Smart Home System: a comprehensive Review Arindom Chakraborty, monirul Islam, Fahim Shahriyar

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Smart Home System A Comprehensive Review

10.2. Energy Management Systems in SHS.
A vital part of the
SHS is energy management, and several studies have been
conducted in this feld. Smart home energy management
systems are designed based on a framework that can
satisfy energy demands and monitor available resources
without the involvement of the user [144]. Researchers
have used methods such as artifcial neural networks
[145], machine learning, deep learning [28], and artifcial
intelligence [73] to develop an energy management system
for SHSs. Smart homes that are fully capable of producing
the required amount of energy are one of the main focuses
of researchers, and several breakthroughs have been
achieved [124]. Te authors in [146, 147] proposed
a nonintrusive load monitoring (NILM) system for better
energy management. Automatic scheduling of household
appliances and electric vehicles to reduce energy costs has
been proposed in [148]. To decrease energy costs, a new
energy management system with the help of photovoltaic
cells that satisfes consumer needs without putting too
much pressure on the national grid has been proposed in
[149]. Photovoltaic cells have been a huge part of the
energy-saving scheme in the SHS. AI-based PV pro-
duction systems have been proposed in [150, 151]. A cloud
server-based energy management system has been pro-
posed in [125]. Multiagent energy optimization systems
have been presented in [152]. PV-based smart homes now
play an active role in the national grid. Extra energy
generated through photovoltaic cells in smart homes can
now be traded through an electric grid [153, 154].
10.3. Activity and Gesture Recognition.
Te process of
detecting and recognizing human body movements such as
handwaves or facial expressions to control and interact with
a computer system is defned as gesture control. It is
a subdivision of image processing and computer vision. In
SHSs, mostly hand gestures are used to control certain
appliances connected to the system. SHS researchers are
trying to develop a more accurate gesture recognition system
that would make home appliance control easier. A computer
vision-based hand gesture recognition system for home
appliance control that does not require the user to wear any
extra wristband or other device is demonstrated in [126]. A
Kinect v2 sensor was used to capture body gestures in [107],
which are used to recognize a set of hand state combinations
to control home appliances. Kinect is a motion-sensing
device that is capable of gesture and voice recognition
[155]. Kinect v2 is again used in [127] for both speech and
gesture recognition systems that are specially tailored for
elderly people of age 65–80 years. In [128], the authors used
Kinect again to register body posture and control home
appliances. Another image processing-based hand gesture
recognition system is proposed by the authors of [30] that
uses MATLAB simulations. A very interesting experiment
was carried out by the author in [138], where a radar device is
used to detect objects and identify gestures. A body sensor-
based gesture recognition system has been explored in [32],
where fex sensors are used with a hand glove to register
gestures and control appliances. A secure blockchain-based
smart home health monitoring system has been proposed in
[63], which uses a sensor device for gesture recognition. A
wearable wrist-mountedmotion-sensing device is used for
gesture recognition in [108]. Te device consists of an in-
ertial sensor to detect the hand motion, an Arduino
microcontroller board for processing the data, and an RF
wireless transceiver to communicate and send the data to the
main processor.
10.4. Elderly and Physically Challenged People Care.
With the
advancement in smart home technology, it is becoming
more and more capable of providing health care and health
monitoring facilities for occupants, especially for the elderly
and physically challenged people [156, 157]. Researchers are
constantly working to provide a more comfortable and safer
environment for elderly people, which gives them more
safety and independence [18, 158]. Te SHS could provide
great physical and health support for elderly people [159].
Several studies have been carried out to investigate the
current situation of elderly care in smart homes and the
perception of elderly people towards the smart home system
[124, 147]. A low-cost smart assistance system for elderly
people has been explored in [131], which generates re-
minders to take medicines and alerts certain people about
signifcant events such as fre eruptions or intrusions. Apart
from that, it also provides a wireless appliance control
option. Te authors in [98] developed a voice and text-based
home appliance control system that uses voice commands or
text messages to turn on and of various appliances. Tis
method is very useful for elderly and physically challenged
people as it enables them to remotely control their appli-
ances. A hidden Makarov model (HMM) is used in [76] to
detect abnormal activity among smart home occupants,
especially elderly people. Te study used only sensor data to
detect abnormalities in their behavior. A patient monitoring
system is discussed in [132], where audio and video data are
collected through a microphone and camera. Te collected
data are then processed in the cloud, and depending on the
result, doctors can prescribe or assist the patient through
audio, video, or text messages. Te researchers in [133, 139]
designed a two-way telemedicine interaction system that
allows simultaneous communication between the elderly
and a physician. An IoT-based elderly care system has been
proposed in [79] that uses AI for voice recognition and ofers
wireless appliance switching as well as home monitoring and
intrusion alert.
22
Journal of Electrical and Computer Engineering

10.5. Smart Home Appliance Control.
Home automation
and wireless appliance control are two of the main felds of
research in SHSs. SHSs are gradually adapting home au-
tomation and allow the user better control over their home
[17]. Several types of methods are available for appliance
switching, such as wireless control over a smartphone app
[134] or website [95], voice command [86], and text com-
mand [98]. In general, smartphone apps [70] or websites
[24] are the most popular means of appliance control in
SHSs because of their simplicity and less complicated in-
stallation process. Other methods, such as gesture recog-
nition, where the user can control devices just with some
simple gestures, have also been developed [107, 126]. Re-
cently, the SHS with dual modes of appliance control such as
speech and gesture control is becoming a more popular topic
of research [127]. IoT-based SHS systems, where the user can
monitor the home environment as well as control various
home appliances such as lights, fans, and other switches, are
already in development [137]. For better speech recognition
in appliance control, researchers are working to develop
a better speech recognition algorithm [160–163].

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