Machine Learning Interpretability and Its Impact on Smart Campus Projects

• URL: http://arxiv.org/abs/2006.04300v1
• Date: Mon, 8 Jun 2020 00:48:53 GMT
• Title: Machine Learning Interpretability and Its Impact on Smart Campus Projects
• Authors: Raghad Zenki and Mu Mu
• Abstract summary: The University of Northampton is building a smart system with multiple layers of IoT and software-defined networks (SDN) on its new Waterside Campus. The system can be used to optimize smart buildings energy efficiency, improve the health and safety of its tenants and visitors, assist crowd management and way-finding, and improve the Internet connectivity.
• Score: 1.90365714903665
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Machine learning (ML) has shown increasing abilities for predictive analytics over the last decades. It is becoming ubiquitous in different fields, such as healthcare, criminal justice, finance and smart city. For instance, the University of Northampton is building a smart system with multiple layers of IoT and software-defined networks (SDN) on its new Waterside Campus. The system can be used to optimize smart buildings energy efficiency, improve the health and safety of its tenants and visitors, assist crowd management and way-finding, and improve the Internet connectivity.

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