DESIGN OF INTELLIGENT DEVICE TO SAVE STANDBY POWER IN NETWORK ENABLED DEVICES

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International Journal of Computer Engineering & Technology (IJCET)
Volume 7, Issue 1, Jan-Feb 2016, pp. 54-61, Article ID: IJCET_07_01_007
Available online at
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ISSN Print: 0976-6367 and ISSN Online: 0976–6375
© IAEME Publication
___________________________________________________________________________
DESIGN OF INTELLIGENT DEVICE TO
SAVE STANDBY POWER IN NETWORK
ENABLED DEVICES
Narayana Swamy .R
Research Scholar
PRIST University, Thanjavur, Tamilnadu, India
Dr. G. Mahadevan
Principal
Annai College of Engineering and Technology,
Kumbakonam, Tamilnadu, India
ABSTRACT
Network connectivity is rapidly expanding to a range of new device groups
that offer both wired and wireless network functionality. In 2012, 74% of
Internet Protocol (IP) traffic and 94% of consumer Internet traffic originated
from personal computers (PCs). By 2017, analysts predict that 49% of IP
traffic and 39% of consumer Internet traffic will originate from non‑PC
networked enabled devices. For network enabled devices, the most
appropriate method of energy consumption reduction would be the total
disconnection reduced time of operation since they are used infrequently.
Automatic Power cut-off and Reset Device is the device which will avoid the
standby power consumption. device automatically cuts off the power supply to
the appliance when it enters the standby mode. Completely cutting off the
power in turn helps in overall power consumption and in turn reduces the
electricity bills.
Key words: IP; IOT; IOB; Network Enabled Device; Standby Power
Cite this Article: M. Dhanalakshmi and Anirban Basu. Energy Efficient
Virtual Machine Assignment Based on Energy Consumption and Resource
Utilization in Cloud Network. International Journal of Computer Engineering
and Technology, 7(1), 2016, pp. 54-61.
http://www.iaeme.com/IJCET/issues.asp?JType=IJCET&VType=7&IType=1

Design of Intelligent Device To Save Standby Power In Network Enabled Devices
1. INTRODUCTION
IoT is based on ubiquitous network connectivity and its vision is “anytime, anywhere,
by anyone and anything” Fig 1.1. Increased usage of Wi-Fi devices in home
automation is due to the networked nature of deployed electronics devices and
increasing rate of adoption of mobile computing devices (smart phones, tablets, etc.).
Organizations are working on integrated technology which will enable single device
control all electronic devices and appliances. The solutions are based on open
platforms that employ a network of intelligent sensors to provide information about
the state of the home [1], such as energy generation and metering, HVAC, lighting,
security and environmental key performance indicators. This collected information is
processed and displayed on touch screens, mobile phones, and 3–D browsers and can
be later analyze various parameters like energy usage, temperature and lighting
variations, building occupancy level. Mobile devices are used to control device
functionality and ensure consumer access over the network.
Figure.1.1 Internet of Things [1]
The IoT gateways securely connect next generation intelligent infrastructure to the
IoT. They integrate technologies and protocols for embedded control, networking,
security and manageability on which third party applications can run. From the layers
of a smart building Fig.1.2, there are many integrated services that can be seen as
subsystems and are useful to provide the best conditions for the activities of the
building occupants.
Figure 1.2 Smart Buildings Layers

Narayana Swamy .R and Dr. G. Mahadevan
Figure.1.3 Smart Building Services Taxonomy
Fig.1.3 presents the taxonomy of basic services. internet enabled devices within
the building and with external entities, such as the electrical grid, simplifies building
control Using the Internet together with energy management systems offers an
opportunity to remotely access building’s energy information and control internet
enabled devices through laptops or Smartphone. This has a huge potential for
providing stakeholders feedback about energy consumption levels and the ability to
act on that information. IBMS can be considered part of a much larger information
system Fig.1.4. This system is used by occupants/owners/managers in buildings to
manage energy consumption and energy procurement and to maintain buildings
systems, based on the infrastructure of the existing Intranets and the Internet, utilizes
the same standards as other IT devices. Due to Reduced cost and reliability of WSNs
we see drastic transformation in building automation by making the maintenance of
energy efficient, productive and healthy work spaces in buildings increasingly cost
effective.
Figure 1.4 Role distributions for a classical building automation system and for a Web-of-
Things architecture.

2. NETWORK STANDBY
2.1. Newage of ICT
Network connectivity is rapidly expanding to a range of new device groups that offer
both wired and wireless network functionality.
Figure 2.1 New age ICT
In 2012, 74% of Internet Protocol (IP) traffic and 94% consumer Internet traffic
originated from PCs. By 2017, analysts predict that 49% of IP traffic and 39% of
consumer Internet traffic will originate from non‑PC networked enabled devices.
Most of the services outlined in Fig.2.1 are not new; Smart appliances and devices
transcend existing functions and capabilities, and offer new ways of providing
services simply by receiving and transmitting information that was previously not
available, quantum leaps are being achieved from established technologies in service
quantity, quality and controllability of normal activities. Network connectivity is
expected to continue growing at exponential rates for decades to come, driven by four
interrelated trends:
 Increasing global online population
 Increasing network traffic
 Increasing demand for online services, from both consumers and business
 Increasing number of devices online.
2.2. Energy Consumption
Energy consumption of network enabled devices (edge devices and user premise
network equipment) exceeded 570 TWh in 2012, surpassing the electricity
consumption of France. By 2013, this had already grown to 615 TWh, overtaking the
electricity consumption of Germany and continues to grow at a rapid rate to almost
1140 TWh by 2025 exceeding the current electricity consumption of Russia and
corresponding to 6% of current total final global electricity consumption. Most ICT
energy demand is consumed in the form of electricity, Fig 2.2. Thus, standby power
also has implications for the range of primary fuels used to generate electricity, as
well as on electricity infrastructure. The electricity mix varies significantly from
country to country, and changes over time [2]. To illustrate the relationship between

electricity generation and fuel use, current ICT energy consumption corresponds to
the annual electricity generated by 520 mid‑size coal‑fired power plants (500 MW),
which together would require 728 MT of coal per year. A 500 MW conventional
coal‑fired power plant may cost over USD 1 billion to construct and will incur fuel,
operating, maintenance and other costs for about 50 years. The savings potentials
from mainstreaming energy efficiency considerations into the ICT ecosystem are
considerable and growing at a rapid rate as these systems expand and connectivity
spreads. Looking just at network enabled devices, implementation of best available
technologies and solutions can result in global electricity savings of almost 740
TWh/yr by 2025. Approximately energy reduction potentials from improving the
efficiency of network‑enabled devices are assessed on a regional basis, reflecting the
different drivers for growth in networked system power demand, Fig.2.3.
Figure 2.2 Current and Projected Global Network Enabled Device Electricity Consumption.
Figure 2.3 Current and Projected Global Network Enabled Device Electricity Consumption
and Savings Potential.
0
200
400
600
800
1 000
1 200
TWh
0
200
400
600
800
1 000
1 200
TWh
Remaining consumption Savings potential

3. CUT-DOWN UNUSED LOAD
It is well known that energy is a function of power watts and time seconds. Therefore,
the strategies to reduce parasitic power consumption would require either to reduce
the total power consumed by any particular device or simply reduce the amount of
time for which it is consuming electricity. Both these approaches would result in
sufficient reduction in standby power consumption. The function of a particular type
of device generally determines the most appropriate strategy. Among these, increasing
the efficiency of the power supply watt consumption reduction would be the most
effective strategy to reduce leaking electricity in a security system since the
electronics must be powered all the time to monitor sensors. For some particular
devices, the most appropriate method of energy consumption reduction would be the
total disconnection reduced time of operation since they are used infrequently.
APCRD (Automatic Power cut-off and Reset Device) is the device which will avoid
the standby power consumption. APCRD automatically cuts off the power supply to
the appliance when it enters the standby mode. Completely cutting off the power in
turn helps in overall power consumption and in turn reduces the electricity bills, Fig
3.1. Reducing the power consumption worldwide helps in reducing the carbon dioxide
emission by 1% i.e. helps in reducing the global warming.
Figure.3.1 Proposed System Block Diagram.
4. STANDBY CONSUMPTION AND POTENTIAL SAVINGS
In case of APCRD the reduction of standby energy consumption is 100%
(261.3kWh), 0% For the Eco design and BAT cases as both require stock turnover
and reduction is achieved only after replacement of the existing systems and both
reach their maximum savings in 2025, reducing standby electricity consumption per
household by an average of 77% and 80%, Fig.4.1.
Figure 4.1 Percentage of Energy savings between Eco design and BAT.
0
20
40
60
80
100
Eco Design
BAT

Figure 4.2 Comparison of standby energy reduction of total households for the period 2013-
2025.
Fig 4.2 shows, standby energy savings with the use of APCRD achieve the highest
values compared with Eco design and BAT case. These savings gradually start
growing for BAT and Eco design Directive. Higher economic benefits are associated
with the use of standby reduction device Fig 4.3. The APCRD devices achieve the
highest CO2 reduction followed by BAT and Eco design Fig 4.4. By applying all the
above mentioned standby power minimization concepts, a significant amount of
energy efficiency improvement is attainable. This, in turn, will minimize the overall
power consumption per household or an industry and reduced energy demand.
Another benefit in this process is the carbon emission reduction, which contributes to
a green atmosphere and thus a green economy Table.4.1.
Figure 4.3 Comparison of economic benefits of total households for the period 2013-2025.
Figure 4.4 Comparison of CO2 savings of total households for period 2013-2025.
0
0.5
1
1.5
2
2.5
Proposed
Eco Design
BAT
0
100
200
300
400
500
2013
2015
2017
2019
2021
2023
2025
Proposed
Eco Design
BAT
0
0.2
0.4
0.6
0.8
1
2013
2015
2017
2019
2021
2023
2025
Proposed
Eco Design
BAT

Table.4.1 Proposed System-Results of energy, CO2 savings & conomic benefits
5. CONCLUSION
Network standby consumption of existing appliance stock, BAT and standby
consumption with standby reduction devices was measured. Network standby power
consumption was analysed in order to investigate consumer behaviour and patterns,
market penetration of appliances. Results of the effectiveness of the proposed system
with respect to Eco design and BAT are compared, with a focus on the savings.
Implemented successfully on any electronic device which enters into standby mode; it
becomes one of the most feasible products to the user. The reduces standby power,
which in turn reduces demand and in turn controls the supply which leads to
economic benefits and reduction in CO2.
REFERENCES
[1] See ITU Internet Reports 2004: The Portable Internet, available
http://www.itu.int/portableinternet/.
[2] A. Arnall, D. Parr, Moving the nanoscience and technology (NST) debate
forwards: short-term impacts, long-term uncertainty and the social constitution,
Technology in Society, Volume 27, pp.23-38, 2005.
[3] Jaykumar Jagani and Prof. Kamlesh Patel. An Enhanced Algorithm For
Classification of Web Data For Web Usage Mining Using Supervised Neural
Network Algorithms. International Journal of Computer Engineering and
Technology, 5(4), 2014, pp. 45-65.
[4] Prof. S.B. Javheri and Shwetambari Ramesh Patil. Attacks Classification in
Network. International Journal of Information Technology and Management
System, 4(3), 2013, pp. 01-11.
Results Proposed Eco design BAT
Annual energy savings per hh in
kWh
261.3 0.04 4.74
Annual energy savings of total hh
for 2013 in TWh
1.96 0.0003 0.04
Energy savings for period 2013-
2025 in TWh
28.3 12.3 13.1
Annual economic benefits per hh 54.2 0.01 0.98
Annual economic benefits for the
year 2013 in Million
408 0.06 7.4
Total economic benefits for period
2013-2025 in billion
5.47 2.55 2.71
Annual CO2 savings per hh, in Kg
CO2
104.5 0.016 1.896
Annual CO2 savings of total hh in
2013, in Million tons CO2
0.78 0.000 0.014
Total CO2 savings of total hh for
period 2013-2025 in M tons CO2
10.54 4.91 5.22

DESIGN OF INTELLIGENT DEVICE TO SAVE STANDBY POWER IN NETWORK ENABLED DEVICES

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