Modelling and Optimisation of Resource Usage in an IoT Enabled Smart Campus

TL;DR

This paper explores how IoT, data analytics, and AI can optimize resource usage in university campuses, aiming to improve efficiency and user experience through modeling and experimentation at UNSW Sydney.

Contribution

It introduces a framework for IoT-enabled resource management in campuses, combining theory and practical experimentation to enhance decision-making.

Findings

Improved resource utilization through IoT data collection

AI-based prediction models for usage patterns

Potential cost savings and efficiency gains

Abstract

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 utilised 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 organisations to lower cost and improve user experience. This thesis explores this opportunity via theory and experimentation using UNSW Sydney as a living laboratory.