1st PUC Computer Science Chapter 3 Emerging Trends Notes

Emerging trends are state-of-the-art technologies that gain popularity and create new trends among users. This chapter introduces important emerging technologies and explains their role in the future of digital economy and digital societies.

Key Points

• AI enables machines to perform intelligent tasks.
• It attempts to imitate cognitive functions of humans.
• Learning, decision-making and problem solving are examples of such functions.
• AI systems can create a knowledge base and make decisions using it.
• An AI system can also learn from past experiences or outcomes.

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.

Applications Mentioned in the Chapter

• Smartphone maps analysing real-time traffic data.
• Automatic recognition and tagging of people in photographs.
• Digital personal assistants such as Siri, Google Now, Cortana and Alexa.

Key Points

• Machine Learning is a subsystem of AI.
• It uses algorithms that learn from data.
• The algorithms are called models.
• Models are trained using training data.
• Models are tested using testing data.
• After successive training, models can make predictions about new and unknown data.

Examples

• Predictive typing.
• Spell checking.
• Voice-based web searching.
• Voice control of devices.
• Text-to-speech conversion.
• Speech-to-text conversion.
• Machine translation.
• Automated customer service.

Applications

• Driving simulators.
• Flight simulators.
• Video games.
• Training and simulation.

• The user can interact with and explore the virtual environment.
• VR is currently achieved with the help of VR headsets.
• Other sensory information can include sound, smell, motion and temperature.
• Applications include gaming, military training, medical procedures, entertainment, social science and psychology, and engineering.

• AR adds components of the digital world to the physical world.
• It makes the environment interactive and digitally manipulable.
• Location-based AR applications can provide information about nearby places.
• Travellers can access real-time information about historical places by pointing a camera viewfinder at them.

Key Points

• A robot is programmable by a computer.
• Robots follow instructions given through computer programs.
• Robots were initially conceptualised for repetitive and labour-intensive tasks.
• Sensors are one of the prime components of a robot.
• Types include wheeled robots, legged robots, manipulators and humanoids.
• Robots resembling humans are called humanoids.
• Robotics involves mechanical engineering, electronics and computer science.

Applications and Examples

• NASA’s Mars Exploration Rover: Robotic space mission to study Mars.
• Sophia: A humanoid using AI, visual data processing and facial recognition.
• Drones: Unmanned aircraft that can be remotely controlled or fly autonomously through software-controlled flight plans.

Drone Applications Mentioned

Journalism, filming, aerial photography, short-distance shipping or delivery, disaster management, search and rescue, healthcare, geographic mapping, structural safety inspections, agriculture, wildlife monitoring, law enforcement and border patrolling.

Data is generated at a very high rate through Internet activities and connected devices. Examples include posts, instant messages, chats, photographs, tweets, blog articles, news items, opinion polls, comments and audio/video chats.

Challenges

• Integration
• Storage
• Analysis
• Searching
• Processing
• Transfer
• Querying
• Visualisation

Volume

Volume represents the enormous size of Big Data. A dataset that is so large that traditional DBMS tools have difficulty processing it can be termed Big Data.

Velocity

Velocity represents the rate at which data is generated and stored. Big Data has a much higher rate of generation than traditional datasets.

Variety

Variety represents different forms of data such as structured, semi-structured and unstructured data. Examples include text, images, videos and web pages.

Veracity

Veracity refers to the trustworthiness of data. Big Data may sometimes be inconsistent, biased, noisy or affected by abnormality or problems in data collection.

Value

Value refers to useful hidden patterns and knowledge in Big Data that can have business value. The potential value should be considered before investing resources in processing the data.

• Data analytics is used for informed business decisions.
• It is useful in science and technology.
• Researchers can use it to verify or disprove scientific models, theories and hypotheses.
• Pandas is a Python library that can be used to make data analysis simpler.

Examples

Smart devices such as bulbs, fans, refrigerators, microwave ovens, air conditioners, door locks and CCTV cameras can be connected to networks and controlled or accessed using computers or smartphones.

Key Points

• IoT connects smart devices.
• Devices can communicate and exchange data.
• Devices can work collaboratively.
• Smartphones can be used to remotely access and control connected devices.

IoT can require different applications for interacting with different devices. WoT provides a way of using the web to connect things together efficiently.

It can help in creating smart homes, smart offices, smart cities and so on.

Sensors are monitoring and observing elements commonly used in real-world applications. Their evolution contributes significantly to sensor-based intelligent IoT systems.

Accelerometer and Gyroscope

• Accelerometer: Detects the orientation of a mobile phone.
• Gyroscope: Tracks rotation or twisting of the hand and adds information to that supplied by the accelerometer.

Rapid urbanisation creates challenges involving land, water, waste, air pollution, health, sanitation, traffic congestion, public safety, security and city infrastructure.

Examples from the Chapter

• Smart Building: Sensors detect earthquake tremors and warn nearby buildings.
• Smart Bridge: Wireless sensors detect loose bolts, cables or cracks and alert concerned authorities through SMS.
• Smart Tunnel: Wireless sensors detect leakage or congestion and send information across sensor networks to a centralised computer for analysis.

Smart City Services

Transportation systems, power plants, water supply networks, waste management, law enforcement, information systems, schools, libraries, hospitals and other community services can work together to improve efficiency.

Cloud Resources

• Software
• Hardware / Servers
• Databases
• Storage

Key Features

• Resources are provided by cloud service providers.
• Services are usually charged on a pay-per-use basis.
• Users can access resources from anywhere through the Internet.
• Large applications or large amounts of data can be processed without having all required storage or processing power locally.
• Cloud computing provides cost-effective, on-demand resources.

(A) Infrastructure as a Service (IaaS)

IaaS provides computing infrastructure such as servers, virtual machines, storage, backup facilities, network components, operating systems and other hardware or software.

• Users can use remote hardware infrastructure.
• Infrastructure can be configured and used on demand.
• Users pay according to usage.
• It can reduce hardware, software, setup, maintenance and security costs.

(B) Platform as a Service (PaaS)

PaaS provides a platform or environment to develop, test and deliver software applications without worrying about the underlying infrastructure.

• Applications can be installed and executed on the platform.
• The user has control over the deployed application and its configuration.
• It reduces the complexity of managing underlying hardware and software.

(C) Software as a Service (SaaS)

SaaS provides on-demand access to application software, usually through licensing or subscription.

Examples mentioned in the chapter include Google Docs, Microsoft Office 365 and Dropbox.

• The user need not worry about software installation or configuration.
• The required application is accessed through the cloud.

GI Cloud — MeghRaj

The chapter states that the Government of India embarked upon the initiative called GI Cloud, named MeghRaj.

• A grid is more application-specific than cloud computing.
• It creates a sense of a virtual supercomputer with enormous processing power and storage.
• The constituent resources are called nodes.
• Different nodes temporarily come together to solve a large task and achieve a common goal.
• Existing computational resources such as memory and processing power can be reused.
• Grid computing can help solve computationally intensive scientific and research problems without procuring costly hardware.

Types of Grid

1. Data Grid: Used to manage large and distributed data requiring multi-user access.
2. CPU / Processor Grid: Processing can be moved between PCs as needed, or a large task can be divided into subtasks for parallel processing.

Grid Computing vs IaaS Cloud Service

Middleware

A middleware is required to implement the distributed processor architecture of a grid. The chapter mentions the Globus Toolkit, an open-source software toolkit used for building grids. It includes software for security, resource management, data management, communication and fault detection.

Key Points

• Blockchain uses a decentralised and shared database.
• Each participating computer or node receives a full copy of the database.
• A block can be considered a secured chunk of data or a valid transaction.
• Each block contains a header visible to other nodes.
• Private data of the block is accessible only to its owner.
• Blocks form a chain.
• The ledger is append-only.
• The blockchain is updated after the nodes in the network authenticate the transaction.

Applications Mentioned in the Chapter

• Digital currency.
• Business and governance systems.
• Healthcare data sharing.
• Land registration records.
• Voting systems.
• Banking.
• Media.
• Telecom.
• Travel and hospitality.

Important Definitions

• AI: Simulates natural human intelligence in machines.
• Machine Learning: Enables computers to learn from data using statistical techniques.
• NLP: Enables interaction between humans and computers using human languages.
• VR: A three-dimensional computer-generated situation that simulates the real world.
• AR: Computer-generated perceptual information superimposed over existing physical surroundings.
• Robot: A programmable machine capable of automatically performing tasks.
• Big Data: Enormous and complex data that is difficult to process with traditional tools.
• Data Analytics: Examining data sets to draw conclusions from the information they contain.
• IoT: Network of devices with embedded hardware and software that communicate and exchange data.
• Smart Sensor: A sensor that takes physical input, processes it using built-in computing resources and passes on the processed data.
• Cloud Computing: Delivery of computer-based services through the Internet.
• Grid: Network of geographically dispersed and heterogeneous computational resources.
• Blockchain: Connected computers maintaining a shared updated and secure ledger.

Five Characteristics of Big Data

Volume → Velocity → Variety → Veracity → Value

Cloud Service Models

IaaS → Infrastructure as a Service

PaaS → Platform as a Service

SaaS → Software as a Service

Types of Grid

Data Grid and CPU / Processor Grid

Important Differences

1. List some cloud-based services that you are using at present.
2. What do you understand by the Internet of Things? List some potential applications.
3. Write short notes on Cloud Computing.
4. Write short notes on Big Data and its characteristics.
5. Explain Artificial Intelligence along with its applications.
6. Explain Machine Learning along with its applications.
7. Differentiate between cloud computing and grid computing with suitable examples.
8. Justify: “Storage of data is cost-effective and time saving in cloud computing.”
9. What is an on-demand service? How is it provided in cloud computing?
10. Give examples of government-provided cloud computing platforms.
11. Explain how IoT concepts can be used to create a smart school.
12. How can a startup with limited infrastructure use cloud services?
13. How can blockchain technology promote accountability, transparency and efficiency in scholarship distribution?
14. How are IoT and WoT related?

• NLP Diagram: Human language ↔ NLP system ↔ Computer.
• IoT Diagram: Smartphone ↔ Internet/Network ↔ Smart Devices.
• Big Data Visual: Five characteristics — Volume, Velocity, Variety, Veracity and Value.
• Cloud Computing Visual: IaaS, PaaS and SaaS.
• Grid Computing Visual: Multiple nodes connected through a Grid Resource Management System.
• Blockchain Flowchart: Transaction request → Broadcast → Verification → Block added → Transaction complete.