população mais idosa a ser propensa a doenças e acidentes, tais como quedas. Neste trabalho, efectua-se um estudo sobre a literatura existente em sistemas não intrusivos de monitorização remota da saúde, com vista à concepção e implementação de um sistema IoT capaz de identificar quedas e monitorizar dados cardíacos. Foi concebida uma Revisão Sistemática da Literatura (SLR), tendo em conta literatura existente sobre sistemas de monitorização da saúde, algoritmos de detecção de quedas e IoT. A metodologia Design Science Research (DSR) foi utilizada para procurar melhorar os conhecimentos tecnológicos sobre o tema desta dissertação, através da criação de um artefacto inovador. O sistema inclui um relógio inteligente (LILYGO T-WATCH-2020-V2), programável em C sob a IDE Arduino para detectar quedas e um dispositivo de monitorização fotopletismográfico (PPG) baseada num oxímetro Onyx 9560 Bluetooth, capaz de medir a percentagem de oxigénio no sangue (SpO2) e o ritmo cardíaco. Fornece ainda monitorização remota através de um website para visualizar dados em direto sobre a saúde do utilizador. O sistema foi testado em voluntários para mostrar a eficácia dos sistemas de monitorização remota da saúde em idosos

IoT Raspberry Pi Based Smart Parking System with Weighted K-Nearest Neighbours Approach

Due to the limited availability of parking slots in parking areas, drivers often have difficulty finding an empty parking slot. The number of parking slots available at a particular location is usually less than the number of vehicles. Hence, drivers spend a lot of time looking for vacant parking slots, which eventually delays the completion of their tasks, such as paying bills, attending a meeting, or visiting a patient at the hospital, etc. There are a couple of parking guidance systems that have been highlighted by the other researchers, but most of them lack real-time, convenient guidance. This research proposed a smart parking guidance system made of an IoT Raspberry Pi combined with an Android application that makes use of the weighted k nearest neighbours for positioning the vehicle. This was achieved through the use of Wi-Fi signal strength indicator fingerprinting, allowing for real-time navigation and parking detection. In order to achieve real-time parking over the internet, Raspberry Pi hardware and the ThingSpeak IoT cloud with ultrasonic sensors are used in the proposed method. An Android application was involved in this parking detection system, which adopted IoT approaches to estimate the location of users in real-time and provide routes using route-finding techniques to assist drivers in finding their desired parking slots. Data from the sensors was processed and translated into the Raspberry Pi using the Python programming language. They were sent using the Message Telemetry Transport protocol to send parking data to the ThingSpeak IoT cloud in real-time. This data was displayed via the Android app. The user is then able to view each available parking slot, acquire the route, and be directed with high accuracy to the parking slots of their choice. In this study, advanced sensing and communication technologies were used together with the weighted k nearest neighbours algorithm for positioning and wayfinding in order to improve parking guidance accuracy. Based on the experimental results, the proposed system showed a lower average error rate of 1.5 metres in comparison to other positioning techniques, such as GPS, or other similar algorithms for positioning, such as maximum a posteriori, which have shown average errors of 2.3 metres and 3.55 metres, respectively, a potential increase of more than 35% from the previous error rate. Doi: 10.28991/CEJ-2023-09-08-012 Full Text: PD

Internet of Things - Smart Surveillance System using PIR Sensor with Raspberry Pi

This paper describes our first research experience in Smart Surveillance System using PIR Sensor with Raspberry pi, by using open-source software tools such as Python, Raspbian OS and etc.Smart Surveillance System using PIR Sensor with Raspberry piemerged with the development of the Internet of Things. The basic concept of the application is to allow the client to uses wireless technology to provide essential security using Surveillance system. The proposed security system captures information and transmit it via a Wi-Fi to static IP, which is viewed using a web browser from any smart devices. Raspberry pi controls a video camera for surveillance. It streams live video and records the motion detected part in the cloud and/or in the window shared folder for future playback. The cameras automatically initiate recording when motion is sensed and Raspberry pi devices stores it in a secured folder