Business is enabling the BI, AI & IoT to help
the production lines to purchasing trends to consumer analysis. I am Ravindra
Pande (ravindrapande@gmail.com / rrpande@indiatrainingservices.in)
trying to extrapolate the possibilities in scientific way this is not Si-Fi but
current situation and very near future
situations. Like to have your suggestions and feedback as always. Imagine a smart future! A future where machines are not merely
dumb devices but intelligent creations that can work in tandem with human
beings. A future that looks remarkably like the robotic utopia in I, Robot
(Well, except the homicidal robots!). This future is not merely an imagination
but a natural consequence of the two most dynamic technologies of today.
Factories deploy AI to automate complex physical
tasks requiring adaptability and agility. Marketers use AI to generate
individualized recommendations to the automatic order fulfillment scenarios. The
list is expanding really fast and open to all new ideas and error free efficient process. A host of
services taken for granted today, from credit card fraud detection to email spam
filters to predictive traffic
alerts to personalized reminders, wouldn’t be possible without AI. One area
where AI is used extensively is business intelligence. Enterprises leverage
deep learning algorithms to spot behavioral patterns likely to lead to sales,
use cues from IoT sensors for predictive maintenance and inventory optimization
and do more. However, what businesses do now is just the tip of the iceberg of
possibilities.
AI Enables
Live Decision Making, with the proliferation of data, several businesses
run the risk of data overload. The unprecedented growth of Big Data and the
obsession to analyze such data can easily gag the core operations of the
business. AI-powered business intelligence software enables enterprises to
break down data into manageable insights, and make sense of Big Data.
AI also has the potential to change the dynamics of
analytics. Conventional data analytics focused on descriptive analytics or
analyzing data to report what happened. The present generation of AI-enabled
analytics tools enable predictive analytics or using data to decipher future
insights. This, however, is based on “best guesses” with behavioral and
historical data used to guess probabilities.
Prescriptive
analytics is all set to take over in the near future. AI-powered
prescriptive analytics tools would scour through vast swathes of data and
enable users to prescribe various possible actions and advise viable solutions.
Prescriptive analytics not just predicts, but offers sound advice as well, and
explains why things will happen the way it will or does.
The shift from reactive predictive analytics to proactive prescriptive analytics
improves the potency and relevance of business decisions. Live, real-time insights
enable enterprises to make the best use of their operational data, making
decisions based on what’s currently happening rather than based on what
happened in the past. Much of the recommendations can be automated as well,
with the best course of action determined by the intelligent machine based on
the available inputs.
AI Brings Voice
and Facial Recognition to the Center stage : AI-powered voice-activated
digital personal assistants have already enamored millennial in a big way. The spurt in deep learning-powered
applications such as speech recognition interfaces, its widespread adoption by
businesses and the tremendous popularity of digital voice assistants such as
Apple Siri, Amazon Alexa and Google Assistant are portents of things to come.
Voice will replace the keyboard and touch interfaces as the default norm for
individuals to engage with brands, cutting across industries.
Likewise, matured facial recognition technology is
all set to make big strides from present levels, in the near future. AI-powered
facial recognition technology may just make the highly irritating password
obsolete.
AI Powers
Hyper-Personalization : AI-based intelligence learns from experience,
becoming better with each experience or transaction. With the next prescribed
decision automatically better than the previous one, the stage where the AI
model is highly matured and covers all eventualities isn’t far off.
It gets better. AI-powered systems of the future
could automatically decipher the user and even the users’ emotions from the
soon-to-be-commonplace voice commands, to make highly accurate recommendations
or engage with them at a truly personal level. The next wave of AI-powered
assistants will be capable of analyzing huge troves of data contextually, in
real-time, to grasp customers’ need and priorities quickly, and do what’s
required. AI is all set to make hyper-personalization the default norm, rather
than a premium service as it is now.
At a macro level, enterprises would be able to
collate information from various data points and make real-time live sentiment analysis. For example, an enterprise
could collect live data from the customer’s engagement with the company, their
social media posts and other data, to understand their thought process and
emotional reaction about a product and make real-time interventions to either
reinforce or change such perceptions.
AI is already helping industries such as financial
services, healthcare, securities trading and life sciences in a big way. For
instance, AI is taking over the role of the clinical assistant, helping
physicians make faster and more reliable diagnoses. Such instances will become
commonplace to the extent human intervention will become rare.
However, as of now, machines traditionally don’t do
well when it comes to abstract tasks involving human capabilities such as
empathy, creativity, judgment, inspiration and leadership. Two critical
management functions, innovation and managing people, are still almost entirely
with humans. This could change in the future thanks to AI systems becoming more
mature. Presently, algorithms may suffer from some amount of bias or
subjectivity, considering the algorithms are designed by humans after all. As
training data gets more mature, such biases and negative effects will be
quickly eradicated.
Artificial intelligence is here to stay. AI has the
potential to transform how top executives make decisions, how marketers engage
with customers, how enterprises compete with each other and how they develop
overall to become more potent and powerful. The future of business intelligence
will surely be driven by AI-enabled systems.
Well, Artificial Intelligence deals with the
creation of systems that can learn to emulate human tasks using their prior experience and without any
manual intervention. (Basically Intelligent Systems!). Internet of Things,
on the other hand, is a network of various devices that are connected over the
internet and they can collect and exchange data with each other enabling the AI in an exponential scale.
To understand this further, all these IoT devices
generate a lot of data that needs to be collected and mined for actionable
results. This is where Artificial Intelligence comes into the picture. Internet
of Things is used to collect and handle the huge amount of data that is
required by the Artificial Intelligence algorithms. In turn, these algorithms
convert the data into useful actionable results that can be implemented by the
IoT devices.
Without AI-powered analytics, IoT devices and the
data they produce throughout the network would have limited value. Similarly, AI systems would struggle to be relevant in
business settings without the IoT-generated data pouring in. However, the
powerful combination of AI and IoT can transform industries and help them make
more intelligent decisions from the explosive growth of data every day. IoT is
like the body, and AI the brains, which together can create new value
propositions, business models, revenue streams and services
The Power
for IoT : The number of sensors in the Internet of Things (IoT) will grow
like never seen before we’re talking of billions to trillions of sensors. As
most of them will be connected wirelessly, we need to rethink the technologies
for how to power the sensors.
Batteries are part of our mobile lives. We find
them in each portable device and in millions of remote controls for smart home
and building automation. With trillions of wireless IoT sensors, the demand for
batteries will increase into infinity. However, infinity is no option for a
battery-powered IoT.
Limits of
Lithium: For the 10 trillion wireless sensors delivering the needed data
for IoT, they would require one million tons of lithium – the combined
worldwide lithium production in 10 years. And, we even need much more for our
smartphones, electrical cars, local energy storage systems, etc. Consequently,
there’s not enough lithium in the world for all of these applications.
Additionally, the environmental impact of lithium
mining results in water shortage, air pollution and destruction of nature reserves.
No recycling technology exists today that is capable of producing enough pure
lithium for a second use in batteries.*
Lithium is just one element batteries contain.
There are also toxic heavy metals such as mercury, lead, cadmium and nickel in
batteries, which are detrimental to the environment. At the end of their
lifetime, they need to be disposed of carefully and expensively. Recycling
isn’t always an option and is polluting as well. Reports reveal that it takes 6
to 10 times more energy to reclaim metals from some recycled batteries than
from mining.
Challenges
of Changing : Besides the environmental impact of battery production,
disposal and recycling, there are further costs that we need to consider as
batteries need maintenance.
Wireless connectivity supports devices to be
flexibly installed or mobile and their location needs to be documented and
updated as their location changes. In a large building system, hundreds of
sensors are distributed over several floors and offices. Often, the devices are
mounted unobtrusively in places that are difficult to reach, e.g. on or above
drop ceilings. Depending on the battery technology in use, a user will dispose
of between 200 and 1,600 batteries over 20 years in a residential home with
only 50 nodes.
In addition, each device has a different battery
access method and requires different types of batteries. This results in extra
work, making the battery replacement a challenging and time-consuming effort.
Usually, batteries don’t run out of energy at the same time. So, the technician
might just have left the facility after changing some batteries when the next
battery dies. Well, call the technician again.
Benefits of Battery
less: Considering the costs of batteries, IoT, with its trillions of sensor
nodes, needs a more eco-balanced and maintenance-free alternative to power
mobile devices. This alternative exists today and is already deployed in
building automation and smart home systems or in outdoor environmental
monitoring systems: energy harvesting wireless sensors.
Like we switch our power production to the use of
renewable energy sources, such as sun, wind, water, etc., self-powered sensors
use the same principles of harvesting energy from the surrounding environment
at a micro-level. Miniaturized energy converters use kinetic motion, light or
temperature differences to power wireless sensing and data communication.
There’s no need for a battery change and disposal and no need for
time-consuming maintenance. Simply install and forget.
It’s a simple calculation and our ecological
responsibility to realize a self-powered Internet of Things. Energy harvesting
wireless sensors are the only way to avoid tons of battery waste and to ensure
reliable and maintenance-free system functionality. Artificial
Intelligence and the Internet of Things is like a match made in Tech Heaven.
While both of these disciplines have individual
value, their true potential can only be realized together. There are many different
applications across multiple industries that require Artificial Intelligence
and Internet of Things.
Connected
Robots: Ever wanted the help of a robot? Well, that’s exactly what you will
get with Collaborative Robots or Cobots. These Cobots are highly complex machines
that are designed to help humans in a shared workspace with environments ranging
from office to industrial. They can be a robot arm designed to perform tasks or
even a complex robot designed to fulfill tough tasks without least manual
interventions.
All favorite Drones:
Drones are aircraft without a human pilot (The piloting is done by the
software!). They are extremely useful as they can navigate unknown surroundings
(even those beyond the reach of the internet) and reach areas hazardous for
humans such as offshore operations, mines, war zones or burning buildings.
Smart Cities:
When everything is getting smart, why not whole cities? Smart cities can be
created with a network of sensors that are attached to the physical city
infrastructure. These sensors can be used to monitor the city for various civic
factors such as energy efficiency, air pollution, water use, noise pollution,
traffic conditions, etc. In India specifically the great innovative vision of
Hon Prime Minister Mr. Nerandra Modi enabled a great project with in Indian
country to enable smart administration of cities.
Smart
Retailing: This is shopping made smart! AI and IoT can be used by retailers
to understand the customer behavior (by studying the consumer online profile,
in-store inventory, etc.) and then send real-time personalized offers while the
customer is in the store. While Artificial Intelligence in the Internet of
Things is a relatively new concept, it has already been successfully applied in
many real-world applications. (Yeah, this world is more tech-savvy than we
thought!) Some of these applications are given as follows:
Self Driving
Cars: Sound like futuristic science-fiction yet they are very much a part
of today’s reality. The Tesla Motors self-driving cars use the latest
advancements in Artificial Intelligence and the Internet of Things. While these
cars are still in the testing phase (With multiple legal and ethical concerns
as baggage!) they are still one of the easier innovations of IoT. A unique
feature of the Tesla self-driving cars is that all of them act like a connected
network. Whenever one car learns some new information, which is passed on to
all the other cars. And that is used to predict the behavior of cars and
pedestrians on the road in various circumstances.
Endangered
Species Preservation: There are many animals that are endangered or going
extinct in various countries (No thanks to human of course!). Also, the
traditional methods of tracking these animals with collars are stressful and
dangerous (Both to the animals and researchers). So WildTrack’s footprint
identification technique (FIT) uses IoT and AI algorithms to identify the
species, individual, age and gender of an animal from its unique footprint. Then
this data can be used to recognize patterns relating to animal movements,
species population, etc. that help in preserving various endangered species.
Smart
thermostat : Everything is becoming smart these days, this device uses IoT
to allow temperature checking and controls from anywhere using smartphone
integration. It is also quite simple to use, which is one of the primary
reasons for its success (apart from AI and IoT of course!). Artificial Intelligence plays a big role in
the Nest Labs thermostat. It is used to understand the temperature preferences
of the users and also their daily schedule. Then it adapts accordingly for
optimal temperature and also maximum energy savings.
Automated vacuum cleaner – iRobot Roomba: When
everything else is becoming smart, why not a smart vacuum cleaner? The iRobot
Roomba is developed by three members of MIT’s Artificial Intelligence Lab and
it uses IoT and AI to clean a room as efficiently as possible. It is a robotic
vacuum cleaner that uses a set of sensors to detect obstacles, dirty spots on
the floor or even steep drops such as stairs.
So, it essentially remembers the layout of the
living space (As much as machines can anyway!) and then uses the most efficient
and economical movements for cleaning. A smartphone app can be used to adjust
the performance requirements with “Clean” mode, “Spot” mode, “Dock” mode, etc.
Conclusion:
This is an exciting new time to live in (both for humans and machines!). With
multiple advances in artificial intelligence, light-speed communications, and
analytics, IoT is even more convenient and high-performance IoT devices are
taking over almost every domain of technology. Moreover, the declining hardware
costs make it feasible to embed sensors and connectivity in just about any
device imaginable. Taken together, Artificial Intelligence and Internet of
Things are ushering in a new era where “smart” is just the normal state of
being and the robotic utopia in the future appears more and more attainable in
the present.
