Energy consumption in the residential sector is 25% of all the sectors. The advent of smart
appliances and intelligent sensors have increased the realization of home energy …

The goal of this work is to give a full review of how machine learning (ML) is used in thermal
comfort studies, highlight the most recent techniques and findings, and lay out a plan for …

A huge body of research is concentrated on develo** advance load control strategies for
reducing energy consumption and ensuring smooth operation of power system. Air …

ADVANCES IN FUZZY-BASED INTERNET OF MEDICAL THINGS (IOMT) This book
explores the latest trends, transitions, and advancements of the Internet of Medical Things …

Twenty‐four percent of all sectors' energy use is in the residential sector. Intelligent sensors
and smart appliances have sped up the development of energy management systems for …

In this paper, two energy management controllers: Binary Particle Swarm Optimization Fuzzy
Mamdani (BPSOFMAM) and BPSOF Sugeno (BPSOFSUG) are proposed and implemented …

Big data frameworks enable companies from various fields to build models that allow them
to increase profit margins by improving decision making at different levels (middle …

The effect of economic and population growth rapidly contributes to the energy usage of
buildings increasing to high levels. To minimize the electrical energy consumption (EC) …

Opportunities in healthcare have expanded to recent advancements in the Internet of Things
(IoT) technology, artificial intelligence, and machine learning. Furthermore, these technical …

One of the main and most practical applications of IOT technology is smart homes. Providing
thermal comfort and temperature control play an important role in these homes. Therefore …