NAVODAYA VIDYALAYA SAMITI,NOIDA

E- Content for Class XI (Informatics Practices)

Topic: Unit 2 – Emerging Trends

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BY

SHILPI RANI

PGT IT

JNV Guntur A.P.

Contents

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• Immersive Experience
• Robotics
• Big Data
• Internet of Things
• Web of Things
• Sensors
• Smart Cities

• Cloud Computing
• Grid Computing
• Blockchain Technology

Artificial Intelligence (AI)

• Artificial Intelligence endeavors to simulate the natural intelligence of human beings into machines, thus making them behave intelligently.
• An intelligent machine is supposed to imitate some of the cognitive functions of humans like learning, decision-making and problem solving.
• In order to make machines perform tasks with minimum human intervention, they are programmed to create a knowledge base (a knowledge base is a store of information consisting of facts, assumptions and rules which an AI system can use for decision making) and make decisions based on it. AI system can also learn from past experiences or outcomes to make new decisions.

Artificial Intelligence (AI)

Machine Learning

• Machine Learning is a subsystem of Artificial Intelligence, wherein computers have the ability to learn from data using statistical techniques, without being explicitly programmed by a human being.
• It comprises algorithms that use data to learn on their own and make predictions. These algorithms, called models, are first trained and tested using a training data and testing data, respectively.
• After successive training, once these models are able to give results to an acceptable level of accuracy, they are used to make predictions about new and unknown data.

Machine Learning - Illustration

Types of Machine Learning Algorithms

Natural Language Processing (NLP)

• Natural Language Processing (NLP) system deals with the interaction between human and computers using human spoken languages, such as Hindi, English, etc.
• An NLP system can perform text-to-speech and speech-to-text conversion.
• The predictive typing feature of search engine that helps us by suggesting the next word in the sentence while typing keywords and the spell checking features are examples of Natural Language Processing (NLP).
• Machine translation is a rapidly emerging field where machines are able to translate texts from one language to another with fair amount of correctness. Another emerging application area is automated customer service where a computer software can interact with customers to serve their queries or complaints.

Natural Language Processing (NLP)

Immersive Experiences

• Immersive experiences allow us to visualize, feel and react by stimulating our senses. It enhances our interaction and involvement, making them more realistic and engaging.
• Immersive experiences have been used in the field of training, such as driving simulators, flight simulator and so on.
• Immersive experience can be achieved using virtual reality and augmented reality.

Immersive Experiences

Virtual Reality:

• Virtual Reality (VR) is a three-dimensional, computer-generated situation that simulates the real world. The user can interact with and explore that environment by getting immersed in it while interacting with the objects and other actions of the user.
• At present, it is achieved with the help of VR Headsets. In order to make the experience of VR more realistic, it promotes other sensory information like sound, smell, motion, temperature, etc.

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Immersive Experiences

Augmented Reality:

• The superimposition of computer generated perceptual information over the existing physical surroundings is called as Augmented Reality (AR). It adds components of the digital world to the physical world, along with the associated tactile and other sensory requirements, thereby making the environment interactive and digitally manipulable.
• With the help of location-based AR App, travelers can access real-time information of historical places just by pointing their camera viewfinder to subjects. Users can access information about the nearest places with reference to their current location

Robotics

• A robot is basically a machine capable of carrying out one or more tasks automatically with accuracy and precision. A robot is programmable, which means it can follow the instructions given through computer programs. Sensors are one of the prime components of a robot.
• Robots were initially conceptualized for doing repetitive industrial tasks that are boring or stressful for humans or were labor-intensive.
• Robot can be of many types, such as wheeled robots, legged robots, manipulators and humanoids. Robots that resemble humans are known as humanoids. Some examples are:

Robotics

Robotics

• Robotics is primarily concerned with the design, fabrication, operation, and application of robots.

Big Data

Big Data

• Such data cannot be processed and analyzed using traditional data processing tools as the data is not only voluminous, but also unstructured. Big data not only represents voluminous data, it also involves various challenges like integration, storage, analysis, searching, processing, transfer, querying and visualization of such data
• Big data hold rich information and knowledge which is of high business value, and therefore there is a keen effort in developing software and methods to process and analyze big data.
• Characteristics of Big Data:
• (A) Volume
• (B) Velocity
• (C) Variety
• (D) Veracity
• (E) Value

Characteristics of Big Data

Characteristics of Big Data

(A) Volume:

The most prominent characteristic of big data is its enormous size. If a particular data set is of such large size that it is difficult to process it with traditional DBMS tools, it can be termed as big data.

(B) Velocity:

It represents the rate at which the data under consideration is being generated and stored. Big data has an exponentially higher rate of generation than traditional data sets.

(C) Variety:

It asserts that a data set has varied data, such as structured, semi-structured and unstructured data. Some examples are text, images, videos, web pages and so on.

Characteristics of Big Data

(D) Veracity:

Big data can be sometimes inconsistent, biased, and noisy or there can be abnormality in the data or issues with the data collection methods. Veracity refers to the trustworthiness of the data because processing such incorrect data can give wrong results or mislead the interpretations.

(E) Value:

Big data is not only just a big pile of data, but also possess to have hidden patterns and useful knowledge which can be of high business value. But as there is cost of investment of resources in processing big data, we should make a preliminary enquiry to see the potential of the big data in terms of value discovery.

Big Data

Data Analytics

• Data analytics is the process of examining data sets in order to draw conclusions about the information they contain, with the aid of specialized systems and software.
• Data analytics are used in commercial industries to enable organizations to make more informed business decisions. In the field of science and technology, it can be useful for researchers to verify or disprove scientific models, theories and hypotheses.

Top Big Data Applications

Internet of Things (IoT)

• The ‘Internet of Things’ is a network of devices that have an embedded hardware and software to communicate (connect and exchange data) with other devices on the same network.
• For example, if a microwave oven, an air conditioner, door lock, CCTV camera or other such devices are enabled to connect to the Internet, we can access and remotely control them on-the-go using our smartphone.

Internet of Things (IoT)

Web of Things (WoT):

• Web of Things (WoT) allows the use of web services to connect anything in the physical world, besides human identities on web. It will pave way for creating smart homes, smart offices, and smart cities and so on.
• Sensors:
• A smart sensor is a device that takes input from the physical environment and uses built-in computing resources to perform predefined functions upon detection of specific input and then process data before passing it on.
• The evolution of smart electronic sensors is contributing in a large way to the evolution of IoT. It will lead to creation of new sensor-based, intelligent systems.

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Internet of Things (IoT)

Smart Cities:

• The idea of a smart city as shown in Figure makes use of computer and communication technology along with IoT, WoT to manage and distribute resources efficiently. The smart building shown here uses sensors to detect earthquake tremors and then warn nearby buildings so that they can prepare themselves accordingly. The smart bridge uses wireless sensors to detect any loose bolt, cable or crack. It alerts concerned authorities through SMS.

The smart tunnel also uses wireless sensors to detect any leakage or congestion in the tunnel. This information can be sent as wireless signals across the network of sensor nodes to a centralized computer for further analysis.

SMART CITIES

An Illustration of Smart City

Cloud Computing

• Cloud computing is an emerging trend in the field of information technology, where computer-based services are delivered over the Internet or the cloud, for the case of their accessibility form anywhere using any smart device.
• The services comprise software, hardware (servers), databases, storage, etc. These resources are provided by companies called cloud service providers and usually charge on pay per use basis.

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• Cloud Services:
• A service corresponds to any facility provided by the cloud. There are three standard models to categorize different computing services delivered through cloud. These are Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).

Cloud Computing

Cloud Computing

(A) Infrastructure as a Service (IaaS):

• The IaaS providers can offer different kinds of computing infrastructure, such as servers, virtual machines (VM), storage and backup facility, network components, operating systems or any other hardware or software.
• Using IaaS from the cloud, a user can use the hardware infrastructure located at a remote location to configure, deploy and execute any software application on that cloud infrastructure, thereby they can save the cost of software, hardware and other infrastructures as well as the cost of setting up, maintenance and security.
• (B) Platform as a Service (PaaS):
• PaaS provides a platform or environment to develop, test, and deliver software applications.
• In PaaS, the user has complete control over the deployed application and its configuration. It provides a deployment environment for developers at a much reduced cost lessening the complexity of buying and managing the underlying hardware and software.

Cloud Computing

(C) Software as a Service (SaaS):

• SaaS provides on-demand access to application software, usually requiring a licensing or subscription by the user.
• For example, while using Google doc, Microsoft Office 365, Drop Box, etc., to edit a document online, we use SaaS from cloud.
• A user is not concerned about installation or configuration of the software application as long as the required software is accessible. Like PaaS, a user is provided access to the required configuration settings of the application software that they are using at present.
• In order to utilize and harness the benefits of cloud computing, Government of India has embarked upon an ambitious initiative —‘GI Cloud’ which has been named as ‘MeghRaj’ (https://cloud.gov.in).

Grid Computing

• A grid is a computer network of geographically dispersed and heterogeneous computational resources. Unlike cloud, whose primary focus is to provide services, a grid is more application specific and creates a sense of a virtual supercomputer with an enormous processing power and storage. The constituent resources are called nodes. These different nodes temporarily come together to solve a single large task and to reach a common goal.
• Grid can be of two types — (i) Data grid, used to manage large and distributed data having the required multi-user access, and (ii) CPU or Processor grid, where processing is moved from one PC to another as needed or a large task is divided into sub-tasks, and allotted to various nodes for parallel processing.
• The grid provides an opportunity to solve computationally intense scientific and research problems without actually procuring a costly hardware.

Grid Computing

• To set up a grid, by connecting numerous nodes in terms of data as well as CPU, a middle-ware is required to implement the distributed processor architecture. The Globus toolkit (https://toolkit.globus.org/toolkit) is one such software toolkit used for building grids, and it is as open source. It includes software for security, resource management, data management, communication, fault detection, etc.

Grid Computing

Grid Computing

Blockchain Technology

• Digital transactions are performed by storing data in a centralized database and the transactions performed are updated one by one on the database. However, since all the data is stored on a central location, there are chances of data being hacked or lost. So, rescue is Blockchain technology.
• The Blockchain technology works on the concept of decentralized and shared database where each computer has a copy of the database.
• A block can be thought as a secured chunk of data or valid transaction. Each block has some data called its header, which is visible to every other node, while only the owner has access to the private data of the block.

Blockchain Technology

• Blockchain can define as a system that allows a group of connected computers to maintain a single updated and secure ledger. Each computer or node that participates in the Blockchain receives a full copy of the database. It maintains an ‘append only’ open ledger which is updated only after all the nodes within the network authenticate the transaction.
• Safety and security of the transactions are ensured because all the members in the network keep a copy of the Blockchain and so it is not possible for a single member of the network to make changes or alter data.

Blockchain Technology

Blockchain Technology – Working Process Illustration

WHY Blockchain Technology ?

Blockchain Technology

Applications of Blockchain Technology:

• The most popular application of block chains technology is in digital currency.
• In healthcare, better data sharing between healthcare providers would result in a higher probability of accurate diagnosis, more effective treatments, and the overall increased ability of healthcare organizations to deliver cost-effective care.
• Another potential application can be for land registration records, to avoid various disputes arising out of land ownership claims and encroachments.
• A Blockchain based voting system can solve the problem of vote alterations and other issues. Since everything gets stored in the ledger, voting can become more transparent and authentic.
• The Blockchain technology can be used in diverse sectors, such as banking, media, telecom, travel and hospitality and other areas.