Applications and Methodologies Class 11 Notes

Teachers and Examiners (CBSESkillEduction) collaborated to create the Applications and Methodologies Class 11 Notes. All the important Information are taken from the NCERT Textbook Artificial Intelligence (417).

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Applications and Methodologies Class 11 Notes

applications and methodologies class 11 notes

Key Fields of Application in AI

According to the father of Artificial Intelligence, John McCarthy, “Artificial Intelligence is the science and
engineering of making intelligent machines, especially intelligent computer programs”.

Artificial intelligence aids in the creation of intelligent hardware and software that functions, learns, and reacts much like humans. AI is now ingrained in all aspects of modern life, including research, engineering, business, medicine, video games, and many more. The applications that are covered here are a few.

Applications and Methodologies Class 11 Notes


One of the uses for AI is the chatbot, which simulates human dialogue using text chats, voice commands, or both. We can characterize a chatbot as an artificial intelligence programme that can mimic a real conversation with a user in their native tongue. On websites, messaging services, mobile applications, or telephones, they make it possible to communicate via text or audio.

Types of Chatbots

Chatbots can broadly be divided into two types:
1. Rule based Chatbot
2. Machine Learning (or AI) based Chatbot risk

Rule – based Chatbot
This is a Chatbot in its most basic version, and it responds to user questions in accordance with a set of pre-established rules. For instance, a chatbot positioned at a front desk at a school can access information from the school’s archive to respond to questions about the cost of attendance, the courses offered, the pass rate, etc.

Rule-based chatbots can only be used for straightforward discussions; they are ineffective for more complicated ones.

Applications and Methodologies Class 11 Notes

Machine Learning (or AI) based Chatbot risk
Such chatbots are more sophisticated chatterbots that can have in-depth real-time dialogues. Prior to answering the questions, they process them (using layers of neural networks). AI-based chatbots continue to evolve by learning from previous experience and reinforced learning.

AI chatbots are created and designed to respond to user inquiries in a reasonable and pertinent manner. The difficulty, however, lies in matching the requests with the closest and smartest response that would please the user.

Example of AI Based Chatbot

HDFC Bank’s EVA – Electronic Virtual Assistant is making banking service simple and is available 24×7 for the HDFC bank’s customers.

Apollo Hospital Amidst – Apollo hospitals (as well as many other hospitals and medical businesses) released a Chatbot to assess one’s risk level amid the current panic around COVID 19.

Applications and Methodologies Class 11 Notes

Natural Language processing (NLP)

Natural language is simply human language. It refers to the various ways that people can communicate with one another, including spoken, written, non-verbal, and facial expressions (sentiments such as sad, happy, etc.). Natural language processing is the field of computer science that enables computers to comprehend and process human language naturally (NLP).

Artificial intelligence that deals with the use of natural language in communication between machines and people. NLP’s primary goal is to read, interpret, comprehend, and coherently make sense of human language in a way that benefits everyone.

Applications and Methodologies Class 11 Notes

Text Recognition

Now that a camera or other device has captured an image of a license plate, NLP software uses a neural network layer to extract the plate’s number. However, the quality of the image also affects how well the data is extracted.

Summarization by NLP

NLP is able to summaries an article into a condensed narrative without altering the meaning in addition to reading and understanding individual paragraphs or the entire piece. It can produce the complete article’s abstract. There are two methods of summarization: one involves extracting significant terms from the source text and combining them to create a summary (extraction-based summarization), and the other involves condensing the original text (abstraction-based summarization).

Applications and Methodologies Class 11 Notes

Information Extraction

Information extraction is a technology that allows you to search within a document or find a specific piece of information. It automatically extracts structured data from unstructured sources, including entities, relationships between entities, and attributes describing entities.

Speech processing

Speech processing describes a computer’s capacity to hear human speech, analyze it, and comprehend its content. Alexa and Siri, among other technologies, understand what we say when we speak to them.

Applications and Methodologies Class 11 Notes

Computer Vision (CV)

The study of CV makes it possible for computers to “see.” It is a branch of artificial intelligence that deals with the analysis and comprehension of the information contained in digital images such as movies and photographs. The following areas are where CV has been most successful:
a. Object detection
b. Optical Character Recognition
c. Fingerprint Recognition

Computer Vision: Primary Tasks

There are primarily four tasks that Computer vision accomplishes:
1. Semantic Segmentation (Image Classification)
2. Classification + Localization
3. Object Detection
4. Instance Segmentation

Applications and Methodologies Class 11 Notes

Semantic Segmentation

Image categorization is another name for semantic segmentation. Semantic segmentation is a technique used in computer vision to categories images based on their visual content. In essence, a model is taught to recognize a set of classes—objects to identify in images—with the aid of labelled sample pictures. In plain English, it takes an image as input and outputs a class, such as a cat, dog, etc., or a probability of classes, from which one has the greatest likelihood of being accurate.

Applications and Methodologies Class 11 Notes

Classification and Localization

The localization job is activated when the object has been identified and labelled, which creates a bounding box around the object in the image. The location of the object within the image is referred to as “localization.” If a picture contains, for example, a dog, the algorithm determines the class and draws a bounding box around it.

Object Detection

Humans can instantly recognize the objects in a video or image when they see it. Computers can produce intelligence like this. If there are numerous objects in the image, the algorithm will locate each one by drawing a bounding box around it. As a result, the bounding boxes and labels around the items will be numerous.

Applications and Methodologies Class 11 Notes

Instance segmentation

The CV technique known as instance segmentation aids in clearly recognising and delineating each object of interest present in an image. This procedure gives us a far more detailed understanding of the object or objects in the image by helping to generate a pixel-wise mask for each one. The figure below illustrates how objects from the same class are displayed in various colours.

Applications and Methodologies Class 11 Notes

Weather Prediction using AI

Global weather forecasts are being accelerated by new AI-based weather forecasting research. The research, which was just published in the Journal of Advances in Modeling Earth Systems, may be used to predict potential extreme weather 2–6 weeks in advance. Accurate weather forecasts with more time to prepare and minimise potential disasters give communities and vital industries including public health, water management, energy, and agriculture more time.

IBM Global High – resolution Atmospheric Forecasting System

A high-precision global weather model called IBM Global High-resolution Atmospheric Forecasting System (IBM GRAF) refreshes hourly to give a more accurate picture of weather activities all over the world.

Applications and Methodologies Class 11 Notes


On its weather predicting model, Panasonic has been working for years. The business manufactures TAMDAR, a unique weather sensor used on commercial aircraft.

Price forecast for commodities

The earth’s natural resources and agricultural products are considered commodities. These products include things like wheat, livestock, soybeans, corn, oranges, different metals, coal, cotton, and oil, among others.

Applications and Methodologies Class 11 Notes

Self-Driving car

A self-driving automobile is a vehicle that can sense its surroundings and move safely with little to no human intervention. It is also referred to as an autonomous vehicle (AV), a driverless car, a robot car, or a robotic car. Self-driving cars use a combination of radar, lidar, sonar, GPS, odometry, and inertial measuring units to sense their environment.

Applications and Methodologies Class 11 Notes

Characteristics and Types of AI

1. Artificial Intelligence is autonomous and can make independent decisions — it does not require human inputs, interference or intervention and works silently in the background without the user’s knowledge. These systems do not depend on human programming, instead they learn on their own through data experiencing.

2. Has the capacity to predict and adapt – Its ability to understand data patterns is being used for
future predictions and decision-making.

3. It is continuously learning – It learns from data patterns.

4. AI is reactive – It perceives a problem and acts on perception.

5. AI is futuristic – Its cutting-edge technology is expected to be used in many more fields in future.

Applications and Methodologies Class 11 Notes

Data Driven AI

Data centric AI systems have become more popular as a result of recent advancements in low-cost data storage (hard discs, etc.), quick processors (CPU, GPU, or TPU), and advanced deep learning algorithms that have made it feasible to extract enormous value from data. These AI systems are particularly effective in foretelling the future based on their past experiences.

Autonomous System

An autonomous system is a piece of technology that can react to its surroundings without human input. Often, artificial intelligence serves as the foundation for autonomous systems. A floor-cleaning robot, a Mars rover, a self-driving car, and other autonomous systems are examples. Another illustration of an autonomous system is an IoT device, such as a smart home system.

Recommendation systems

A recommendation system makes suggestions or recommendations to users based on data analysis and a variety of characteristics, including the user’s past behavior, preferences, and interests. Data is required for training this data-driven AI. For instance, when you view a video on YouTube, it suggests a number of other videos that are similar to, better, or more appropriate than the videos you often search for, favor, or have recently been watching.

Applications and Methodologies Class 11 Notes

Cognitive Computing (Perception, Learning, Reasoning)

To simulate the functions of the human brain (speech, vision, reasoning, etc.) and aid people in making decisions, cognitive computing is a technology platform based on AI and signal processing.

Applications of Cognitive Computing

Humans can utilise cognitive computing to help them make decisions. The treatment of disease/illness through assisting medical professionals is one example of cognitive computing and its applications.

The IBM Watson for Oncology, for example, has been deployed at the Memorial Sloan Kettering Cancer Center to offer doctors evidence-based therapy options for cancer patients. Watson creates a list of theories and suggests possible treatments for doctors in response to inquiries from medical professionals.

AI and Society

While there is little doubt that AI is transforming the world, there is also a lot of hype and misinformation surrounding it. It is essential that we have a realistic perspective on AI if individuals, corporations, and the government are to fully benefit from it.

Nearly every aspect of society, including health, security, culture, education, employment, and enterprises, will be impacted by AI. As with any change or development, AI can have both beneficial and harmful effects on society, depending on how we use it.


IBM Watson (An AI Tool by IBM) can predict development of a particular form of cancer up to 12 months before its onset with almost a 90% accuracy.

Such advancements are occurring often in the world of medicine. China used Artificial Intelligence (AI), Data Science, to track cases and combat the pandemic in order to contain the CORONA virus spread. Robots and AI tools will eventually work alongside doctors in our healthcare sectors.


Artificial intelligence and machine learning have made significant advancements in the sector of transportation.

With the help of cutting down on traffic accidents, autonomous vehicles, such as cars and trucks, can offer features including lane-changing systems, automated vehicle guiding, automated braking, usage of sensors and cameras for collision avoidance, and real-time information analysis.

Disaster Prediction

One of the best techniques for predicting natural events is artificial intelligence (AI). Before the development of artificial intelligence, it was impossible to imagine a model that could virtually accurately predict the weather for the upcoming few days.


The farming industry faces a variety of difficulties, including erratic weather, a lack of natural resources, an increase in population, etc. Farmers can now analyze a range of factors in real time, such as weather, temperature, water use, or soil conditions gathered from their farm, with the aid of artificial intelligence (AI).

Integrity of AI

In 2016, it was shown that the professional networking website LinkedIn has a gender bias in its code.
The site would display suggestions and search results for male users who went by the name “Andrew” and its variants when a feminine name was searched, such as “Andrea”. For male names, the website did not display any comparable suggestions or results.

Technological Unemployment

Some groups of individuals will lose their occupations as a result of substantial automation (caused by the development of AI and robotics).
Intelligent machines will take the place of these jobs. Both the workforce and the market will undergo major change; while new, highly skilled positions will be created, some will become outdated.

Disproportionate control over data

The more data you have, the more intelligent machines you will be able to create. Data is the fuel for AI. Technology behemoths are significantly funding initiatives involving AI and data collection. They have an unfair advantage over their smaller rivals as a result.


Whether a person is at work, home, or a public venue, AI can be used to identify, track, and monitor them across various devices. AI doesn’t forget anything, which just makes everything more complicated. Once AI recognizes you, it does so permanently!

Applications and Methodologies Class 11 Notes

Image Datasets

Image Datasets is categorized in three types –

a. Initial Training Dataset – These are the images students should use to “teach” their machine learning model which image is a cat and which image is a dog.

b. Test Dataset – These are the images that students should use to test their classifier after training. Students should show these images to their model and record if their classifier predicts if the image is of a dog or a cat.

c. Recurating dataset – This is a large assortment of images students can use to make their training dataset of cats and dogs larger and more diverse.

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