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

Internet of Things Affordance for Open Educational Resources in a Comprehensive Open Distance E-learning

The Internet of Things (IoT) space has dual dimensions of affordance to support open educational resources (OER). The duality of affordance has little or not been well articulated in relation to OER, particularly in a Comprehensive open distance e-learning (CODEL) institution. Such an institution is a mega open distance in South Africa and beyond the continent to accommodate students globally and rely on information and communication technology (ICT) in the provision of tuition. In the CODEL institution, there is a recognizable shift as the institution encourages the appropriation of OER and phasing out the prescription of the prescribed textbooks. The research opted for the qualitative approach to establish the role and the causality of IoT affordance in the appropriation of OER. The technology affordance theory has been used as the main theoretical underpinning for this study. The study found that the CODEL institution is IoT driven when handling OER. Furthermore, IoT affordance for OER suggests two propositions as a contribution: CODEL requires to articulate and realignment of its business enterprise system with IoT-driven infrastructure to accommodate tuition using OER; and the IoT-driven context needs to seek possible solutions to adopt artificial intelligence practices for the advancement of OER. In a recommendation for future research, there is a need to investigate the appropriation of OER through IoT affordance in all South African higher education institutions including the contact or traditional universities

Modelling and optimisation of resource usage in an IoT enabled smart campus

University campuses are essentially a microcosm of a city. They comprise diverse facilities such as residences, sport centres, lecture theatres, parking spaces, and public transport stops. Universities are under constant pressure to improve efficiencies while offering a better experience to various stakeholders including students, staff, and visitors. Nonetheless, anecdotal evidence indicates that campus assets are not being utilized efficiently, often due to the lack of data collection and analysis, thereby limiting the ability to make informed decisions on the allocation and management of resources. Advances in the Internet of Things (IoT) technologies that can sense and communicate data from the physical world, coupled with data analytics and Artificial intelligence (AI) that can predict usage patterns, have opened up new opportunities for organizations to lower cost and improve user experience. This thesis explores this opportunity via theory and experimentation using UNSW Sydney as a living laboratory. The building blocks of this thesis consist of three pillars of execution, namely, IoT deployment, predictive modelling, and optimization. Together, these components create an end-to-end framework that provides informed decisions to estate manager in regards to the optimal allocation of campus resources. The main contributions of this thesis are three application domains, which lies on top of the execution pillars, defining campus resources as classrooms, car parks, and transit buses. Specifically, our contributions are: i) We evaluate several IoT occupancy sensing technologies and instrument 9 lecture halls of varying capacities with the most appropriate sensing solution. The collected data provides us with insights into attendance patterns, such as cancelled lectures and class tests, of over 250 courses. We then develop predictive models using machine learning algorithms and quantile regression technique to predict future attendance patterns. Finally, we propose an intelligent optimisation model that allows allocations of classes to rooms based on the dynamics of predicted attendance as opposed to static enrolment number. We show that the data-driven assignment of classroom resources can achieve a potential saving in room cost of over 10\% over the course of a semester, while incurring a very low risk of disrupting student experience due to classroom overflow; ii) We instrument a car park with IoT sensors for real-time monitoring of parking demand and comprehensively analyse the usage data spanning over 15 months. We then develop machine learning models to forecast future parking demand at multiple forecast horizons ranging from 1 day to 10 weeks, our models achieve a mean absolute error (MAE) of 4.58 cars per hour. Finally, we propose a novel optimal allocation framework that allows campus manager to re-dimension the car park to accommodate new paradigms of car use while minimizing the risk of rejecting users and maintaining a certain level of revenue from the parking infrastructure; iii) We develop sensing technology for measuring an outdoor orderly queue using ultrasonic sensor and LoRaWAN, and deploy the solution at an on campus bus stop. Our solution yields a reasonable accuracy with MAE of 10.7 people for detecting a queue length of up to 100 people. We then develop an optimisation model to reschedule bus dispatch times based on the actual dynamics of passenger demand. The result suggests that a potential wait time reduction of 42.93% can be achieved with demand-driven bus scheduling. Taken together, our contributions demonstrates that there are significant resource efficiency gains to be realised in a smart-campus that employs IoT sensing coupled with predictive modelling and dynamic optimisation algorithms

Exploring Campus through Web-Based Immersive Adventures Using Virtual Reality Photography: A Low-Cost Virtual Tour Experience

This study aims to assess the incorporation of virtual reality (VR) photography into the web-based immersive application “virtual interactive campus tour (VICT).” This application offers users an immersive experience, allowing them to virtually explore university campuses and access information about the facilities and services available. The VICT application offers a cost-effective, attractive, and sustainable alternative for universities to display their resources and interact with potential students. Through black box testing, we conducted user acceptance testing (UAT) and functionality testing, confirming the application’s readiness for deployment and its capability to meet institutional and end-user requirements. This study also examined the potential for universities to use VR to meet the expectations of prospective students. The application is compatible with both desktop and mobile devices. The results indicated that the overall average validity score was 0.88, suggesting that the measure is valid. The validation results were thoroughly tested and reliable. This study emphasizes the potential of immersive web-based tours in higher education and aims to bridge the divide between virtual exploration and physical visits. By offering an immersive virtual campus experience, this innovative tool has the potential to revolutionize university marketing strategies, increase student engagement, and transform campus visit approaches

NMC Horizon Report: 2017 Higher Education Edition

The NMC Horizon Report > 2017 Higher Education Edition is a collaborative effort between the NMC and the EDUCAUSE Learning Initiative (ELI). This 14th edition describes annual findings from the NMC Horizon Project, an ongoing research project designed to identify and describe emerging technologies likely to have an impact on learning, teaching, and creative inquiry in education. Six key trends, six significant challenges, and six important developments in educational technology are placed directly in the context of their likely impact on the core missions of universities and colleges. The three key sections of this report constitute a reference and straightforward technology-planning guide for educators, higher education leaders, administrators, policymakers, and technologists. It is our hope that this research will help to inform the choices that institutions are making about technology to improve, support, or extend teaching, learning, and creative inquiry in higher education across the globe. All of the topics were selected by an expert panel that represented a range of backgrounds and perspectives

Modelling and optimisation of resource usage in an IoT enabled smart campus

University campuses are essentially a microcosm of a city. They comprise diverse facilities such as residences, sport centres, lecture theatres, parking spaces, and public transport stops. Universities are under constant pressure to improve efficiencies while offering a better experience to various stakeholders including students, staff, and visitors. Nonetheless, anecdotal evidence indicates that campus assets are not being utilized efficiently, often due to the lack of data collection and analysis, thereby limiting the ability to make informed decisions on the allocation and management of resources. Advances in the Internet of Things (IoT) technologies that can sense and communicate data from the physical world, coupled with data analytics and Artificial intelligence (AI) that can predict usage patterns, have opened up new opportunities for organizations to lower cost and improve user experience. This thesis explores this opportunity via theory and experimentation using UNSW Sydney as a living laboratory. The building blocks of this thesis consist of three pillars of execution, namely, IoT deployment, predictive modelling, and optimization. Together, these components create an end-to-end framework that provides informed decisions to estate manager in regards to the optimal allocation of campus resources. The main contributions of this thesis are three application domains, which lies on top of the execution pillars, defining campus resources as classrooms, car parks, and transit buses. Specifically, our contributions are: i) We evaluate several IoT occupancy sensing technologies and instrument 9 lecture halls of varying capacities with the most appropriate sensing solution. The collected data provides us with insights into attendance patterns, such as cancelled lectures and class tests, of over 250 courses. We then develop predictive models using machine learning algorithms and quantile regression technique to predict future attendance patterns. Finally, we propose an intelligent optimisation model that allows allocations of classes to rooms based on the dynamics of predicted attendance as opposed to static enrolment number. We show that the data-driven assignment of classroom resources can achieve a potential saving in room cost of over 10\% over the course of a semester, while incurring a very low risk of disrupting student experience due to classroom overflow; ii) We instrument a car park with IoT sensors for real-time monitoring of parking demand and comprehensively analyse the usage data spanning over 15 months. We then develop machine learning models to forecast future parking demand at multiple forecast horizons ranging from 1 day to 10 weeks, our models achieve a mean absolute error (MAE) of 4.58 cars per hour. Finally, we propose a novel optimal allocation framework that allows campus manager to re-dimension the car park to accommodate new paradigms of car use while minimizing the risk of rejecting users and maintaining a certain level of revenue from the parking infrastructure; iii) We develop sensing technology for measuring an outdoor orderly queue using ultrasonic sensor and LoRaWAN, and deploy the solution at an on campus bus stop. Our solution yields a reasonable accuracy with MAE of 10.7 people for detecting a queue length of up to 100 people. We then develop an optimisation model to reschedule bus dispatch times based on the actual dynamics of passenger demand. The result suggests that a potential wait time reduction of 42.93% can be achieved with demand-driven bus scheduling. Taken together, our contributions demonstrates that there are significant resource efficiency gains to be realised in a smart-campus that employs IoT sensing coupled with predictive modelling and dynamic optimisation algorithms

Redefining Community in the Age of the Internet: Will the Internet of Things (IoT) generate sustainable and equitable community development?

There is a problem so immense in our built world that it is often not fully realized. This problem is the disconnection between humanity and the physical world. In an era of limitless data and information at our fingertips, buildings, public spaces, and landscapes are divided from us due to their physical nature. Compared with the intense flow of information from our online world driven by the beating engine of the internet, our physical world is silent. This lack of connection not only has consequences for sustainability but also for how we perceive and communicate with our built environment in the modern age. A possible solution to bridge the gap between our physical and online worlds is a technology known as the Internet of Things (IoT). What is IoT? How does it work? Will IoT change the concept of the built environment for a participant within it, and in doing so enhance the dynamic link between humans and place? And what are the implications of IoT for privacy, security, and data for the public good? Lastly, we will identify the most pressing issues existing in the built environment by conducting and analyzing case studies from Pomona College and California State University, Northridge. By analyzing IoT in the context of case studies we can assess its viability and value as a tool for sustainability and equality in communities across the world

When Internet of Things meets Metaverse: Convergence of Physical and Cyber Worlds

In recent years, the Internet of Things (IoT) is studied in the context of the Metaverse to provide users immersive cyber-virtual experiences in mixed reality environments. This survey introduces six typical IoT applications in the Metaverse, including collaborative healthcare, education, smart city, entertainment, real estate, and socialization. In the IoT-inspired Metaverse, we also comprehensively survey four pillar technologies that enable augmented reality (AR) and virtual reality (VR), namely, responsible artificial intelligence (AI), high-speed data communications, cost-effective mobile edge computing (MEC), and digital twins. According to the physical-world demands, we outline the current industrial efforts and seven key requirements for building the IoT-inspired Metaverse: immersion, variety, economy, civility, interactivity, authenticity, and independence. In addition, this survey describes the open issues in the IoT-inspired Metaverse, which need to be addressed to eventually achieve the convergence of physical and cyber worlds.info:eu-repo/semantics/publishedVersio

Scalable pathways to net zero carbon in the UK higher education sector: A systematic review of smart energy systems in university campuses

The following literature review sets out the state-of-the-art research relating to smart building principles and smart energy systems in UK higher education university campuses. The paper begins by discussing the carbon impact of the sector and the concept of ‘smart campuses' applied to the sector in the context of decarbonisation. Opportunities and challenges associated with integrating smart energy systems at the university campus from a policy and technical perspective are then discussed. This is followed by a review of building and campus-scale frameworks supporting a transition to smart energy campuses using the BPIE’ Smart Buildings' framework. The paper finds that the complexity of achieving net-zero carbon emissions for new and existing higher education buildings and energy systems can be addressed with the adoption of ‘smart building principles' and integrating 'smartness' into their energy systems. Several universities in the UK and worldwide are integrating smart services and Information and Communication Technologies (ICT) in their operations following the smart campus premise. At the building level, existing frameworks often create conceptual roadmaps for the smart building premise or propose technical implementation and assessment methods. At university campus scale, implementation typically comes through single-vector interventions, and only few examples exist that propose a multi-vector approach. Comparisons of the drivers and the decision-making process are made, with carbon and cost reduction being the most prominent from leveraging distributed energy generation. Therefore, this study identified the need for a comprehensive technical or policy framework to drive the uptake of the smart energy campus, aiming to bring together the holistic value of smart energy campuses