Machine Learning Interpretability and Its Impact on Smart Campus Projects

06/08/2020
by   Raghad Zenki, et al.
0

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.

READ FULL TEXT

page 2

page 3

research
11/27/2022

Machine Learning for Smart and Energy-Efficient Buildings

Energy consumption in buildings, both residential and commercial, accoun...
research
09/05/2021

A Survey on IoT Smart Healthcare: Emerging Technologies, Applications, Challenges, and Future Trends

The internet of things (IoT) refers to a framework of interrelated, web ...
research
02/25/2019

A Reference Architecture for Smart and Software-defined Buildings

The vision encompassing Smart and Software-defined Buildings (SSDB) is b...
research
11/06/2022

B-SMART: A Reference Architecture for Artificially Intelligent Autonomic Smart Buildings

The pervasive application of artificial intelligence and machine learnin...
research
10/11/2017

Exploring Cross-Domain Data Dependencies for Smart Homes to Improve Energy Efficiency

Over the past decade, the idea of smart homes has been conceived as a po...
research
04/09/2019

Enabling Smart Buildings by Indoor Visible Light Communications and Machine Learning

The smart building (SB), a promising solution to the fast-paced and cont...
research
01/22/2019

Beyond Control: Enabling Smart Thermostats For Leakage Detection

Smart thermostats, with multiple sensory abilities, are becoming pervasi...

Please sign up or login with your details

Forgot password? Click here to reset