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Foreword
A successful preliminary project initiation meeting is the one that facilitates satisfactory results.
With immense pleasure and gratitude IEEE BKBIET SB is presenting the first edition of
“Technefois”, the magazine. Earlier named as “The Tech Times”.
This magazine is a combination of many creative mind sets who work for the betterment of life
through technology. Information of technological areas have been bound together. We, being a
team welcome all the comments and feedback by our readers. The contact details can be found
at the end of the magazine.
A special gratitude towards the Director of B. K. Birla Institute of Engineering & Technology,
Dr. S. M. Prasanna Kumar and the Branch Counsellor, Dr .L. Solanki.
Thank you.
Contents
~ From the desk of
i. Anti – Solar Panel
ii. Embedded Systems
iii. Deep Learning
iv. SAP
v. Robotic Process Automation
vi. Wearable Technology
vii. Smart home Technology
viii. Quantum Computer
ix. Regenerative Braking System
x. Cloud computing
xi. Machine Learning
xii. Blockchain
xiii. Development of Arduino
Mailing Address
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15
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Dr. S.M. Prasanna Kumar
Director, BKBIET
Message
It gives me immense pleasure in noting down, as usual, every year this year as well, IEEE
chapter of BKBIET team is ready to publish magazine, which helps student fraternity to go
through the modern and emerging areas of technology and application area of the same in
reputed industries.
The content of this magazine is worth appreciable. The topics chosen by the students are
displaying their thoughts in new modern areas, this itself says their mode of learning and
knowing about application drive and industry requirement has started with a positive note.
The articles “Anti solar panel”, “Embedded Systems”, “Deep learning”, “SAP”, “Robotic
process Automation”, “Wearable Technology” , “Smart home Technology”, “Quantum
computers”, “Regenerative braking system”, “Cloud computing”, “Machine Learning”, “Block
chain”, “Development of Arduino” themselves say the interest shown by the students are all
buzz words in industry. Also, very proud to acknowledge the written articles are worth to note
by everyone.
I wish each and every member and all other students a grand success in taking up this chapter to
greater heights and acquire the industrial knowledge by participating and attending all activities.
From the desk of…
Prof. (Dr.) L. Solanki
Branch Counsellor – IEEE BKBIET SB
Message
I am very pleased to learn that newly elected IEEE-BKBIET ExeComm which was formulated for
session the 2020-21 is coming up with its first issue of Technical Magazine “Technefois” and I am
sure that this magazine will provide a platform for students to share their innovative ideas and plans
to resolve the future growth of the country.
I wish to thank all its past Chairman, Vice Chair, Secretaries and ExeComm members for giving
their valuable contributions in adding value to IEEE-BKBIET chapter, and making it most active,
popular and prominent among the IEEE chapters in the northern region.
My best wishes to present Chairperson Kumar Sachin and his team members for taking up the
initiative so early and with great enthusiasm. I wish that present ExeComm will together add an
extra feather in the cap of the IEEE-BKBIET chapter.
Finally, my sincere thanks to the students whose articles have been selected for publication, and
happy to acknowledge their achievements.
From the desk of…
Mr. Santosh Jangid
Faculty Advisor – IEEE BKBIET Pilani Chapter
HoD Electronics Department
Message
It gives me immense pleasure to learn about the forthcoming technical magazine for IEEE
BKBIET Pilani Chapter .I wish to extend my deep appreciation to the new Executive Team of
this professional body who have so generously volunteered their time to plan out the new
upcoming events for IEEE Pilani Chapter. I hope that this creative endeavour will bring out an
array of scientific and technological expressions with distinct individual signatures. I congratulate
the editorial board for bringing out this magazine as per schedule, which in itself is an achievement
considering the effort and time required. I again wish the team to achieve the future endeavours.
From the desk of…
Mr. Praveen Kr. Sharma
Faculty Advisor – IEEE BKBIET Pilani Chapter
Assistant Professor, Department of Electronics and Communication Engineering
Message
The forthcoming technical magazine “Technefois”, of the IEEE BKBIET Pilani Chapter reveals
the hard work and sincerity of work that the complete IEEE team is performing from the past
many years. I have been fortunate enough to be a part of this team. I hope that the newly appointed
Executive Committee 2020 will add another milestone to their account with this magazine. I want
to wish all the members of the editorial team who are directly or indirectly associated with this
work an enormous success. I know that all the members of the IEEE BKBIET family will maintain
their legacy and continue to shine as always.
“STRIVE NOT TO BE A SUCCESS BUT RATHER TO BE OF VALUE- ALBERT EINSTEIN”
Best of Luck!
From the desk of…
Researchers have developed a new prototype of night time solar cells that can produce
electricity at night through a radiative cooling mechanism.
Solar power has numerous benefits. Notably, it is a clean and renewable energy resource that
can help us to reduce carbon emissions from fossil fuel use and mitigate climate change.
However, solar energy production is limited to daytime hours when sunlight is abundant.
Researchers from the University of California, Davis explain in a new paper that was just
published in the journal ACS Photonics that if you want to create a solar panel that generates
electricity at night, then you just have to create one that operates the exact opposite way solar
panels work during the day. It’s being referred to as the “anti-solar panel”.
Tristan Deppe of the University of Maryland and Jeremy Munday of the University of
California, Davis are currently developing prototypes of these new night time solar cells. Jeremy
Munday explained the concept in detail in statement.
A regular solar cell generates power by absorbing sunlight, which causes a voltage to appear
across the device and for current to flow. In these new devices, light is instead emitted and the
current and voltage go in the opposite direction, but you still generate power. You have to use
different materials, but the physics is same.
You have heat energy coming from the Sun towards the Earth and that normal solar cell picks
off that energy as it’s transmitted from Sun to Earth, so basically you need these two different
temperature bodies and some way of converting that power. What this nigh time device does is
similar sort of thing – where it’s just taking a hot body and a cold body – but now the relatively
hot body is the Earth and space is the cold body. As this heat is flowing from the Earth to outer
space, it’s picking that off and converting that into power.
Munday and his team are currently working on developing prototypes to see how well they can
make this concept work.
While the prototype night time solar cells can only generate about a quarter of the energy
produced by conventional solar cells, the scientist hoping that they can improve their
performance in the future better designs. This would represent an exciting breakthrough in
renewable energy research.
SOLAR Panels don’t generate
electricity at night, so we have to
store the electricity they generate
during the day to power
applications during the evening.
That works fine, but what if we
could develop solar panels that
did generate electricity at night?
It’s possible, and the way it works
is pretty surprising.
01
ANTI – SOLAR PANEL
The devices don’t use the same technology as solar panels, although they’d probably look
similar. Solar panels rely on photovoltaic cells that absorb to create electron – hole pairs across
the semiconductor, generating a working voltage. A night time panel would use a
thermoradiative cell to emit infrared radiation from the Earth into space to create electron – hole
pairs.
The team estimates that thermoradiative cells would only be able to generate about a quarter as
much power as a solar panel of the same area. That’s mainly a consequence of the lower energy
of infrared light. Silicon is the current material of choice for solar panels as it’s good at
capturing light in the visible wavelengths. It may be possible to boost the efficiency of
thermoradiative cells by using materials that can better interact with longer wavelengths of light,
for example, mercury alloys.
The University of California study is just an initial proposal for night time energy generation.
The next step is to start building the devices to see how well they perform.
Source: Deanna Conners in HUMAN WORLD; Nighttime Photovolatic Cells:
Electrical Power Generation by optically Coupling with Deep Space (Via
University of California, Davis)
TAGS: SOLAR ENERGY | CLIMATE CRISIS
-Kumar Sachin
Other researchers are also looking into how to make solar panels, or “anti-solar panels”, that generates
electricity at night. Researchers at Stanford published a paper in the journal Jouele in November showing
how a thermoelectric generator that radiates heat to the sky can generate electricity.
02
An embedded system is a computer system—a combination of a computer processor, computer
memory, and input/output peripheral devices—that has a dedicated function within a larger
mechanical or electrical system. It is embedded as part of a complete device often including
electrical or electronic hardware and mechanical parts. Because an embedded system typically
controls physical operations of the machine that it is embedded within, it often has real-time
computing constraints. Embedded systems control many devices in common use today. Ninety-
eight percent of all microprocessors manufactured are used in embedded systems. Modern
embedded systems are often based on microcontroller (i.e. microprocessors with integrated
memory and peripheral interfaces), but ordinary microprocessors (using external chips for
memory and peripheral interface circuits) are also common, especially in more complex systems.
In either case, the processor(s) used may be types ranging from general purpose to those
specialized in a certain class of computations, or even custom designed for the application at hand.
A common standard class of dedicated processors is the digital signal processor (DSP).
Since the embedded system is dedicated to specific tasks, engineers can optimize it to reduce the
size and cost of the product and increase the reliability and performance. Complexity varies from
low, with a single microcontroller chip, to very high with multiple units, peripherals and networks
mounted inside a large equipment rack. Embedded systems are commonly found in consumer,
industrial, automotive, home appliances, medical, commercial and military applications.
Telecommunications systems employ numerous embedded systems from telephone switches for
the network to cell phones at the end user. Computer networking uses dedicated routers and
network bridges to route data.
Consumer electronics include MP3 players, television sets, mobile phones, video game consoles,
digital cameras, GPS receivers, and printers. Household appliances, such as microwave ovens,
washing machines and dishwashers, include embedded systems to provide flexibility, efficiency
and features. Advanced HVAC systems use networked thermostats to more accurately and
efficiently control temperature that can change by time of day and season. Home automation uses
wired- and wireless-networking that can be used to control lights, climate, security, audio/visual,
surveillance, etc., all of which use embedded devices for sensing and controlling.
-Cherry Vaish
03
EMBEDDED SYSTEM
04
Deep Learning is a new area of Machine Learning research, which has been introduced with the
objective of moving Machine Learning closer to one of its original goals: Artificial Intelligence.
It is capable of learning unsupervised data that is unstructured or unlabeled. Also known as deep
neural learning or deep neural network.
In deep learning, a computer model learns to perform classification tasks directly from images,
text, or sound. Deep learning models can achieve state-of-the-art accuracy, sometimes exceeding
human-level performance. Models are trained by using a large set of labeled data and neural
network architectures that contain many layers.
While deep learning was first theorized in the 1980s, there are two main reasons it has only
recently become useful:
1. Deep learning requires large amounts of labeled data. For example, driverless car development
requires millions of images and thousands of hours of video.
2. Deep learning requires substantial computing power. High-performance GPUs have a parallel
architecture that is efficient for deep learning. When combined with clusters or cloud computing,
this enables development teams to reduce training time for a deep learning network from weeks
to hours or less.
Deep learning is a machine learning technique that teaches computers to do what comes naturally
to humans: learn by example. Deep learning achieves recognition accuracy at higher levels than
ever before. Recent advances in deep learning have improved to the point where deep learning
outperforms humans in some tasks like classifying objects in images.
What’s the difference between deep learning and machine learning?
A machine learning workflow starts with relevant features being manually extracted from images.
The features are then used to create a model that categorizes the objects in the image. With a deep
learning workflow, relevant features are automatically extracted from images. In addition, deep
learning performs “end-to-end learning” – where a network is given raw data and a task to
perform, such as classification, and it learns how to do this automatically.
A key advantage of deep learning networks is that they often continue to improve as the size of
your data increases. In machine learning, you manually choose features and a classifier to sort
images. With deep learning, feature extraction and modeling steps are automatic.
-Sakshi Kumari
DEEP LEARNING
SAP is one of the world’s leading producers of software for the
management of business processes, developing solutions that enable effective data processing
and information flow across organizations.
Founded in 1972, the company was initially called System Analysis Program Development
(Systemanalyse Programmentwicklung), later abbreviated to SAP. Since then, it has grown from
a small five-person startup to a multinational enterprise with more than 100,000 employees and
over 440,000 customers in 180 countries. Its global headquarters is in Walldorf, Germany.
With its original SAP R/2 and SAP R/3 software, SAP established the standard for enterprise
resource planning (ERP) software. SAP S/4HANA takes ERP to the next level by using the
power of in-memory computing to process vast amounts of data and support advanced
technologies such as artificial intelligence (AI) and machine learning.
The company’s integrated applications connect all parts of a business into an intelligent suite on
a digital platform. Today, SAP has more than 215 million cloud users, more than 100 solutions
covering all business functions, and the largest cloud portfolio of any provider.
The name is an acronym of the company’s original German name: Systemanalyse
Programmentwicklung, which translates to System Analysis Program Development. Today the
company’s legal corporate name is SAP SE — SE stands for societas Europaea, a public
company registered in accordance with the European Union corporate law.
What is SAP software used for?
Traditional business models often involve decentralized data management, with each business
function storing data about its operations in a separate database. This means that employees from
other business functions cannot access the information, and duplication of data across multiple
departments increases IT storage costs and the risk of data errors.
By centralizing data management, SAP software provides a single view of the truth that is used
by multiple business functions. This helps companies better manage complex business processes
involving different departments by giving employees access to real-time insights across the
enterprise. As a result, businesses can accelerate workflows, improve operational efficiency, raise
productivity, enhance customer experiences – and ultimately increase profits.
-Tushar Budhiraja
05
SAP
Robotic Process Automation (RPA) is enjoying tremendous growth as organizations worldwide
seek to accelerate productivity and boost efficiency by automating mundane and repetitive tasks.
Yet despite its benefits, RPA continues to stir debates about replacement of the human workforce.
When you bring up automation, it is not uncommon for employees to think “job loss.”
A significant number of organizations remain hesitant to adopt RPA within business or IT
functions because employees worry that it will change their roles and responsibilities.
When implemented thoughtfully, however, RPA can reduce the costs associated with Human
Training, services, and support will become more important over time.
RPA does not interfere with existing systems of records or business applications and therefore
does not require a lot of integration work. However, to leverage RPA software, individuals and
teams must be trained so that deployment and implementation meet expectations.
People didn’t believe much on creation of robots in older decades. Aparently, humans again
proved that nothing is impossible. Robots do much of the human work, satisfactorily when given
proper command. Digital workers and robots are essential to eliminate existing skill gaps while
also improving the productivity and quality of work. One way to overcome resistance is to identify
an initial path and start by automating small, highly manual processes. This will let you prove
quick wins that build momentum with key stakeholders and employees.
Most of the vendors offer free version that allow for proofs-of-concept, and current, per-bot
licensing models make it possible to invest into RPA one bot at the time.
-Suyash Sharma
06
ROBOTIC PROCESS
AUTOMATION
Wearable technology, wearables, fashion technology, tech togs, or fashion electronics are smart
electronic devices (electronic device with micro-controllers) that are worn close to and/or on the
surface of the skin, where they detect, analyze, and transmit information concerning e.g. body
signals such as vital signs, and/or ambient data and which allow in some cases immediate
biofeedback to the wearer. Wearable technology has a variety of applications which grows as
the field itself expands. It appears prominently in consumer electronics with the popularization
of the smartwatch and activity tracker. Apart from commercial uses, wearable technology is
being incorporated into navigation systems, advanced textiles, and healthcare.
Google Glass
The day marked with the official launch of Google Glass, a device intended to deliver rich text
and notifications via a heads-up display worn as eyeglasses. The device also had a 5 MP camera
and recorded video at 720p. Its various functions were activated via voice command, such as
"OK Glass". The company also launched the Google Glass companion app, MyGlass. The first
third-party Google Glass App came from the New York Times, which was able to read out
articles and news summaries.
Monitoring Systems for assisted living
Another field of application of wearable technology is monitoring systems for assisted
living and eldercare. For this reason, researchers are moving their focus from data collection to
the development of intelligent algorithms able to glean valuable information from the collected
data, using data mining techniques such as statistical classification and neural networks.
Virtual Reality
Another increasingly popular wearable technology involves virtual reality. VR headsets have
been made by a range of manufacturers for computers, consoles, and mobile devices. Recently
Google released their headset, the Google Daydream. In July 2014 a smart technology footwear
was introduced in Hyderabad, India. The shoe insoles are connected to a smartphone application
that uses Google Maps, and vibrate to tell users when and where to turn to reach their
destination.
07
WEARABLE TECHNOLOGY
Bluetooth Sunglasses
This bluetooth headset headphone sunglasses is the perfect combination of durable and fashion.
You may wear it and enjoy music anytime anywhere, getting hands-free phone call, control the
phone to take pictures of yourself. It also can filter ultraviolet and protect your eyesight at the
same time. The Bose Frames are the answer to the question: what if your sunglasses were also a
set of smart, hidden headphones with no earbuds or no bone-conduction system, just a set of
personal speakers? There’s no screen, camera or any visible signs of “smart” from the front.
Instead they have built-in sensors and a pair of hidden speakers, which pipe music to your ears.
Smartwatches and Activity Trackers
While optical head-mounted display technology remains a niche, two popular types of wearable
devices have taken off: smartwatches and activity trackers.
The FDA drafted a guidance for low risk devices advises that personal health wearables are
general wellness products if they only collect data on weight management, physical fitness,
relaxation or stress management, mental acuity, self-esteem, sleep management, or sexual
function.This was due to the privacy risks that were surrounding the devices. Although they help
track health and promote independence there is still an invasion of privacy that ensues to gain
information. This is due to the huge amounts of data that has to be transferred which could raise
issues for both the user and the companies if a third partied gets access to this data. The issue is
consent as well when it comes to wearable technology because it gives the ability to record and
that is an issue when permission is not asked when a person is being recorded.
-Komal Sharma
08
Smart Home technology often referred to as home automation or domotics (from the Latin
"domus" meaning home), provides homeowners security, comfort, convenience and energy
efficiency by allowing them to control smart devices, often by a smart home app on their
smartphone or other networked device. A part of the internet of things (IoT), smart home systems
and devices often operate together, sharing consumer usage data among themselves and
automating actions based on the homeowner’s preferences.
The origin of the smart home
With the 1975 release of X10, a communication protocol for home automation, the smart home,
once a pipe dream a la The Jetsons, came to life. X10 sends 120 kHz radio frequency (RF) bursts
of digital information into a home's existing electric wiring to programmable outlets or switches.
These signals convey commands to corresponding devices, controlling how and when the devices
operate. A transmitter could, for example, send a signal along the house's electric wiring, telling
a device to turn on at a specific time.
Nest Labs was founded in 2010 and released its first smart product, the Nest Learning Thermostat,
in 2011. The company also created smart smoke/carbon monoxide detectors and security
cameras. After being acquired by Google in 2015, it became a subsidiary of Alphabet Inc. in the
same year.
In 2012, Smart Things Inc. launched a Kick starter campaign, raising $1.2 million to fund its
smart home system. Following additional funding, the company came in the market in August
2013 and was acquired by Samsung in 2014.
Recently, companies including Amazon, Apple and Google have released their own smart home
products and demotics platforms, including Amazon Echo, Apple Home Kit and Google Home.
Examples of smart home technology
~ Smart TVs connect to the internet to access content through applications, such as on-demand
video and music. Some smart TVs also include voice or gesture recognition.
~ In addition to being able to be controlled remotely and customized, smart lighting systems,
such as Hue from Philips Lighting Holding B.V., can detect when occupants are in the room and
adjust lighting as needed. Smart light bulbs can also regulate themselves based on daylight
availability.
09
SMART HOME TECHNOLOGY
• Using smart locks and garage-door openers, users can grant or deny access to visitors. Smart
locks can also detect when residents are near and unlock the doors for them.
• With smart security cameras, residents can monitor their homes when they are away or on
vacation. Smart motion sensors are also able to identify the difference between residents,
visitors, pets and burglars, and can notify authorities if suspicious behavior is detected.
Kitchen appliances of all sorts are available, including smart coffee makers that can brew you
a fresh cup as soon as your alarm goes off.
• Household system monitors may, for example, sense an electric surge and turn off appliances
or sense water failures or freezing pipes and turn off the water so there isn't a flood in your
basement
• Smart thermostats, such as Nest from Nest Labs Inc., come with integrated Wi-Fi, allowing
users to schedule, monitor and remotely control home temperatures. These devices also learn
homeowners' behaviors and automatically modify settings to provide residents with
maximum comfort and efficiency. Smart thermostats can also report energy use and remind
users to change filters, among other things.
• Using smart locks and garage-door openers, users can grant or deny access to visitors. Smart
locks can also detect when residents are near and unlock the doors for them
-Kanchan Tanwar
10
Quantum computers are machines that use the properties of quantum physics to store data and
perform computations. This can be extremely advantageous for certain tasks where they could
vastly outperform even our best supercomputers.
Classical computers, which include Smartphone’s and laptops, encode information in binary
“bits” that can either be 0s or 1s. In a quantum computer, the basic unit of memory is a quantum
bit or qubit.
Quantum computers, on the other hand, use qubits, which are typically subatomic particles such
as electrons or photons. Generating and managing qubits is a scientific and engineering
challenge. Some companies, such as IBM, Google, and Rigetti Computing, use superconducting
circuits cooled to temperatures colder than deep space. Others, like IonQ, trap individual atoms
in electromagnetic fields on a silicon chip in ultra-high-vacuum chambers. In both cases, the
goal is to isolate the qubits in a controlled quantum state.
Qubits have some quirky quantum properties that mean a connected group of them can provide
way more processing power than the same number of binary bits. One of those properties is
known as superposition and another is called entanglement.
What can quantum computers do?
Quantum computers will find a use anywhere where there’s a large, uncertain complicated
system that needs to be simulated. That could be anything from predicting the financial markets,
to improving weather forecasts, to modelling the behaviour of individual electrons: using
quantum computing to understand quantum physics.
Quantum computers aren’t just about doing things faster or more efficiently. They’ll let us do
things that we couldn’t even have dreamed of without them. Things that even the best
supercomputer just isn’t capable of.
11
QUANTUM COMPUTERS
WHAT IS QUANTUM SUPERPOSITION ?
Superposition helps do away from binary constraints. The working of a quantum computer is
based on using the particles in superposition. Rather than representing bits, such particles
represent qubits, which can take on the value 0, 1, or both simultaneously.
Quantum computer can hold the information using a system that can exist in two states at the
same time. This is possible due to the superposition principle of quantum mechanics. This
“qubit” can simultaneously store a “0” and “1.” Similarly, two qubits can simultaneously hold
four values: 00, 01, 10, and 11.
Conclusion — TRANFORMATION IN TECHNOLOGY
We can never imagine what such a new technology can achieve in the next 10 years. Researchers
are working on creating full-fledged quantum computers to answer problems which are just too
hard for classical computers today. Many fields such a cryptography, machine learning,
information security may soon undergo a drastic change due to the advent of the Quantum
computing capabilities. World of science and technology is getting weirder and harder to explain
day by day. We cannot even imagine how the entire concept of computing might change in the
coming years, and that’s what excites me the most!
“Without change there is no innovation, creativity, or incentive
for improvement. Those who initiate change will have a better
opportunity to manage the change that is inevitable.”
-Abhishek Pandey
12
Moving vehicles have a lot of kinetic energy, and when brakes are applied to slow a vehicle, all
of that kinetic energy has to go somewhere. Back in the Neanderthal days of internal combustion
engine cars, brakes were solely friction based and converted the kinetic energy of the vehicle into
wasted heat in order to decelerate a car. All of that energy was simply lost to the environment.
Fortunately, we have evolved as a species and developed a better way. Regenerative braking uses
an electric vehicle’s motor as a generator to convert much of the kinetic energy lost when
decelerating back into stored energy in the vehicle’s battery. Then, the next time the car
accelerates, it uses much of the energy previously stored from regenerative braking instead of
tapping in further to its own energy reserves.
It is important to realize that on its own, regenerative braking isn’t a magical range booster for
electric vehicles. It doesn’t make electric vehicles more efficient per se, it just makes them less
inefficient. Basically, the most efficient way to drive any vehicle would be to accelerate to a
constant speed and then never touch the brake pedal. Since braking is going to remove energy and
require you to input extra energy to get back up to speed, you’d get your best range by simply
never slowing down in the first place.
But that obviously isn’t practical. Since we need to brake often, regenerative braking is the next
best thing. It takes the inefficiency of braking and simply makes the process less wasteful.
Effectiveness
This is where things get really interesting. The effectiveness of regenerative braking is a measure
of how much it can increase your range. Does it make your theoretical range 5% further? 50%
further? Even more?
As you’ve probably already guessed, the effectiveness of regenerative braking varies
significantly based on factors including driving conditions, terrain and vehicle size.
Driving conditions have a large impact. You’ll see much better effectiveness for regenerative
braking in stop-and-go city traffic than in highway commuting. This should make sense, as if
you’re repeatedly braking, you’ll recapture a lot more energy than if you simply drive for hours
without touching the brake pedal. Terrain also plays a large role here too, as uphill driving
doesn’t give you much chance for braking, but downhill driving will regenerate a much larger
amount of energy due to the long braking periods. On long downhills, regenerative braking can
be used nearly constantly to regulate speed while continuously charging the battery.
13
REGENERATIVE BRAKING
SYSTEM
Vehicle size may be the largest factor in the effectiveness of regenerative braking for the simple
reason that heavier vehicles have much more momentum and kinetic energy. Just like a big
flywheel is more effective than a small flywheel, a four-wheel electric car has a lot more kinetic
energy when in motion than an electric bicycle or scooter.
Data for comparison can be somewhat hard to come by. Tesla vehicles show you the
regenerative braking power, such as 60 kW during hard braking, but that doesn’t answer the
more interesting question. We want to know how much energy we are recapturing over a trip,
not how strong our brakes are each time we mash the pedal.
Fortunately, a number of Tesla drivers have reported back energy contribution data using
different data tracking apps. Model S drivers have reported recapturing as much as 32% of their
total energy use while driving up and then back downhill. This would effectively increase a 100
mile car’s range to 132 miles, for example. A Model S P85D owner reported approximately
28% energy recapture (forum in Danish) and still others have reported recapturing between 15-
20% of their total kWh usage on average during normal trips.
For smaller EVs such as personal electric vehicles, the numbers aren’t quite as optimistic. On
multiple electric bicycles with regenerative braking options, I’ve generally averaged around 4-
5% regeneration, with a maximum of around 8% in hilly areas. Other personal electric vehicles
including electric scooters and skateboards have similar results, usually in the lower single
digits. Again, keep in mind this isn’t the raw efficiency of the system (as in how much braking
energy is lost in the energy transfer), it’s the effectiveness (as in how much further your range
increases due to the use of regenerative braking).
They do not have much momentum and thus have less kinetic energy to convert back into the
battery.
-Tarun Sharma
14
What is Cognitive Computing? Cognitive Computing refers to machine systems that can mimic human understanding of the
environment, bringing an immense level of contextualization and intelligence to business
processes. Cognitive Computing is closely related to artificial intelligence and its multiple
subsumed technologies (image recognition, pattern recognition, machine learning, natural
language processing, and the like).
It differs from traditional data analytics, owing to its agile, interactive and contextual properties.
A cognitive algorithm, for example, can intuitively change in response to real-time data and help
you make more accurate decisions. And, the interfaces used for Cognitive are very high on
intractability, letting users deep-dive into the insights and multiple predictive scenarios available.
But the biggest USP of Cognitive is possibly its power to contextualize information. Equipped
with in-the-moment data on customers/users/machines, algorithms can make decisions that are
relevant and effective.
Expectedly, Cognitive is highly resource-intensive, requiring powerful servers, deep technical
skillsets, and often leading to a high degree of technical debt. For example, developing machine
learning models not only consumes significant computing power but also adds technical debt
with every learning cycle. That’s why, for a long time, Cognitive was limited to large enterprises
such as the Fortune 500s.
This has been completely overturned by the cloud. The Cloud allows developers to build
Cognitive models, test solutions, and integrate with existing systems without needing physical
infrastructure. While there are still resource costs involved, enterprises can flexibly subscribe to
Cloud resources for Cognitive development and downscale as and when necessary.
-Abhishek Sharma
15 15
CLOUD COMPUTING
Let’s Demystify Machine Learning!!
Machine Learning: - Now that’s a word that packs a punch! Machine learning is hot stuff these
days! And why won’t it be? Almost every “enticing” new development in the field of Computer
Science and Software Development in general has something related to machine learning behind
the veils. Microsoft’s Cortana - Machine Learning, Object and Face Recognition – Machine
Learning and Computer Vision. Advanced UX improvement programs – Machine Learning (yes!
The Amazon product recommendation you just got was the number crunching effort of some
Machine Learning Algorithm).
And not even just that. Machine Learning and Data Science in general is EVERYWHERE. It is
as omnipotent as God himself, had he been into Computers! Why? Because Data is everywhere!
So it is natural, that anyone who has above average brains and can differentiate between
Programming Paradigms by taking a sneak-peek at Code, is intrigued by Machine Learning.
But what is Machine Learning? And how big is Machine Learning? Let’s demystify Machine
Learning, once and for all. And to do that, rather than presenting technical specifications, we’ll
follow a “Understand by Example” approach.
Well, Machine Learning is a subfield of Artificial Intelligence which evolved from Pattern
Recognition and Computational Learning theory. Arthur Lee Samuel defines Machine Learning
as: Field of study that gives computers the ability to learn without being explicitly programmed.
So, basically, the field of Computer Science and Artificial intelligence that “learns” from data
without human intervention.
But this view has a flaw. As a result of this perception, whenever the word Machine Learning is
thrown around, people usually think of “A.I.” and “Neural Networks that can mimic Human brains
(as of now, that is not possible)”, Self-Driving Cars and what not. But Machine Learning is far
beyond that. Below we uncover some expected and some generally not expected facets of Modern
Computing where Machine Learning is in action.
So as you might have seen now. Machine Learning actually is everywhere. From Research and
Development to improving business of Small Companies. It is everywhere. And hence it makes
up for quite a career option, as the industry is on the rise and is the boon is not stopping any time
soon.
So, this is it for now. This wraps up our Machine Learning 101. We’ll hopefully meet again, and
when we do, we’ll dive into some technical details of Machine Learning, what tools are used in
the industry, and how to start your journey to Machine Learning prowess. Till then, Code Away!
-Yashaswini .S. M.
16
MACHINE LEARNING
Although most people think of blockchain technology in relation to cryptocurrencies such as Bitcoin,
blockchain offers security that is useful in many other ways. In the simplest of terms, blockchain can
be described as data you can only add to, not take away from or change. Hence the term “chain”
because you’re making a chain of data. Not being able to change the previous blocks is what makes it
so secure. In addition, blockchains are consensus-driven, so no one entity can take control of the data.
Key elements of Blockchain
Distributed ledger technology
All network participants have access to the distributed ledger and its immutable record of transactions.
With this shared ledger, transactions are recorded only once, eliminating the duplication of effort that’s
typical of traditional business networks
Records are immutable
No participant can change or tamper with a transaction after it’s been recorded to the shared ledger. If
a transaction record includes an error, a new transaction must be added to reverse the error, and both
transactions are then visible.
Smart contracts
To speed transactions, a set of rules – called a smart contract – is stored on the blockchain and executed
automatically.
Types of blockchain networks:
There are several ways to build it, viz:-
Public blockchain networks
A public blockchain is one that anyone can join and participate in, such as Bitcoin. Drawbacks might include substantial computational power required, little or no privacy for transactions, and weak security. These are important considerations for enterprise use cases of blockchain. Private blockchain networks
A private blockchain network, similar to a public blockchain network, is a decentralized peer-to-peer network, with the significant difference that one organization governs the network. Permissioned blockchain networks Businesses who set up a private blockchain, will generally set up a permissioned blockchain
network. It is important to note that public blockchain networks can also be a permissioned.
The Bitcoin is the first successful implementation of blockchain. Today, the world has found
applications of blockchain technology in several industries, where the trust without the involvement of a
centralized authority is desired. So welcome to the world of Blockchain.
-Sandeep Shah
-
17
BLOCKCHAIN
Arduino provides open-source electronics prototyping platforms based on flexible, easy-to-use
hardware and software. Arduino prototyping platforms are intended for artists, designers,
hobbyists, and anyone interested in creating interactive objects or environments. Arduino's
prototyping platforms can sense the environment by receiving input from a variety of sensors and
can affect their surroundings by controlling lights, motors, and other actuators. Arduino projects
can be stand-alone or they can communicate with software running on a computer.
In 2005, building upon the work of Hernando Barragán (creator of Wiring), Massimo Banzi and
David Cuartielles created Arduino, an easy-to-use programmable device for interactive art design
projects, at the Interaction Design Institute Ivrea in Ivrea, Italy. David Mellis developed the
Arduino software, which was based on Wiring. Before long, Gianluca Martino and Tom Igoe
joined the project, and the five are known as the original founders of Arduino. They wanted a
device that was simple, easy to connect to various things (such as relays, motors, and sensors),
and easy to program. It also needed to be inexpensive, as students and artists aren’t known for
having lots of spare cash. They selected the AVR family of 8-bit microcontroller (MCU or µC)
devices from Atmel and designed a self-contained circuit board with easy-to-use connections,
wrote bootloader firmware for the microcontroller, and packaged it all into a simple integrated
development environment (IDE) that used programs called “sketches.” The result was the
Arduino.
Since then the Arduino has grown in several different directions, with some versions getting
smaller than the original, and some getting larger. Each has a specific intended niche to fill. The
common element among all of them is the Arduino runtime AVR-GCC library that is supplied
with the Arduino development environment, and the on-board bootloader firmware that comes
preloaded on the microcontroller of every Arduino board.
-Manash Khetan
DEVELOPMENT OF ARDUINO
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02
IEEE Executive Committee 2020-2021
Designation Member Name
Chairperson Kumar Sachin
Vice-Chairperson Cherry Vaish
WIE Chairperson Sakshi Kumari
General Secretary Tushar Budhiraja
Joint Secretary Suyash Sharma
WIE Vice-Chairperson Komal Sharma
Technical Coordinator (Comp. Soc.) Abhishek Pandey
Technical Coordinator (Robex) Kanchan Tanwar
Graphic Designer Tarun Sharma
PR Head Abhishek Sharma
Editorial & Publication Head Yashaswini .S.M.
Program Coordinator Sandeep Shah
Program Coordinator Manash Khetan
Mailing Address:
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IEEE BKBIET Student Chapter
CSIR-CEERI Road, Pilani – 333 031
Rajasthan (INDIA)
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