UNIT 4

Overview of Digital Transformation. Block chain – Concepts and Industrial Applications,

Challenges in adopting Block chain. Artificial Intelligence- Machine Learning, Deep Learning
Singularity – Time Lines and Implication. Augmented Reality, Virtual Reality and Mixed
Reality and Applications. Internet of Things (IoT).

Block chain – Concepts (https://youtu.be/SSo_EIwHSd4)

 About Blockchain: Blockchain derives its name from the digital databases or ledgers
where information is stored as “blocks’’ that are coupled together forming “chains”.
o It offers a singular combination of permanent and tamper-evident record keeping,
real-time transaction transparency and auditability.
o An exact copy of the blockchain is available to each of the multiple
computers or users who are joined together in a network.
 Any new information added or altered via a new block is to be vetted and
approved by over half the total users.
 Significance of Blockchain:
o Blockchain technology can facilitate innovations across a range of processes and
applications requiring management, storage, retrieval and safety of vast and
important information.
o These include - management of information pertaining to financial transactions (as
in the case of cryptocurrencies), electoral voting, medical records, academic
lessons, property ownership records and professional testimonials.
o A decentralised framework like blockchain makes the system and the information
stored therein fraud-proof, transparent and credible.
 Blockchain and Digital Education:
o Fulfilling the Objectives of NEP 2020: The National Education Policy (NEP)
2020 calls for introducing multidisciplinary education where students would be able
to choose their own combination of major and minor subjects along with flexibility
in course duration.
 In this context, blockchain can help implement a multiple-entry-and-exit
structure.
o Displaying Skill Badges: Further, students can be assured of the quality of teachers
and educators as the technology could enable educators to display their certified
Skill Badges, allowing students to opt for courses in an informed manner.
 Moreover, the students, especially those in higher education and research, can
adopt Skill Badges to indicate their proficiencies.
 This would enable faculty to identify the right students for projects.
o Designing Scholarship Ecosystem: A blockchain-based ecosystem could also be
used to design a scholarship system incentivising students to maintain
consistency and achieve academic excellence.
 o Record-Keeping: It would be a secure system that ensures educational records
remain immutable.
 Blockchain can provide an excellent framework to manage student records
ranging from day-to-day information such as assignments, attendance and
extracurricular activities, to information about degrees and colleges they have
attended.
 These could be relied upon by prospective educational institutions and
recruiters, who can be provided access to relevant records.
o Monitoring Faculty Performance: The blockchain ledger would provide a time-
stamped and tamper-proof record of faculty performance - student evaluations,
number of students opting for their electives, research output and publications.
 These records could be linked to faculty appraisal systems, thereby ensuring
greater accountability.
o Learner-Centric Model: Using blockchain in education will lead to a truly
learner-centric model where learners are not just receivers but also the co-
creators and teachers are not just sending information one way but becoming more
participative.
CHALLENGES ASSOCIATED TO BLOCKCHAIN TECHNOLOGY

 Low Scalability: In reality, blockchains work fine for a small number of users. However,
when the user number increases on the network, the transitions take longer to process.
o As a result, the transactions cost higher than usual. It also restricts more users
on the network.
 Security Challenges: Blockchains are vulnerable to network attacks as they were not
originally designed for network protocols. There are challenges of insertion of malware
files and objectionable content as Blockchain services continue to grow.
o This raises issues of privacy violation, potentially illegal files, copyright
violations, malware etc.
 Interoperability: Interoperability is another sore point. It still is in its nascent stage in
the country and a lot needs to be done in many key areas.
 Immutability: One of the features of the technology is its immutability — that is, once
some data has been entered, it cannot be altered or deleted.
o It poses a challenge as it eliminates the possibility of modifying student records
for legitimate purposes.
 Lack of Technology Experts: In the current regulatory environment, Indian developers
do not have the ability to develop open blockchain solutions at scale.
o Blockchain professionals are migrating rapidly to countries with more friendly
regulations.
o As a result India’s ability to benefit from jobs, capital, local innovation and
positioning is all curtailed without the talent ecosystem in place.
 lockchain applications go far beyond cryptocurrency and bitcoin. With its ability to create more
transparency and fairness while also saving businesses time and money, the
technology is impacting a variety of sectors in ways that range from how contracts are enforced
to making government work more efficiently.
We've rounded up 34 examples of real-world blockchain use cases for this pragmatic yet
revolutionary technology. It's far from an exhaustive list, but they're already changing how we
do business.

13 PROMINENT BLOCKCHAIN APPLICATIONS TO KNOW

 Secure sharing of medical data
 NFT marketplaces
 Music royalties tracking
 Cross-border payments
 Real-time IoT operating systems
 Personal identity security
 Anti-money laundering tracking system
 Supply chain and logistics monitoring
 Voting mechanism
 Advertising insights
 Original content creation
 Cryptocurrency exchange
 Real estate processing platform

APPLICATION OF BLOCKCHAIN TECHNOLOGY

1. Money Transfer Use

Pioneered by Bitcoin, cryptocurrency transfer apps are exploding in popularity right now.
Blockchain is especially popular in finance for the money and time it can save financial
companies of all sizes.
By eliminating bureaucratic red tape, making ledger systems real-time and reducing third-party
fees, blockchain can save the largest banks $8-$12 billion a year, according to a recent article
by ComputerWorld. We’ll take a deeper dive into four companies using blockchain to
efficiently transfer money.

2. Algorand
Industry: Finance, Cryptocurrency, Cybersecurity
Location: Boston, MA
Blockchain application: Algorand is developing technology that reduces the gaps between
traditional and decentralized finance, implementing next-generation products and protocols to
make financial transactions more equitable for all. The company’s technology is enabled by a
set of Layer-1 blockchains to provide scalability, security, transaction finality, privacy, co-
chain and smart contract capabilities, with use cases ranging from securities and supply chains
to insurance, gaming, digital contracts and beyond.

3. Gemini
Industry: Cryptocurrency
Location: New York, NY
Blockchain application: Gemini is a licensed digital asset exchange and custodian that
facilitates regulated and secure buying, selling and storing of digital assets like Bitcoin and
Etherium. The company offers a range of products and services that allow crypto traders to
utilize their assets in the ways they best see fit, from credit cards that provide crypto rewards
to the Gemini Earn program that allows users to earn up to 7.4% interest on their wallets.

4. Chainalysis
Industry: Fintech, Cryptocurrency, Cybersecurity
Location: New York, New York
How it's using blockchain: Chainalysis builds tools to help financial institutions and
governments monitor the exchange of cryptocurrencies. The company’s due diligence software
monitors and detects fraudulent trading, laundering and compliance violations, and builds trust
in blockchain.

5. Circle
Industry: Fintech, Cryptocurrency
Location: Boston, Massachusetts
How it's using blockchain: Boston-based Circle oversees more than $2 billion a month in
cryptocurrency investments and exchanges between friends. Circle’s investment and money
transfer platform currently features seven different cryptocurrencies, including Bitcoin,
Monero and Zcash.

6. Chain.io
Industry: Fintech, Cloud
Location: San Francisco, California
How it's using blockchain: Chain builds cloud blockchain infrastructures for financial
services. The San Francisco company’s cryptographic ledgers help financial institutions safely
and efficiently handle the transfer of cryptocurrencies.

Smart Contracts Use Cases

Smart contracts are like regular contracts except the rules of the contract are enforced in real-
time on a blockchain, which eliminates the middleman and adds levels of accountability for all
parties involved in a way not possible with traditional agreements. This saves businesses time
and money, while also ensuring compliance from everyone involved.
Blockchain-based contracts are becoming more and more popular as sectors like government,
healthcare and the real estate industry discover the benefits. Below are a few examples of how
companies are using blockchain to make contracts smarter.
1. BurstIQ
Industry: Healthcare
Location: Denver, Colorado
How it's using blockchain: BurstIQ’s big data blockchain contracts help patients and doctors
securely transfer sensitive medical information. The smart contracts establish the parameters
of what data can be shared and even displays details of personalized health plans for each
patient.

2. Mediachain
Industry: Music
Location: New York, New York
How it's using blockchain: Mediachain uses smart contracts to get musicians the money they
deserve. By entering into a decentralized, transparent contract, artists can agree to higher
royalties and actually get paid in full and on time. Streaming giant Spotify acquired
Mediachain in April 2017.

3. Propy Inc
Industry: Real Estate
Location: Palo Alto, California
How it's using blockchain: Propy is a global real estate marketplace with a decentralized title
registry system. The online marketplace uses blockchain to make title issuance instantaneous
and even offers properties that can be purchased using cryptocurrency.

Internet of Things Use Cases

The Internet of Things (IoT) is the next logical boom in blockchain applications. IoT has
millions of applications and many safety concerns, and an increase in IoT products
means better chances for hackers to steal your data on everything from an Amazon Alexa to
a smart thermostat.
Blockchain-infused IoT adds a higher level of security to prevent data breaches by utilizing
transparency and virtual incorruptibility of the technology to keep things "smart." Below are a
few US companies using blockchain to make the Internet of Things safer and smarter.
1. Filament!
Industry: Internet of Things, Hardware, Software
Location: Reno, Nevada
How it's using blockchain: Filament creates software and microchip hardware that
lets connected devices operate on blockchain. The Reno-based company’s products encrypt
ledger data, distribute real-time information to other blockchain-connected machines and allow
for the monetization of those machines based on timestamps.

2. HYPR
Industry: Internet of Things, Cybersecurity
Location: New York, New York
How it's using blockchain: HYPR thwarts cybersecurity risks in IoT devices with its
decentralized credential solutions. By taking passwords off a centralized server, while
using biometric and password-free solutions, the company makes IoT devices virtually
unhackable.

3. Xage Security
Industry: Internet of Things, Cybersecurity
Location: Palo Alto, California
Blockchain Application: Xage is the world’s first blockchain-enabled cybersecurity platform
for IoT companies. The technology manages billions of devices at once and can even self-
diagnose and heal possible breaches. Xage is primarily used by IoT companies in the
transportation, energy and manufacturing industries.

Personal Identity Security Use Cases

According to identity theft expert LifeLock, more than 16 million Americans complained of
identity fraud and theft in 2017 alone, with an identity being stolen every two seconds. Fraud
on this scale can occur via everything from forged documents to hacking into personal files.
By keeping social security numbers, birth certificates, birth dates and other sensitive
information on a decentralized blockchain ledger, the government could see a drastic drop in
identity theft claims. Here are a few blockchain-based enterprises at the forefront of identity
security.
1. Ligero
Industry: Data, fintech
Location: Rochester, NY
Blockchain application: Ligero provides lightweight, scalable protocols for secure multiparty
computation and zero-knowledge proofs, providing a highly capable platform for facilitating
decentralized collaboration both on and off blockchain. The platform makes it possible to
complete confidential transactions, private smart contracts, secure auctions for decentralized
exchanges and enable verifiable machine learning capabilities, and is led by a team of capital
and cryptography experts with decades of experience.

2. Illinois Blockchain Initiative

Industry: Government, Technology
Location: Springfield, Illinois
Blockchain Application: Illinois is at the forefront of experimental blockchain in government
with the Illinois Blockchain Initiative. The state-funded initiative has already put in place
measures to use a distributed blockchain ledger to enhance the security of birth certificates,
death certificates, voter registration cards, social security numbers and much more.

3. Civic
Industry: Identity Security, Fintech
Location: Palo Alto, California
How it's using blockchain: Civic is a blockchain-based ecosystem that gives individuals
insights into who has their information. The company’s users enter into smart contracts, where
they decide who can share their personal information and how much. If the contract is broken
or an unauthorized source tries to access private data, the individual is immediately alerted.

4. Evernym, Inc.
Industry: IT, Software
Location: Salt Lake City, Utah
How it's using blockchain: Evernym’s Sovrin identity ecosystem lets individuals manage
their identities all over the web using distributed ledger technology. Sovrin stores private
information, acts as a communication medium between the individual and entities wanting
private information, and verifies information as true in real-time.

5. Ocular
Industry: Cybersecurity, Fintech
Location: Los Angeles, California
How it's using blockchain: Ocular’s anti-money laundering compliance platform leverages
blockchain-enabled security to ensure data cannot be manipulated. The technology uses
biometric systems to scan the faces of individuals applying for passports, driver’s licenses and
other government issued IDs. By viewing biometric systems on blockchains, governments can
more easily catch identity thieves foraging fake passports, certificates and IDs from other
countries.
Healthcare Use
Blockchain in healthcare, though early in its adoption, is already showing some promise. In
fact, early blockchain solutions have shown the potential to reduce healthcare costs, improve
access to information across stakeholders and streamline businesses processes. An advanced
system for collecting and sharing private information could be just what the doctor ordered to
make sure that an already bloated sector can trim down exorbitant costs.
1.WholeCare
Industry: Healthcare, Data
Location: Baltimore, MD
Blockchain application: For both health professionals and families providing
care, WholeCare simplifies and streamlines the influx of information necessary to properly
manage and provide care for those who need it when they need it most. The WholeCare
platform brings care plan information, medication protocols, appointment creation and high
quality resources into an easily distillable platform that allows individuals, support systems and
multi-care facilities to better understand how to provide the nuanced care possible. Built on a
blockchain network to remain as secure as possible, WholeCare provides HIPAA-compliant
record keeping so all people involved in the care process can maintain peace of mind.

2. Patientory
Industry: Healthcare, Cybersecurity, Recordkeeping
Location: Atlanta, Georgia
How it’s using blockchain: Patientory is an all-in-one medical record system for patients and
doctors alike, backed by blockchain technology. One of the biggest issues with healthcare is
the fragmentation of data across different providers and clinics. With Patientory, a patient’s
medical history, records, current providers and mostly everything else a medical doctor would
need to know is constantly and securely accessible. The blockchain-platform allows for patients
and doctors to stay in constant communication, while a steady pipeline of medical data allows
for any medical professional to quickly and safely diagnose patients based on a clearer medical
history.

3.Nebula Genomics
Industry: Healthcare, Genomics, Data Privacy
Location: San Francisco
How it’s using blockchain: Nebula Genomics is on a mission to understand the human
genome and to make personal genomics more affordable and accessible. The company’s
whole-genome DNA sequencing tests are the only tests available that decode 100% of an
individual’s DNA. All information gathered from an individual test is totally anonymous and
kept private through a blockchain-based encryption, so a user's data can never be identified or
stole.

4.MEDICALCHAIN
Industry: Healthcare, Data Privacy
Location: London
How it’s using blockchain: Medicalchain’s cooperative blockchain platform allows for an
easier and more secure flow of information that helps both the patient and medical
professionals. With Medicalchain, doctors no longer have to wait on insurance information.
The blockchain can automatically verify whether a patient has insurance and is covered.
Additionally, drug and clinical trials can easily identify top candidates through a blockchain-
based portal that safely shows patient medical records and identifies prime contenders for
different trials.
Logistics Use
A major complaint in the shipping industry is the lack of communication and transparency due
to the large number of logistics companies crowding the space. According to a joint study by
Accenture and logistics giant DHL, there are more than 500,000 shipping companies in the
US alone, causing data siloing and transparency issues. The report goes on to say blockchain
can solve many of the problems plaguing logistics and supply chain management.
The groundbreaking study argues that blockchain enables data transparency by revealing a
single source of truth. By acknowledging data sources, blockchain can build greater trust within
the industry. The technology can also make the logistics process leaner and more automated,
potentially saving the industry billions of dollars a year. Blockchain is not only safe, but a cost-
effective solution for the logistics industry. Here are some companies on the cutting-edge of
logistics blockchain technology.
1.DHL
Industry: Logistics, Supply Chain
Location: Plantation, Florida (US headquarters)
How it's using blockchain: Shipping giant DHL is at the forefront of blockchain-backed
logistics, using it to keep a digital ledger of shipments and maintain integrity of transactions.
DHL has a major presence in the US and is one of the largest shipping companies to embrace
blockchain.

2.Block Array
Industry: Logistics, Supply Chain
Location: Chattanooga, Tennessee
How it's using blockchain: Block Array introduced the first “Bill of Lading” to run on
blockchain. The logistics operation platform helps businesses safely monitor the progress of
their shipped goods, house information on drivers and materials, and manage payments. Block
Array also features smart contract processing and secure document management.

3.Maersk
Industry: Logistics, Supply Chain
Location: Florham Park, New Jersey (US headquarters)
How it's using blockchain: Based in Denmark, but with offices all over the US, shipping
giant Maersk has teamed up with tech giant IBM to infuse blockchain into global trade. The
two companies will use blockchain to better understand supply chain and track goods digitally
across international borders in real-time.

4.ShipChain
Industry: Logistics,SupplyChain
Location: Los Angeles, California
How it's using blockchain: ShipChain is a fully integrated blockchain system serving the end-
to-end shipping process. From the moment the shipment leaves the facility to the time it arrives
at its destination, the logistics ecosystem safely tracks and documents every move to create a
transparent ledger. Based in Los Angeles, ShipChain is aiming to modernize the $8.1 trillion
supply chain market using blockchain.

5.Non-Fungible Tokens (NFTs)

Non-Fungible Tokens (NFTs) have been the hottest blockchain application since
cryptocurrency. 2021 brought a rise in these digital items that are currently taking the world by
storm. NFTs are simply digital items, like music, art, GIFs, videos, etc., that are sold on a
blockchain, ensuring that a sole owner can claim full rights to it. Thanks to blockchain
technology, consumers can now claim sole ownership over some of the most desirable digital
assets out there.
Remember the 2011 meme Nyan Cat? That memorable GIF just sold for $600,000 in
ethereum on the blockchain. Before October, the digital artist “Beeple” never sold anything
over $100. In March 2020, his digital work The First 5000 Days sold for an astounding $69
million. NFTs give buyers the chance to own digital moments, art, and culture that will outlive
us all. Below are a few examples of companies taking advantage of the NFT wave.

6.Candy
Industry: NFTs
Location: New York City, NY
Blockchain application: Candy operates a cutting-edge NFT ecosystem that allows fans and
collectors to interact with top sports, art, music and cultural icons in the form of official licensed
digital collectibles, opening up the doors to a secure marketplace where users can buy, sell and
trade NFTs to maximize their investment. The company works directly with athletes, artists
and content owners to bring their NFT projects to life in breathtaking ways and is currently
producing a series highlighting Major League Baseball’s 30 stadiums.

7.Dapper Labs
Industry: Sports, NFTs
Location: Remote-First
How it’s using blockchain: Dapper Labs is one of the first companies to explode thanks to the
NFT craze. They’ve partnered with the NBA to bring about “NBA Top Shot”, a NFT
marketplace where buyers have the opportunity to become owners of digital media from their
favorite NBA players or teams. Buyers have the opportunity to own collectible moments that
range from a Lebron James highlight reel dunk to an Anthony Davis blocked shot GIF. To date,
Top Shot has already produced more than $500 million in sales.

8.Pixura
Industry: NFTs, Creative
Location: Remote-First
How it’s using blockchain: Pixura is a platform that helps non-technical users to create, track
and exchange digital NFTs on the blockchain. The company helps everyone from game studios
to individual musicians and artists to create their own digital assets in just minutes. The
company also created the site SuperRare, which has become one of the go-to sites for buying
and selling digital art in the NFT era.

Government Use
One of the most surprising applications for blockchain can be in the form of improving
government. As mentioned previously, some state governments like Illinois are already using
the technology to secure government documents, but blockchain can also improve bureaucratic
efficiency, accountability and reduce massive financial burdens. Blockchain has the potential
to cut through millions of hours of red tape every year, hold public officials accountable
through smart contracts and provide transparency by recording a public record of all activity,
according to the New York Times.
Blockchain could also revolutionize our elections. Currently, voter apathy in the US is at an
all-time high, with just over 58 percent turning out in the 2016 presidential election, while only
36.4 percent of the voting-eligible public showed up for \the 2014 midterm elections, according
to PBS. Blockchain-based voting could improve civic engagement by providing a level of
security and incorruptibility that allows voting to be done on mobile devices.
The following companies and government entities are a few examples of how blockchain
applications are improving government.
1. VOATZ
Industry: Government, Cybersecurity, Politics
Location: Boston, Massachusetts
How it's using blockchain: Voatz is a mobile voting platform that runs on blockchain. The
encrypted biometric security system makes it secure to vote on a mobile device from anywhere
in the world without fear of hacking or data corruption. West Virginia is one of the first states
to use the company’s platform to collect votes from eligible service people and travelers abroad
during elections.

2.State of Delaware
Industry: Government
Location: Dover, Delaware
How it's using blockchain: Similar to the Illinois Blockchain Initiative, the State
of Delaware is also launching their own initiative to explore the benefits of blockchain in
business and government. So far, the state has mostly focused its efforts into archiving public
documents and safely securing private records. The next step in Delaware’s initiative is to
begin implementing smart contracts between the government and corporations.

3.Follow My Vote
Industry: Government, Software
Location: Blacksburg, Virginia
How it's using blockchain: Follow My Vote is a secure online voting platform using an open-
source virtual blockchain ballot box. The technology decreases spending on physical ballots
and can be accessed via any device. Follow My Vote implements the end-to-end tools that
elections need in order to provide total safety and confidence in the voting process.

Media Use
Many of the current problems in media deal with data privacy, royalty payments and piracy of
intellectual property. According to a study by Deloitte, the digitization of media has caused
widespread sharing of content that infringes on copyrights. Deloitte believes blockchain can
give the industry a much needed facelift when it comes to data rights, piracy and payments.
Blockchain’s strength in the media industry is its ability to prevent a digital asset, such as an
mp3 file, from existing in multiple places. It can be shared and distributed while also preserving
ownership, making piracy virtually impossible through a transparent ledger system.
Additionally, blockchain can maintain data integrity, allowing advertising agencies to target
the right customers, and musicians to receive proper royalties for original works. The
following US-based companies are helping grow the popularity of blockchain in our media.
1.MadHive
Industry: Digital Media
Location: New York, New York
How it's using blockchain: MadHive is a blockchain-based advertising and data solution for
digital marketers. The platform tracks, stores and generates reports on customer activity, saving
all the data to a private blockchain. MadHive’s targeted audience reports and real-time data
monitoring give advertisers insights into their customers without compromising data privacy.

2.STEEM
Industry: Social Media
Location: Austin, Texas
How it's using blockchain: Steem is a social media platform backed by blockchain.
Its “Proof-of-Brain” community uses tokens as incentives, encouraging people to create
original content. The amount of tokens distributed is based on the number of upvotes each
article receives. Steem has payed over $40 million in tokens to creators.

3.Open Music Initiative

Industry: Music, Non-profit
Location: Boston, Massachusetts
How it's using blockchain: Open Music Initiative is a Boston-based nonprofit creating an
open source protocol to identify original creators and music rights holders. By trusting their
music rights data to blockchain, the nonprofit is making it easier for artists and musicians to be
recognized for their work and paid correctly. The initiative has backing from from virtually all
areas of the music industry, including producers and radio stations, as well as media giants like
Netflix and Spotify.

Artificial Intelligence –

What is artificial intelligence?

While a number of definitions of artificial intelligence (AI) have surfaced over the last few
decades, John McCarthy offers the following definition in this 2004 paper (PDF, 106 KB) (link
resides outside IBM), " It is the science and engineering of making intelligent machines,
especially intelligent computer programs. It is related to the similar task of using computers to
understand human intelligence, but AI does not have to confine itself to methods that are
biologically observable."

However, decades before this definition, the birth of the artificial intelligence conversation was
denoted by Alan Turing's seminal work, "Computing Machinery and Intelligence" (PDF, 89.8
KB)(link resides outside of IBM), which was published in 1950. In this paper, Turing, often
referred to as the "father of computer science", asks the following question, "Can machines
think?" From there, he offers a test, now famously known as the "Turing Test", where a human
interrogator would try to distinguish between a computer and human text response. While this
test has undergone much scrutiny since its publish, it remains an important part of the history
of AI as well as an ongoing concept within philosophy as it utilizes ideas around linguistics.

Stuart Russell and Peter Norvig then proceeded to publish, Artificial Intelligence: A Modern
Approach (link resides outside IBM), becoming one of the leading textbooks in the study of
AI. In it, they delve into four potential goals or definitions of AI, which differentiates computer
systems on the basis of rationality and thinking vs. acting:

Human approach:

 Systems that think like humans

 Systems that act like humans

Ideal approach:
  Systems that think rationally
 Systems that act rationally

Alan Turing’s definition would have fallen under the category of “systems that act like
humans.”

At its simplest form, artificial intelligence is a field, which combines computer science and
robust datasets, to enable problem-solving. It also encompasses sub-fields of machine learning
and deep learning, which are frequently mentioned in conjunction with artificial intelligence.
These disciplines are comprised of AI algorithms which seek to create expert systems which
make predictions or classifications based on input data.

Today, a lot of hype still surrounds AI development, which is expected of any new emerging
technology in the market. As noted in Gartner’s hype cycle (link resides outside IBM), product
innovations like, self-driving cars and personal assistants, follow “a typical progression of
innovation, from overenthusiasm through a period of disillusionment to an eventual
understanding of the innovation’s relevance and role in a market or domain.” As Lex Fridman
notes here (link resides outside IBM) in his MIT lecture in 2019, we are at the peak of inflated
expectations, approaching the trough of disillusionment.

As conversations emerge around the ethics of AI, we can begin to see the initial glimpses of
the trough of disillusionment. To read more on where IBM stands within the conversation
around AI ethics, read more here.

Types of artificial intelligence—weak AI vs. strong AI

1. Weak AI—also called Narrow AI or Artificial Narrow Intelligence (ANI)—

It is AI trained and focused to perform specific tasks. Weak AI drives most of the AI that
surrounds us today. ‘Narrow’ might be a more accurate descriptor for this type of AI as it is
anything but weak; it enables some very robust applications, such as Apple's Siri, Amazon's
Alexa, IBM Watson, and autonomous vehicles.

2. Strong AI is made up of Artificial General Intelligence (AGI) and Artificial

Super Intelligence (ASI).

Artificial general intelligence (AGI), or general AI, is a theoretical form of AI where a machine
would have an intelligence equalled to humans; it would have a self-aware consciousness that
has the ability to solve problems, learn, and plan for the future. Artificial Super Intelligence
(ASI)—also known as superintelligence—would surpass the intelligence and ability of the
human brain. While strong AI is still entirely theoretical with no practical examples in use
today, that doesn't mean AI researchers aren't also exploring its development. In the meantime,
the best examples of ASI might be from science fiction, such as HAL, the superhuman, rogue
computer assistant in 2001: A Space Odyssey.

DEEP LEARNING VS. MACHINE LEARNING

Since deep learning and machine learning tend to be used interchangeably, it’s worth noting
the nuances between the two. As mentioned above, both deep learning and machine learning
are sub-fields of artificial intelligence, and deep learning is actually a sub-field of machine
learning.

Deep learning is actually comprised of neural networks. “Deep” in deep learning refers to a
neural network comprised of more than three layers—which would be inclusive of the inputs
and the output—can be considered a deep learning algorithm. This is generally represented
using the following diagram:

The way in which deep learning and machine learning differ is in how each algorithm learns.
Deep learning automates much of the feature extraction piece of the process, eliminating some
of the manual human intervention required and enabling the use of larger data sets. You can
think of deep learning as "scalable machine learning" as Lex Fridman noted in same MIT
lecture from above. Classical, or "non-deep", machine learning is more dependent on human
intervention to learn. Human experts determine the hierarchy of features to understand the
differences between data inputs, usually requiring more structured data to learn.

"Deep" machine learning can leverage labelled datasets, also known as supervised learning, to
inform its algorithm, but it doesn’t necessarily require a labelled dataset. It can ingest
unstructured data in its raw form (e.g. text, images), and it can automatically determine the
hierarchy of features which distinguish different categories of data from one another. Unlike
machine learning, it doesn't require human intervention to process data, allowing us to scale
machine learning in more interesting ways.
Artificial intelligence applications

There are numerous, real-world applications of AI systems today. Below are some of the most
common examples:

 Speech Recognition: It is also known as automatic speech recognition (ASR),

computer speech recognition, or speech-to-text, and it is a capability which uses
natural language processing (NLP) to process human speech into a written
format. Many mobile devices incorporate speech recognition into their systems to
conduct voice search—e.g. Siri—or provide more accessibility around texting.
 Customer Service: Online chatbots are replacing human agents along the customer
journey. They answer frequently asked questions (FAQs) around topics, like shipping,
or provide personalized advice, cross-selling products or suggesting sizes for users,
changing the way we think about customer engagement across websites and social
media platforms. Examples include messaging bots on e-commerce sites with virtual
agents, messaging apps, such as Slack and Facebook Messenger, and tasks usually
done by virtual assistants and voice assistants.
 Computer Vision: This AI technology enables computers and systems to derive
meaningful information from digital images, videos and other visual inputs, and based
on those inputs, it can take action. This ability to provide recommendations
distinguishes it from image recognition tasks. Powered by convolutional neural
networks, computer vision has applications within photo tagging in social media,
radiology imaging in healthcare, and self-driving cars within the automotive
industry.
 Recommendation Engines: Using past consumption behavior data, AI algorithms
can help to discover data trends that can be used to develop more effective cross-
selling strategies. This is used to make relevant add-on recommendations to customers
during the checkout process for online retailers.
 Automated stock trading: Designed to optimize stock portfolios, AI-driven high-
frequency trading platforms make thousands or even millions of trades per day
without human intervention.

Industrial Application of AI:

Artificial Intelligence (AI) is a key driver of the Fourth Industrial Revolution. Its effect can be
seen in homes, businesses, schools and even public spaces - enabling advances in autonomous
driving, energy efficiency, and even facilitating better care for the young and elderly. AI holds
the promise of solving some of society’s most pressing issues, but also presents challenges
such as inscrutable “black box” algorithms, unethical use of data and potential job
displacement.

As rapid advances in machine learning (ML) increase the scope and scale of AI’s deployment
across all aspects of daily life, multistakeholder collaboration is required to optimize
accountability, transparency, privacy and impartiality to create trust.

 https://www.weforum.org/videos/5-surprising-things-that-rely-on-artificial-
intelligence?trk=organization-update-content_share-embed-video_share-article
 https://www.weforum.org/videos/how-ai-is-changing-therapy
History of artificial intelligence: Key dates and names

The idea of 'a machine that thinks' dates back to ancient Greece. But since the advent of
electronic computing (and relative to some of the topics discussed in this article) important
events and milestones in the evolution of artificial intelligence include the following:

 1950: Alan Turing publishes Computing Machinery and Intelligence. In the paper,
Turing—famous for breaking the Nazi's ENIGMA code during WWII—proposes to
answer the question 'can machines think?' and introduces the Turing Test to determine
if a computer can demonstrate the same intelligence (or the results of the same
intelligence) as a human. The value of the Turing test has been debated ever since.
 1956: John McCarthy coins the term 'artificial intelligence' at the first-ever AI
conference at Dartmouth College. (McCarthy would go on to invent the Lisp
language.) Later that year, Allen Newell, J.C. Shaw, and Herbert Simon create the
Logic Theorist, the first-ever running AI software program.
 1967: Frank Rosenblatt builds the Mark 1 Perceptron, the first computer based on a
neural network that 'learned' though trial and error. Just a year later, Marvin Minsky
and Seymour Papert publish a book titled Perceptrons, which becomes both the
landmark work on neural networks and, at least for a while, an argument against future
neural network research projects.
 1980s: Neural networks which use a backpropagation algorithm to train itself become
widely used in AI applications.
 1997: IBM's Deep Blue beats then world chess champion Garry Kasparov, in a chess
match (and rematch).
 2011: IBM Watson beats champions Ken Jennings and Brad Rutter at Jeopardy!
 2015: Baidu's Minwa supercomputer uses a special kind of deep neural network
called a convolutional neural network to identify and categorize images with a higher
rate of accuracy than the average human.
 2016: DeepMind's AlphaGo program, powered by a deep neural network, beats Lee
Sodol, the world champion Go player, in a five-game match. The victory is significant
given the huge number of possible moves as the game progresses (over 14.5 trillion
after just four moves!). Later, Google purchased DeepMind for a reported $400
million.

Singularity – Time Lines and Implication

The technological singularity—or simply the singularity[1]—is a hypothetical point in time
at which technological growth becomes uncontrollable and irreversible, resulting in
unforeseeable changes to human civilization.[2][3] According to the most popular version of the
singularity hypothesis, called intelligence explosion, an upgradable intelligent agent will
eventually enter a "runaway reaction" of self-improvement cycles, each new and more
intelligent generation appearing more and more rapidly, causing an "explosion" in intelligence
and resulting in a powerful superintelligence that qualitatively far surpasses all human
intelligence.
The first person to use the concept of a "singularity" in the technological context was John von
Neumann.[4] Stanislaw Ulam reports a discussion with von Neumann "centered on
the accelerating progress of technology and changes in the mode of human life, which gives
the appearance of approaching some essential singularity in the history of the race beyond
which human affairs, as we know them, could not continue".[5] Subsequent authors have echoed
this viewpoint.[3][6]
J. Good's "intelligence explosion" model predicts that a future superintelligence will trigger
a singularity.

Intelligence explosion is a possible outcome of humanity building artificial general

intelligence (AGI). AGI may be capable of recursive self-improvement, leading to the rapid
emergence of artificial superintelligence (ASI), the limits of which are unknown, shortly after
technological singularity is achieved.

Timelines and Implication: In a recent survey the median estimate among leading computer
scientists reported a 50% chance that this technology would arrive within 45 years.
Researchers predict AI will outperform humans in many activities in the next ten years, such
as translating languages (by 2024), writing high-school essays (by 2026), driving a truck (by
2027), working in retail (by 2031), writing a bestselling book (by 2049), and working as a
surgeon (by 2053). Researchers believe there is a 50% chance of AI outperforming humans in
all tasks in 45 years and of automating all human jobs in 120 years, with Asian respondents
expecting these dates much sooner than North Americans. These results will inform discussion
amongst researchers and policymakers about anticipating and managing trends in AI.
WHAT’S THE DIFFERENCE BETWEEN A R, VR, AND MR?

 Augmented reality (AR) adds digital elements to a live view often by using the camera
on a smartphone. Examples of augmented reality experiences include Snapchat lenses
and the game Pokemon Go.
AR let us see the real-life environment right in front of us—trees swaying in the park, dogs
chasing balls, kids playing soccer—with a digital augmentation overlaid on it.
For example, a pterodactyl might be seen landing in the trees, the dogs could be mingling with
their cartoon counterparts, and the kids could be seen kicking past an alien spacecraft on their
way to score a goal.
With advances in AR technology, these examples are not that different from what might already
be available for your smartphone. Augmented reality is, in fact, readily available and being
used in a myriad of ways including as Snapchat lenses, in apps that help you find your car
in a crowded parking lot, and in variety of shopping apps that let you try on clothes
without even leaving home.
Perhaps the most famous example of AR technology is the mobile app Pokemon Go, which
was released in 2016 and quickly became an inescapable sensation. In the game, players locate
and capture Pokemon characters that pop up in the real world—on your sidewalk, in a fountain,
even in your own bathroom.
Games aside, there are as many uses for AR in our everyday lives as there are Pikachu on the
loose in Pokemon GO. Here are just a few examples:
 Enhanced navigation systems use augmented reality to superimpose a route over the live view
of the road.
 During football games, broadcasters use AR to draw lines on the field to illustrate and analyze
plays.
 Furniture and housewares giant IKEA offers an AR app (called IKEA Place) that lets you see
how a piece of furniture will look and fit in your space.
 Military fighter pilots see an AR projection of their altitude, speed, and other data on their
helmet visor, which means they don’t need to waste focus by glancing down to see them.
 Neurosurgeons sometimes use an AR projection of a 3-D brain to aid them in surgeries.
 At historical sites like Pompeii in Italy, AR can project views of ancient civilizations over
today’s ruins, bringing the past to life.
 Ground crew at Singapore’s airport wear AR glasses to see information about cargo
containers, speeding up loading times

 Virtual reality (VR) implies a complete immersion experience that shuts out the
physical world. Using VR devices such as HTC Vive, Oculus Rift or Google
Cardboard, users can be transported into a number of real-world and imagined
environments such as the middle of a squawking penguin colony or even the back of a
dragon.
 In a Mixed Reality (MR) experience, which combines elements of both AR and VR,
real-world and digital objects interact. Mixed reality technology is just now starting to
take off with Microsoft’s HoloLens one of the most notable early mixed reality
apparatuses. (https://youtu.be/eqFqtAJMtYE)
 Extended Reality (XR) is an umbrella term that covers all of the various technologies
that enhance our senses, whether they’re providing additional information about the
actual world or creating totally unreal, simulated worlds for us to experience. It includes
Virtual Reality (VR), Augmented Reality (AR) and Mixed Reality (MR) technologies.
(https://youtu.be/lbJ-IKPn2l8)

The border between the virtual and real world continues to break down, providing breathtaking
experiences that, a short time ago, could only be found in the imagination of sci-fi writers.

Virtual Reality (VR) has been the “next big thing” for several years, but its time has finally
come as a way to generate realistic images, sounds, and other sensations that put you smack in
the middle of a spectacular imaginary world. Augmented Reality (AR), which adds virtual stuff
to your real world environment, is contributing to the buzz, and both technologies should
become a big part of our future. With Mixed Reality (MR), you can play a virtual video game,
grab your real world water bottle, and smack an imaginary character from the game with the
bottle. Imagination and reality have never been so intermingled.

So much is happening so fast that the differences between VR, AR, and MR can seem a little
puzzling at first. Each of these spellbinding technologies are accessible to almost everyone, but
before you throw down your hard-earned money for the latest head-mounted display, let’s take
a closer look at what you’ll need for an amazing VR, AR, or MR experience.

The History and Future of Virtual Reality

We’ve been trying to capture “Virtual Reality” for much longer than just the past five to ten
years. There were popular peer-through toys in the 1950s and enclosed flight simulators
debuted in the 1960s, but the idea of VR goes back even further.

As early as the 1930s, science fiction writers, inventors, and tinkerers dreamt of an environment
where you could escape from reality via art and machines. We were weighing questions about
Virtual Reality vs. Augmented Reality vs. Mixed Reality long before we had the technology to
make them possible.

Technology has caught up to fiction, and market researchers predict rapid growth for the VR
industry.

VR and AR Meet MR
First things first, let’s define the terminology. Virtual Reality can be used as an umbrella term
to describe other technologies similar to, but different from, an actual Virtual Reality
experience. But what's the difference between Augmented Reality and Mixed Reality? Here
are some more details:

Virtual Reality
VR is the most widely known of these technologies. It is fully immersive, which tricks your
senses into thinking you’re in a different environment or world apart from the real world.
Using a head-mounted display (HMD) or headset, you’ll experience a computer-generated
world of imagery and sounds in which you can manipulate objects and move around using
haptic controllers while tethered to a console or PC.

Augmented Reality
AR overlays digital information on real-world elements. Pokémon GO* is among the best-
known examples. Augmented reality keeps the real world central but enhances it with other
digital details, layering new strata of perception, and supplementing your reality or
environment.

Mixed Reality
MR brings together real world and digital elements. In mixed reality, you interact with and
manipulate both physical and virtual items and environments, using next-generation sensing
and imaging technologies. Mixed Reality allows you to see and immerse yourself in the
world around you even as you interact with a virtual environment using your own hands—all
without ever removing your headset. It provides the ability to have one foot (or hand) in the
real world, and the other in an imaginary place, breaking down basic concepts between real
and imaginary, offering an experience that can change the way you game and work today.
Using Virtual Reality Technologies
From gaming, to movies, to medicine, the uses for Virtual Reality, Augmented Reality, and
Mixed Reality are expanding.

 Healthcare—For training, such as for surgical simulations

 Film and TV—For movies and shows to create unique experiences
 Virtual travel—For virtual trips to an art museum—or another planet—all from home
 Professional sports—For training programs like STRIVR to help pro and amateur
athletes
 Gaming—For over 1,000 games already available, from first-person shooters to
strategy games to role-playing adventures

What You’ll Need: Headsets

There are many, many VR headsets available, all with varying performance levels and prices.
Entry-level gear, such as Google Cardboard*, uses your mobile phone as the screen, whereas
PC-operated devices, like the HTC Vive* or Oculus Rift*, are immersive—providing a
premium VR environment. Microsoft has recently announced their Windows* 10 Mixed
Reality platform that initially uses fully immersive headsets offered by Acer, Asus, Dell, HP,
Lenovo, and Samsung.

Some AR headsets are available on the market today, with more rumored to be coming in the
future. The Microsoft Hololens*, Google Glass*, and the Meta 2* headset are great
examples.

Every PC-connected HMD (head mounted display) will have different system requirements,
so if you’re buying a new Virtual Reality headset, make sure you check with the HMD
vendor for their recommended and minimum system requirements.

What You’ll Need: Computers

If you are looking for a new computer and you’re interested in VR, you’ll need something
that can handle heavy loads. When it comes to high-end desktops or laptops for Virtual
Reality (and other advanced tasks like gaming or video editing), the CPU, GPU, and memory
are the most critical components.

Without these high-performing components working in sync, you could have a pretty
miserable experience. A powerful system will ensure that you’ll have fun as you lean in,
stand up, or walk around. VR that lags makes it impossible for the virtual world to respond as
you expect, which can lead to more than just disappointment; it increases the risk of motion
sickness.

A high-end processor assists in positional tracking and controls how real and immersive your
virtual environment will be, so you'll enjoy a deeper experience in a higher-fidelity
environment. For a great VR experience, consider the latest generation Intel Core™ i7
processor.

A discrete graphics processing unit (GPU) is recommended, or in the case of Oculus Rift*,
HTC Vive*, and Windows Mixed Reality Ultra*, it is required. The GPU is responsible for
rendering the high resolution, immersive images needed for VR. Oculus, HTC,
and Microsoft all have profiler tools that you can download from their websites, and you can
use to run on your PC to determine if it meets the minimum requirements for their VR
headsets.
Choose Your Experience
New VR and AR technologies and products continue to come to market, making new
environments accessible to the masses. Virtual, Augmented, Mixed—the choice for a new
reality is up to you. Let your imagination, and your readiness to try new gear, enhance your
experience!

Key VR Terms to Know

Use this chart to learn more VR terms and definitions.

Term Description Why It Matters

Frames Frequency at which a system Without a high and constant frame rate
per can display consecutive (greater than 60 FPS), the motion won’t
second images, or frames look right, and you could even feel sick
(FPS)

Field of The angle of the observable If the window of view is too narrow, you
view world that can be seen could end up making unnatural head
rotations

Degrees The number of directions More DoFs allow you to move more
of that an object can move or naturally in VR
Freedom rotate. The six degrees of
(DoF) freedom are pitch, roll, yaw,
left and right, forward and
backward, up and down

Latency The amount of time it takes a Latency is critical when it comes to the
system to react/respond to presence inside Virtual Reality—if the
movements or commands system doesn’t respond instantly, it
doesn’t feel real.

Internet of Things (IoT)

The Internet of Things (IoT) describes the network of physical objects—“things”—that are
embedded with sensors, software, and other technologies for the purpose of connecting and
exchanging data with other devices and systems over the internet. These devices range from
ordinary household objects to sophisticated industrial tools. With more than 7 billion connected
IoT devices today, experts are expecting this number to grow to 10 billion by 2020 and 22
billion by 2025. Oracle has a network of device partners.
Example: IoT intelligent applications
 Why is Internet of Things (IoT) so important?
Over the past few years, IoT has become one of the most important technologies of the 21st
century. Now that we can connect everyday objects—kitchen appliances, cars, thermostats,
baby monitors—to the internet via embedded devices, seamless communication is possible
between people, processes, and things.

By means of low-cost computing, the cloud, big data, analytics, and mobile technologies,
physical things can share and collect data with minimal human intervention. In this hyper
connected world, digital systems can record, monitor, and adjust each interaction between
connected things. The physical world meets the digital world—and they cooperate.

What technologies have made IoT possible?

While the idea of IoT has been in existence for a long time, a collection of recent advances in
a number of different technologies has made it practical.

 Access to low-cost, low-power sensor technology. Affordable and reliable sensors are
making IoT technology possible for more manufacturers.
 Connectivity. A host of network protocols for the internet has made it easy to connect
sensors to the cloud and to other “things” for efficient data transfer.
 Cloud computing platforms. The increase in the availability of cloud platforms enables
both businesses and consumers to access the infrastructure they need to scale up without
actually having to manage it all.
 Machine learning and analytics. With advances in machine learning and analytics, along
with access to varied and vast amounts of data stored in the cloud, businesses can gather
insights faster and more easily. The emergence of these allied technologies continues to
push the boundaries of IoT and the data produced by IoT also feeds these technologies.
 Conversational artificial intelligence (AI). Advances in neural networks have brought
natural-language processing (NLP) to IoT devices (such as digital personal assistants Alexa,
Cortana, and Siri) and made them appealing, affordable, and viable for home use.

What is industrial IoT?

Industrial IoT (IIoT) refers to the application of IoT technology in industrial settings, especially
with respect to instrumentation and control of sensors and devices that engage cloud
technologies. Refer to this Titan use case PDF for a good example of IIoT. Recently, industries
have used machine-to-machine communication (M2M) to achieve wireless automation and
control. But with the emergence of cloud and allied technologies (such as analytics and
machine learning), industries can achieve a new automation layer and with it create new
revenue and business models. IIoT is sometimes called the fourth wave of the industrial
revolution, or Industry 4.0. The following are some common uses for IIoT:
 Smart manufacturing
 Connected assets and preventive and predictive maintenance
 Smart power grids
 Smart cities
 Connected logistics
 Smart digital supply chains
 Unlock business value with IoT
As IoT becomes more widespread in the marketplace, companies are capitalizing on the
tremendous business value it can offer. These benefits include:

 Deriving data-driven insights from IoT data to help better manage the business
 Increasing productivity and efficiency of business operations
 Creating new business models and revenue streams
 Easily and seamlessly connecting the physical business world to the digital world to drive
quick time to value

What are IoT applications?

Business-ready, SaaS IoT Applications

 IoT Intelligent Applications are prebuilt software-as-a-service (SaaS) applications that

can analyze and present captured IoT sensor data to business users via dashboards.
 IoT applications use machine learning algorithms to analyze massive amounts of
connected sensor data in the cloud. Using real-time IoT dashboards and alerts, you gain
visibility into key performance indicators, statistics for mean time between failures, and
other information. Machine learning–based algorithms can identify equipment
anomalies and send alerts to users and even trigger automated fixes or proactive counter
measures.

 With cloud-based IoT applications, business users can quickly enhance existing
processes for supply chains, customer service, human resources, and financial services.
There’s no need to recreate entire business processes.

What are some ways IoT applications are deployed?

The ability of IoT to provide sensor information as well as enable device-to-device
communication is driving a broad set of applications. The following are some of the most
popular applications and what they do.

 Create new efficiencies in manufacturing through machine monitoring and

product-quality monitoring.
Machines can be continuously monitored and analyzed to make sure they are performing
within required tolerances. Products can also be monitored in real time to identify and
address quality defects.

 Improve the tracking and “ring-fencing” of physical assets.

Tracking enables businesses to quickly determine asset location. Ring-fencing allows them
to make sure that high-value assets are protected from theft and removal.

 Use wearables to monitor human health analytics and environmental conditions.

IoT wearables enable people to better understand their own health and allow physicians to
remotely monitor patients. This technology also enables companies to track the health and
 safety of their employees, which is especially useful for workers employed in hazardous
conditions.

 Drive efficiencies and new possibilities in existing processes.

One example of this is the use of IoT to increase efficiency and safety in connected logistics for
fleet management. Companies can use IoT fleet monitoring to direct trucks, in real time, to
improve efficiency.
 Enable business process changes.

An example of this is the use of IoT devices for connected assets to monitor the health of
remote machines and trigger service calls for preventive maintenance. The ability to remotely
monitor machines is also enabling new product-as-a-service business models, where customers
no longer need to buy a product but instead pay for its usage.

What industries can benefit from IoT?

Organizations best suited for IoT are those that would benefit from using sensor devices in
their business processes.

1. Manufacturing

Manufacturers can gain a competitive advantage by using production-line monitoring to enable

proactive maintenance on equipment when sensors detect an impending failure. Sensors can
actually measure when production output is compromised. With the help of sensor alerts,
manufacturers can quickly check equipment for accuracy or remove it from production until it
is repaired. This allows companies to reduce operating costs, get better uptime, and improve
asset performance management.
2. Automotive

The automotive industry stands to realize significant advantages from the use of IoT
applications. In addition to the benefits of applying IoT to production lines, sensors can detect
impending equipment failure in vehicles already on the road and can alert the driver with details
and recommendations. Thanks to aggregated information gathered by IoT-based applications,
automotive manufacturers and suppliers can learn more about how to keep cars running and
car owners informed.

3. Transportation and Logistics

Transportation and logistical systems benefit from a variety of IoT applications. Fleets of cars,
trucks, ships, and trains that carry inventory can be rerouted based on weather conditions,
vehicle availability, or driver availability, thanks to IoT sensor data. The inventory itself could
also be equipped with sensors for track-and-trace and temperature-control monitoring. The
food and beverage, flower, and pharmaceutical industries often carry temperature-sensitive
inventory that would benefit greatly from IoT monitoring applications that send alerts when
temperatures rise or fall to a level that threatens the product.
4. Retail

IoT applications allow retail companies to manage inventory, improve customer experience,
optimize supply chain, and reduce operational costs. For example, smart shelves fitted with
weight sensors can collect RFID-based information and send the data to the IoT platform to
automatically monitor inventory and trigger alerts if items are running low. Beacons can push
targeted offers and promotions to customers to provide an engaging experience.

5. Public Sector

The benefits of IoT in the public sector and other service-related environments are similarly
wide-ranging. For example, government-owned utilities can use IoT-based applications to
notify their users of mass outages and even of smaller interruptions of water, power, or sewer
services. IoT applications can collect data concerning the scope of an outage and deploy
resources to help utilities recover from outages with greater speed.

6. Healthcare

IoT asset monitoring provides multiple benefits to the healthcare industry. Doctors, nurses, and
orderlies often need to know the exact location of patient-assistance assets such as wheelchairs.
When a hospital’s wheelchairs are equipped with IoT sensors, they can be tracked from the IoT
asset-monitoring application so that anyone looking for one can quickly find the nearest
available wheelchair. Many hospital assets can be tracked this way to ensure proper usage as
well as financial accounting for the physical assets in each department.

7. General Safety Across All Industries

In addition to tracking physical assets, IoT can be used to improve worker safety. Employees
in hazardous environments such as mines, oil and gas fields, and chemical and power plants,
for example, need to know about the occurrence of a hazardous event that might affect them.
When they are connected to IoT sensor–based applications, they can be notified of accidents
or rescued from them as swiftly as possible. IoT applications are also used for wearables that
can monitor human health and environmental conditions. Not only do these types of
applications help people better understand their own health, they also permit physicians to
monitor patients remotely.

How is IoT changing the world?

Take a look at connected cars.
IoT is reinventing the automobile by enabling connected cars. With IoT, car owners can operate
their cars remotely—by, for example, preheating the car before the driver gets in it or by
remotely summoning a car by phone. Given IoT’s ability to enable device-to-device
communication, cars will even be able to book their own service appointments when warranted.

The connected car allows car manufacturers or dealers to turn the car ownership model on its
head. Previously, manufacturers have had an arms-length relationship with individual buyers
(or none at all). Essentially, the manufacturer’s relationship with the car ended once it was sent
to the dealer. With connected cars, automobile makers or dealers can have a continuous
relationship with their customers. Instead of selling cars, they can charge drivers usage fees,
offering a “transportation-as-a-service” using autonomous cars. IoT allows manufacturers to
upgrade their cars continuously with new software, a sea-change difference from the traditional
model of car ownership in which vehicles immediately depreciate in performance and value.