ENERGY EFFICIENT IOT BASED SMART HOME

CHAPTER 1
INTRODUCTION
The concept of “automated home/smart home” was first introduced over 80 years ago and
has been facing different technical limitations since then. Recently, service providers and
home appliance manufacturers have launched a new initiative to bring the concept of smart
homes to reality. This Smart Home initiative allows subscribers to remotely manage and
monitor different home devices from anywhere via smart phones or over the web with no
physical distance limitations. With the ongoing development of mass-deployed broadband
internet connectivity and wireless technology, the concept of a Smart Home has become a
reality where all devices are integrated and interconnected via through the wireless network.
These “smart” devices have the potential to share information with each other given the
permanent availability to access the broadband internet connection. Hence, the Smart Home
Technology has become part of Internet of Things (IOT), the wireless sharing of information.

A smart home is one that incorporates advanced sensing and automation systems to
provide the inhabitants with monitoring and control regardless of whether they are inside or
outside the home. For example, a smart home may have controls for lighting, temperature,
multi-media, security, window and door operations, as well as many other functions.

A smart home, then, may be defined as a residence or a building with equipment which
can be remotely controlled and operated from any location in the world by means of Smart
Devices or through a smartphone. Smart Homes comprise of Devices that provide comfort,
security, convenience, energy efficiency and enhance intelligent living. The Devices
communicate and interact with each other and form a connected ecosystem. Smart Home is
usually understood as automated home, but the actual capabilities are beyond automation.
Smart Home ecosystem comprises of a set of connected gadgets with Intelligence that help
them in executing the task and take necessary decisions.

A smart home is an aggregation of all the needs of its occupants while they are inside and
when they are not. Remote control, Security, surveillance, remote monitoring of premises
including monitoring those who are sick, young, elderly, etc are all requirements of users. In
order to meet these requirements, an integration at the Application level and scalability at the
cloud level are needed.

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A new challenge is now present in the design process of a Smart Home. In today’s world, the
Smart Home is not enough to the environmentally-conscious user, but energy efficiency is a
key. The IOT provides a strong tool that not only connects wireless communication devices
but wireless sensors for heating/cooling or any needed utility within the house to better
manage energy usage as well as enhance the living experience in modern homes.

In this work, a house model is analysed to demonstrate the comprehensive simulation studies
on consumed energy reduction for lighting as well as home cooling and heating. Various
Multiphysics simulations were carried out on the kitchen room using ANSYS products.
Integration of the different smart technologies is also studied including smartwatch
communication with home control unit as an example of customizing the Smart Home for the
user-based experience. Camera/motion sensor were used as part of the home security system
and were coupled with the home light and HVAC control system, to remotely switch on/off
the lights and turn on/off the heating/cooling system when a person enters or leaves the room.

Finally, the coupling/RF interference (RFI) between the antennas integrated within the
house’s smart devices within their RF circuit. Signal integrity is examined to ensure IOT-
enabled devices can communicate seamlessly to execute an energy saving protocol. This
protocol turns on the LED light bulb and an actuator to open the HVAC duct damper when an
occupant enters the kitchen area and gets sensed by the security/motion sensor/camera.

Home buildings in Indian scenario are difficult to be classified into a few categories, largely
due to the economic disparity and the place of living. On one hand there is a large population
that has barely access to essential requirements of water, electricity and food; and on the
other hand, India has a small percentage of population with income levels like those of
developed countries. The expectations of comfort, automation, security and services by this
population are same as those of the developed countries.

The simulation strategies addressed in this work can be utilized to create a virtual smart
model of an IOT-enabled smart home and the fundamental elements. Such computational
methodologies can be extended to other home parts and buildings such as warehouses,
commercial buildings, stadiums, and shopping malls.

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The Internet of things can be defined as connecting the various types of objects like smart
phones, personal computer and Tablets to internet, which brings in very new-fangled type of
communication between things and people and between things. With the introduction of
IOTs, the research and development of home automation are becoming popular in the recent
days. Many of the devices are controlled and monitored for helps the human being.
Additionally, various wireless technologies help in connecting from remote places to improve
the intelligence of home environment. An advanced network of IOT is being formed when a
human being needs connecting with other things. IOTs technology is used to come in with
innovative idea and great growth for smart homes to improve the living standards of life.
Internet helps us to bring in with immediate solution for many problems and able to connect
from any of the remote places which contributes to overall cost reduction and energy
consumption.

In recent years, there has been a growing interest among consumers in the smart home
concept. Home automation system represents and reports the status of the connected devices
in an intuitive, user-friendly interface allowing the user to interact and control various devices
with the touch of a few buttons. Some of the major communication technologies used by
today’s home automation system include Bluetooth, Wi-MAX and Wireless LAN (Wi-Fi),
ZigBee, and Global System for Mobile Communication (GSM). Here we are using Wi-Fi
module. It offers the user complete access control of the appliances through a remote
interface. Automation is the use of control systems and information technology to control
equipment, industrial machinery and processes, reducing the need for the human intervention.

The wide variety of potential IOT applications needs a software development

environment that ties together the applications, the command, control and routing processing
and the security of the node and system. While the importance of software in MCU solutions
has increased during the past few years, for MCUs supporting the IoT, even more software,
tools and enablement will be needed. A broad ecosystem with easily accessible support is key
to enabling the development of embedded processing nodes and IoT applications.

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1.1 OBJECTIVES

1) Data is centralized.
2) Multiple protocol support and uniformity in data format.
3) Ease of setup.
4) Reduces the cost for customers.
5) Reduces the number of gateways to be used.
6) Data lost is reduced and no need to manage locally.
7) Private or public cloud can be set up.
8) Reduces overhead of maintenance.

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CHAPTER 2
LITERATURE REVIEW
2.1 Home Automation Using Internet of Things:
K. N. Vinay Sagar, S. M. Kusuma, “Home Automation Using Internet of Things,”
IRJET, e-ISSN:2395-0056, Vol. 02, Issue 03, pp. 0966-1970, June 2015.
A new challenge is now present in the design process of a Smart Home. In today’s world,
the Smart Home is not enough to the environmentally-conscious user, but energy
efficiency is a key. The IOT provides a strong tool that not only connects wireless
communication devices but wireless sensors for heating/cooling or any needed utility
within the house to better manage energy usage as well as enhance the living experience
in modern homes.

2.2 Smart Home Design using Wireless Sensor Network and Biometric

Technologies:

B. M. El-Basioni, S. M. Abd El-kader, and M. A. Fakhreldin, “Smart Home Design using

Wireless Sensor Network and Biometric Technologies,” IJAIEM, ISSN 2319-4847, Vol.
2, Issue 3, March 2013.
A house model is analysed to demonstrate the comprehensive simulation studies on
consumed energy reduction for lighting as well as home cooling and heating. Various
Multiphysics simulations were carried out on the kitchen room using ANSYS products.
Integration of the different smart technologies is also studied including smartwatch
communication with home control unit as an example of customizing the Smart Home for
the user-based experience. Camera/motion sensor were used as part of the home security
system and were coupled with the home light and HVAC control system, to remotely
switch on/off the lights and turn on/off the heating/cooling system when a person enters
or leaves the room.

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2.3Remotely controlled home automation system:

Singh, Navab, et al. "Remotely controlled home automation system. “Advances in

Engineering andTechnology Research (ICAETR), 2014 International Conference on.
IEEE, 2014.

Here we are using Wi-Fi module. It offers the user complete access control of the
appliances through a remote interface. Automation is the use of control systems and
information technology to control equipment, industrial machinery and processes,
reducing the need for the human intervention.

2.4Smart GSM Based Home Automation System:

Teymourzadeh, Rozita, et al. "Smart GSM Based Home Automation System."

Systems, Process & Control (ICSPC),2013 IEEE Conference on. IEEE, 2013.

Home automation system represents and reports the status of the connected devices in
an intuitive, user-friendly interface allowing the user to interact and control various
devices with the touch of a few buttons. Some of the major communication
technologies used by today’s home automation system include Bluetooth, WiMAX
and Wireless LAN (Wi-Fi), ZigBee, and Global System for Mobile Communication
(GSM). All GSM is one of the most widely used cellular technologies in the world.
With the increase in the number of GSM subscribers, research and development is
heavily supported in further investigating the GSM implementation.

2.5 Research directions for the internet of things:

Stankovic, John. "Research directions for the internet of things." Internet of Things
Journal, IEEE1.1 (2014).

A sensing and actuation utility will not only exist in public spaces, but also extend
into the home, apartments, and condominiums. Here people will be able to run health,
energy, security, and entertainment apps on the infrastructure. Installing and running
new apps will be as easy as plugging in a new toaster into the electric utility. One app
may help monitor and control heart rate, another performs financial and investments
services, another automatically ordering food and wine, or even predicting a
impending medical problem that should be addressed early to mitigate or even avoid
the problem. Humans will often be integral parts of the IOT system. The Industrial

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Internet is also a form of IOT where the devices (things) are objects in manufacturing
plants, dispatch centres, process control industries, etc.

2.6 What the Internet of Things (IoT) needs to become a reality:

Karimi, Kaivan, and Gary Atkinson. "What the Internet of Things (IoT) needs to
become a reality." White Paper,Freescale and ARM (2013).

A radical evolution of the current Internet into a Network of interconnected objects

that not only harvests information from the environment (sensing) and interacts with
the physical world (actuation/ command/control), but also uses existing Internet
standards to provide services for information transfer, analytics, applications, and
communications. Fuelled by the prevalence of devices enabled by open wireless
technology such as Bluetooth, radio frequency identification (RFID), Wi-Fi, and
telephonic data services as well as embedded sensor and actuator nodes, IOT has
stepped out of its infancy and is on the verge of transforming the current static
Internet into a fully integrated Future Internet. The Internet revolution led to the
interconnection between people at an unprecedented scale and pace. The next
revolution will be the interconnection between objects to create a smart environment.
John A. Stankovic vision saying, many technical communities are vigorously pursuing
research topics that contribute to the IOT. Today, as sensing, communication, and
control become ever more sophisticated and ubiquitous, there is significant overlap in
these communities; sometimes from slightly different perspectives.

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CHAPTER 3
METHODOLOGY
3.1 IN-HOUSE SMART WIRELESS COMMUNICATION

FIG.3.11 Simulated Smart Home Model

The IOT relies on wireless communication enabled by antennas. Depending on

antenna placement, communication can degrade due to obstructions in the antenna path and
multipath signal propagation and fading. Figure.3.11 shows the complete model of the
simulated smart home as well as the kitchen room where the different smart devices are
populated. Therefore, it is vital for the integrity of the system to study the fields generated by
the different antennas employed by the smart devices: triple band energy control unit (900
MHz, 2.45 GHz, 5.8 GHz), security/motion sensor and surveillance camera (5.8 GHz), LED
light bulbs (2.45 GHz), and actuator of the HVAC duct dampers (900 MHz).

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FIG.3.12 Antenna design with simulated reflection coefficient and far field
(a) Generic motion sensor antenna, (b) Generic light bulb antenna

Figure 3.12 shows the different antenna models along with their antenna reflection
coefficients and far field gain patterns.

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FIG.3.13 (a)Triple band energy control unit antenna model based on far field antenna
gain (b) 900MHz, (c) 2.45GHz (d) 5.8GHz

The suggested modelling scenario starts when an occupant approaches the kitchen. A motion
sensor detects this and wirelessly relays this information to the home energy control unit,
which turns on LED light bulbs in the kitchen. Temperature sensors that are co-installed in
the motion sensor communicate ambient temperature readings to the home energy control
unit that remotely turns on or off the HVAC system to regulate the temperature in the kitchen.

Having modelled the antenna performance, ANSYS EMIT can be used to simulate the
performance of the Smart Home’s sensors. ANSYS EMIT provides built-in library and

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behavioural models for the sensors used in the house. In this case, the sensors operate in
unlicensed spectrum at the 900 MHz, 2.45 GHz and 5.8 GHz bands using available protocols
such as Zigbee. The antenna performance results can then be used with the available RF
models to first compute the RF link margin between the sensors and the home control unit
(HCU) in the home without any other RF sources.

TABLE I. SUMMARY OF RF LINK MARGIN BETWEEN THE

SENSORS ANDTHE HOME CONTROL UNIT (HCU)

The results are summarized in the Table I. Our target for the wireless system was to obtain
a 10dB link margin in this interference-free environment to allow for a comfortable margin.
The results show an acceptable 14.6dB link margin for the link between the actuator and
HCU. For the motion sensor, the link margin is excessive at 40dB. While this would ensure
more than adequate performance for this link, the link is over-designed, and changes should
be considered to reduce the potential for harmful interference to other links and to reduce
power consumption. Finally, the Lightbulb-to-HCU link is only 2.2 dB which, while non-
negative, falls short of our 10dB goal. This is somewhat troublesome, particularly in the
congested 2.45 GHz band as this link will be particularly susceptible to interference from
other sources of RF energy in the home or due to fluctuations in the propagation channel.

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FIG.3.14 (a) RFI block diagram with wireless speaker system (b) ANSYS EMIT
scenario matrix that represents the interactions between systems and colours them
according to performance

ANSYS EMI is also used to evaluate the interference from other RF sources within the
home. As an example, we can evaluate the impact of a typical wireless speaker system. In this
case, we place a wireless speaker that uses a Texas Instruments Pure PathWireless Audio
chipset in the home as shown in Fig.3.14(a) The obtained results indicate that the speaker
system will cause severe interference to the Light-Bulb/HCU link (red square) in Fig.3.14(b)
but will not cause problems with the other links (green) squares. The 21.2 dB EMI Margin is
severe and requires further evaluation of theRF environment in the home.

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3.2 BLOCK DIAGRAM

FIG.3.21

The System architecture of Smart Home Security System is shown in the figure 3.21.
Raspberry Pi, PiCamera and Power supply forms the entire security system to be installed at
the required place. PIR motion sensor is connected to GPIO pins of Raspberry Pi. We can use
LCD monitor for setting up Raspberry web server. Loudspeaker mounted at Audio Jack of
Raspberry Pi. Relay Driver circuit with IC ULN2003 is interfaced to Raspberry Pi to control
Electromagnetic Door Lock. The image captured can save with time and date on SD card or
USB Pen drive connected on Raspberry Pi.

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3.3 SYSTEM DESCRIPTION

FIG.3.31 Raspberry Pi3

Raspberry Pi board is a miniature marvel, packing considerable computing power into a

footprint no larger than a credit card. The processor at the heart of the Raspberry Pi system is
a Broadcom BCM2835 system-on-chip (SoC) multimedia processor. This means that the vast
majority of the system’s components, including its central and graphics processing units
along with the audio and communications hardware, are built onto that single component
hidden beneath the 512 MB memory chip at the centre of the board.

It’s not just this SoC design that makes the BCM2835 different to the processor found in your
desktop or laptop, however. It also uses a different instruction set architecture (ISA), known
as ARM. The Raspberry Pi, by contrast, is designed to run an operating system called
GNU/Linux Raspbian. Hereafter referred to simply as Linux.

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Windows or OS X, Linux is open source: it’s possible to download the source code for the
entire operating system and make whatever changes you desire.

Features of the Raspberry Pi:

 Model B+ Raspberry Pi with Mounting Points and
 512MB RAM.
 Broadcom BCM2835 ARM11 700 MHz

 Integrated Video core 4 Graphics GPU capable of playing

 Full 1080p HD Video.
 4 x USB Ports (Max Output 1.2A).
 Board Power Draw: 600mA.
 HDMI Video Output.
 10/100Mb Ethernet Port for Internet Access.
 Micro SD Flash Memory Card Slot.
 40-pin 2.54mm Header Expansion Slot (Which allow for peripherals and
expansion boards)
 Dimensions 85 x 56 x 17mm.
 The Raspberry Pi is boot by external memory card with Raspbian Jessie images

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FIG.3.32 Raspberry Pi Camera module

The Raspberry Pi Camera Module is a custom designed add-on for Raspberry Pi. It attaches
to Raspberry Pi by way of one of the two small sockets on the board upper surface.
Thisinterface uses the dedicated CSI interface, which was designed especially for interfacing
to cameras. The CSI bus is capable of extremely high data rates, and it exclusively carries
pixel data.

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FIG.3.33 PIR Motion Sensor

The PIR (Passive Infra-Red) Sensor is a Pyroelectric device that detects human body
motion by measuring changes in the infrared levels emitted by surrounding objects. This
motion can be detected by checking for a high signal on a single I/O pin. Incorporating a
Fresnel lens and motion detection circuit. High sensitivity and low noise. Output is a standard
5V active low output signal. Module provides an optimized circuit that will detect motion up
to 6 meters away Inexpensive and easy to use, The Output can be connected toGPIO pins of
Raspberry Pi directly to monitor signal.

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FIG.3.34 Light Intensity Sensor

BH1750FVI is a Digital Light sensor which is most suitable for obtaining the ambient
light towards adjusting LCD and Keypad backlight power of Mobile phone. Unit of light
quantity is called lumen where light flows from a source in one second. In here, reading is
taken as Lux which is equalto one lumen per square meter.

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FIG.3.35ESP8266 Wi-Fi module

ESP8266 is a Wi-Fi networking module or solution allowing Wifi networking function from
one host to another. The ESP8266 requires 3.3 v to 5V. ESP8266 need to communicate via
serial 3.3 V and does not have 5V tolerant inputs, so you need level conversion to
communicate with a 5V microcontroller like most Arduino use.

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FIG.3.36 Hall Sensor

The Allegro™ ACS712 is a Hall sensor providing economical and precise solution in
industries, commercial and communication systems. The hall sensor is used to measure
current flowing in the wire. The hall sensor can measure the current by placing a fixed
resistance for the wire. A part of the wire that is going to the appliance from the transistor is
cut and made to go through the hall sensor. The hall sensor has 3 pins- voltage pin, the
ground pin and the output pin. The voltage pin is connected to the 5-volt supply from
Arduino and the ground pin is connected to the ground and the output pin is connected to the
analog pin in the Arduino. The output pin from the hall sensor measuring current in fan is
connected to the analog pin A2 and that measuring the current into light is connected to
Arduino pin A1.

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FIG.3.37 Humidity and Temperature Sensor

DHT11 Sensor is a temperature and humidity sensor which has been calibrated with digital
signal output. This Sensor ensures high reliability and excellent long-term stability.
Resistivity type humidity measurement and NTC temperature measurement component is
included in this type of sensor which is connected to a 8 bit microcontroller which ultimately
offers an excellent quality, fast response, anti-interference and cost effectiveness.

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FIG.3.38 Darlington Transistor

The transistor consists of three pins the base pin, the emitter pin and the collector pin. The
collector pin is connected to the Arduino, the base pin is connected to the wire that carries
power supply to the device and the emitter pin is connected to the ground pin. The amount of
current passing can be controlled by giving different values in between 0-255. The collector
pin is connected to the analog output pin number 9 for the power supply to fan and the
collector pin is connected to the analog output pin number 10 for the power supply to the
light. In this prototype since we need to measure the amount of power consumed, the wire
from base pin is connected to one end of the current sensor.

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3.4THERMAL AND STRESS ANALYSIS ON SMART LEDS

(a) (b) (c)

FIG.3.41 (a) LED temperature contour and flow field formation (b) Heatsink and LED
sources temperature map (c)PCB thermal conductivity map

Smart LEDs, with an embedded antenna, not only help energy efficiency but also the overall
efficiency of the system (home) through wireless communication with other IOT devices. It is
important to study the performance of the LED under various operating conditions. At higher
temperatures, the antenna’s operating frequency shifts from its nominal value due to changes
in the PCB’s substrate dielectric constant as well as the electric resistivity of the different
metallic parts. In addition, thermal stress may cause deformation for both antenna and circuit
components causing a drop in the antenna radiation performance. Thermal analysis is

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performed using ANSYS Icepack on the LED installed in the kitchen ceiling. The LED
dissipates heat via conduction to the ceiling, and via natural convection and radiation to its
surroundings. The detailed PCB layout is imported for accurate representation of the
conduction paths.

FIG.3.42 Total solid deformation of LED bulb

The computed temperature distribution from the thermal analysis is used to re-evaluate
the material properties of the dielectric and conductor materials in the electromagnetic
analysis setup. The updated electromagnetic analysis determines a drift in the antenna’s
operating frequency. The maximum temperature of the LED in this simulation is in line with
reported values (by LED manufacturers) for a 13 Watts LED light bulb as shown in Fig.3.41

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Additionally, thermal stress and deformation analyses were conducted using ANSYS
Mechanical. The total deformation of internal components is computed and verified for
structural integrity and performance as shown in Fig.3.42.

FIG.3.43 Appliances
In this research, we have tried to depict 2 appliances light and fan. The PC cooling fan is used
instead of a real fan and a Led is used instead of a light. We have used a 12-volt battery as a
power supply to both the appliances. To operate with real appliances, we will use a relay to
switch off and, on the power, and a 220 volts electricity voltage line. The cooling fan runs at
top speed at maximum of 12 volt and the light too glows brightest at full 12 volt, the speed of
the fan and dimness of light can be controlled by the transistor.

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3.5SMART COOLING SYSTEM CONTROLLED BY IOT DEVICES

FIG.3.51 Flow streamlines in the HVAC ducting and kitchen areas at t = 36.6 sec. A
surface in air with temperature of 72 F has been shown and coloured by its velocity
value.

In this work, a virtual model of flow and heat distribution in the kitchen area of the home
with a “zonal” cooling system is demonstrated. A Computational Fluid Dynamics (CFD)
model is built using ANSYS FLUENT that includes the ducting from the HVAC unit to the
kitchen and its surroundings. In this model, two duct dampers (valves) are considered; the
first damper in the vertical duct is slightly open and feeds cool air to the second floor while
the second damper is mounted in the horizontal duct and is used to cool the kitchen
temperature. The CFD model has a 3.9 million computational grid with polyhedral elements.

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The grid has two prism layers on dampers, horizontal duct and vanes of the vent. A k-w SST
turbulence model is used to account for turbulent flow in the ducting and the house. At start
time (t = 0 sec), the duct is initialized with a temperature of 55 F, which is equal to the cool
air supply temperature from the HVAC unit. The kitchen temperature is initialized with 90 F,
a typical room temperature on a warm summer day. The damper opens at the start of the
simulation with a speed of 90 degrees/0.5sec (30 RPM). The initial time step of the model is
0.0055 sec (equal to 1 degree of rotation). After the damper is fully open (i.e., t = 0.5 s), the
time step gradually increases to capture longer operating times (it takes much longer to
stabilize the temperature in the room to a comfortable temperature such as 72 F).

The CFD model in Fig.3.51 shows details of flow and temperature distribution in
the ducts and the kitchen after opening of the damper. The streamlines of velocity in the
domain at t = 36.6 s show the cold air from the HVAC unit dissipating in the kitchen area.
Additionally, a surface in the flow with a constant temperature of 72 F is shown and its colour
indicates the flow velocity of this surface. This provides feedback on how the room
temperature is decreasing to the intended comfort temperature of 72 F. The CFD model
outputs can provide valuable insight on the response time of cooling system to zonal damper
opening or closing. It can also provide a virtual tool to examine whether this smart IOT based
energy control procedure satisfies acceptable limits for temperature, pressure and flow
velocity in the ducting and in the living areas.

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Chapter 4
EXPECTED OUTCOME
The implementation of the Smart Home devices necessitates the
design of the individual units as well as their co-existence within the home environment.
Thus, a Multiphysics analysis approach is needed. In this paper, electromagnetic simulation
was coupled to thermal and structural simulations to demonstrate the design and tuning of the
Smart Home devices in a virtual world. Within the Smart Home, each wireless device has its
own antenna module which is designed to ensure that it adheres to specific electrical wireless
design constrains. In addition, detailed modelling of the different antennas operating in
multiple frequency bands as well as in the diverse thermal and structural environment of the
Smart Home was presented. This paper summarizes the antenna module mounted on a smart
LED as well as the one mounted on the HVAC system. The ability to control these devices
under different environmental scenarios will assist in making the smart home more energy
efficient.

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REFERENCES
[1] K. N. Vinay Sagar, S. M. Kusuma, “Home Automation Using Internet of Things,”
IRJET, e-ISSN:2395-0056, Vol. 02, Issue 03, pp. 0966-1970, June 2015.

[2] B. M. El-Basioni, S. M. Abd El-kader, and M. A. Fakhreldin, “Smart Home Design

using Wireless Sensor Network and Biometric Technologies,” IJAIEM, ISSN 2319-
4847, Vol. 2, Issue 3, March 2013.

[3] M. Chan, E. Campo, D. Esteve, and J. Y. Fourniols, “Smart homes-current features

and future perspectives,” MATURITAS Journal, Vol. 64, Issue 2, pp. 90-97, Oct.
2009.

[4] N. Sriskanthan, and T. Karand, “Bluetooth Based Home Automation System,” Journal
of Microprocessors and Microsystems, Vol. 26, pp. 281-289, 2002.

[5] R. Piyare, and M. Tazil, “Bluetooth Based Home Automation System Using Cell
Phone,” IEEE 15th International Symposium on Consumer Electronics, 2011.

[6] S. D. T. Kelly, N. K. Suryadevara, and S. C. Mukhopadhyay, “Towards the

Implementation of IoT for Environmental Condition Monitoring in Homes,” IEEE,
Vol. 13, pp. 3846-3853, 2013.

[7] R. Piyare, “Internet of Things: Ubiquitous Home Control and Monitoring System
using Android based Smart Phone,” International Journal of Internet of Things 2013.

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