Emerging Trends

Cloud-based services commonly used today include:

1. Google Drive / OneDrive / Dropbox – Cloud storage for files, photos and documents.
2. Gmail / Outlook – Web-based email services hosted on the cloud.
3. Google Docs / Microsoft 365 – Online word processing, spreadsheets and presentations.
4. YouTube / Netflix / Hotstar – Cloud-based video streaming platforms.
5. Google Classroom / DIKSHA – Cloud-based e-learning platforms.
6. WhatsApp / Telegram – Messaging apps that store media and chats on the cloud.
7. iCloud / Google Photos – Automatic cloud backup of photos and contacts.
8. Zoom / Google Meet – Cloud-based video conferencing services.

All these services allow users to access data and applications from any device connected to the internet, without needing local storage or processing power.

Internet of Things (IoT):

The Internet of Things (IoT) is a network of physical devices (things) embedded with sensors, software, and other technologies that enable them to connect and exchange data with other devices and systems over the internet — without requiring human-to-human or human-to-computer interaction.

Key idea: Everyday objects become 'smart' by being connected to the internet.

Potential Applications of IoT:

| Domain | Application |
|---|---|
| Smart Home | Smart lighting, smart locks, smart thermostats |
| Healthcare | Wearable health monitors, remote patient monitoring |
| Agriculture | Soil moisture sensors, automated irrigation systems |
| Transportation | GPS vehicle tracking, smart traffic management |
| Smart Cities | Smart parking, waste management, smart street lights |
| Education | Smart classrooms, e-attendance using wearables |
| Retail | Inventory tracking, smart shelves |
| Industry | Predictive maintenance of machines (Industrial IoT) |

Thus, IoT connects the physical world to the digital world, enabling automation and real-time monitoring across virtually every sector.

Cloud Computing:

Definition: Cloud computing is a model that allows users to access computing resources — such as servers, storage, databases, networking, software and analytics — over the internet ('the cloud') on a pay-as-you-go or on-demand basis, without owning or managing physical infrastructure.

Key Characteristics:
- On-demand self-service: Resources can be provisioned automatically without human interaction.
- Broad network access: Services are accessible from anywhere via the internet.
- Resource pooling: Resources are shared among multiple users.
- Rapid elasticity: Resources can be scaled up or down quickly.
- Measured service: Usage is monitored and billed accordingly.

Service Models:
1. IaaS (Infrastructure as a Service): Provides virtualised computing infrastructure. *Example: Amazon Web Services (AWS), Microsoft Azure.*
2. PaaS (Platform as a Service): Provides a platform for developers to build and deploy applications. *Example: Google App Engine.*
3. SaaS (Software as a Service): Provides ready-to-use software over the internet. *Example: Gmail, Google Docs, Salesforce.*

Advantages: Cost-effective, scalable, accessible from anywhere, automatic updates, disaster recovery.

Examples of Cloud Providers: Amazon AWS, Google Cloud, Microsoft Azure, MeghRaj (Government of India).

Big Data:

Definition: Big data refers to extremely large and complex datasets that cannot be processed or analysed using traditional data processing tools. It holds rich information and knowledge that can be of high business and social value.

Sources of Big Data: Social media posts, sensor data, transaction records, medical records, satellite images, log files, etc.

Five Characteristics of Big Data (5 V's):

| Characteristic | Description | Example |
|---|---|---|
| Volume | Enormous amount of data generated every second | Terabytes/Petabytes of data from social media |
| Velocity | Speed at which data is generated and processed | Real-time stock market data, Twitter feeds |
| Variety | Different types of data — structured, semi-structured, unstructured | Text, images, videos, sensor data |
| Veracity | Accuracy, reliability and trustworthiness of data | Filtering fake news or incorrect sensor readings |
| Value | Usefulness of data after processing and analysis | Business insights, medical discoveries |

Applications of Big Data: Healthcare (disease prediction), banking (fraud detection), e-commerce (recommendation systems), government (policy making), weather forecasting.

Tools used: Hadoop, Apache Spark, NoSQL databases.

Artificial Intelligence (AI):

Definition: Artificial Intelligence is the simulation of human intelligence processes by computer systems. It endeavours to make machines capable of performing tasks that typically require human intelligence, such as reasoning, learning, problem-solving, perception, and language understanding.

Goals of AI:
- To create expert systems that exhibit intelligent behaviour.
- To implement human intelligence in machines.

Branches of AI:
- Machine Learning
- Natural Language Processing (NLP)
- Computer Vision
- Robotics
- Expert Systems

Applications of AI:

| Domain | Application |
|---|---|
| Healthcare | Disease diagnosis (e.g., cancer detection), drug discovery |
| Finance | Fraud detection, algorithmic trading, credit scoring |
| Transportation | Self-driving cars (Tesla, Waymo) |
| Education | Personalised learning, intelligent tutoring systems |
| Entertainment | Netflix/YouTube recommendation engines |
| Customer Service | AI chatbots (e.g., Siri, Alexa, Google Assistant) |
| Agriculture | Crop disease detection, yield prediction |
| Security | Face recognition, surveillance systems |

Conclusion: AI is transforming every industry by automating complex tasks and enabling smarter decision-making.

Machine Learning (ML):

Definition: Machine Learning is a subset of Artificial Intelligence that comprises algorithms which enable computers to learn from data on their own, identify patterns, and make decisions or predictions — without being explicitly programmed for each task.

How it works:
$$\text{Data} \xrightarrow{\text{ML Algorithm}} \text{Model} \xrightarrow{\text{New Input}} \text{Prediction/Decision}$$

Types of Machine Learning:
1. Supervised Learning: Model is trained on labelled data. *Example: Email spam detection.*
2. Unsupervised Learning: Model finds hidden patterns in unlabelled data. *Example: Customer segmentation.*
3. Reinforcement Learning: Model learns by trial and error using rewards. *Example: Game-playing AI like AlphaGo.*

Applications of Machine Learning:

| Domain | Application |
|---|---|
| E-commerce | Product recommendation (Amazon, Flipkart) |
| Healthcare | Predicting patient readmission, medical image analysis |
| Finance | Credit risk assessment, stock price prediction |
| Social Media | Targeted advertising, content filtering |
| NLP | Language translation (Google Translate) |
| Cybersecurity | Detecting malware and intrusions |
| Autonomous Vehicles | Object detection and path planning |

Conclusion: Machine Learning allows systems to improve automatically through experience, making it one of the most powerful tools in modern computing.

Difference between Cloud Computing and Grid Computing:

| Basis | Cloud Computing | Grid Computing |
|---|---|---|
| Definition | Delivery of computing services (storage, servers, software) over the internet on demand | A network of geographically dispersed, heterogeneous computers working together to solve a large problem |
| Ownership | Resources are owned and managed by a cloud provider | Resources are contributed by multiple organisations or individuals |
| Accessibility | Accessible to anyone via the internet | Typically used within a specific organisation or research community |
| Scalability | Highly scalable — resources can be increased/decreased on demand | Less flexible; depends on available nodes |
| Payment | Pay-as-you-go model | Usually free or shared-cost model |
| Management | Centralised management by the provider | Decentralised — each node is independently managed |
| Purpose | General-purpose computing, storage, software delivery | Solving large-scale scientific or computational problems |
| Standardisation | Highly standardised services | Heterogeneous — different hardware and OS |
| Examples | Amazon AWS, Google Cloud, Microsoft Azure | SETI@home, LHC Computing Grid (CERN), BOINC |

Summary:
- *Cloud computing* is like renting a fully managed apartment — you use what you need and pay for it.
- *Grid computing* is like a cooperative where many people pool their resources to complete a massive shared task.

Justification:

The statement is true. Cloud computing makes data storage both cost-effective and time-saving for the following reasons:

Cost-Effectiveness:
1. No capital expenditure: Organisations do not need to purchase expensive physical servers, hard drives or data centres.
2. Pay-as-you-go: Users pay only for the storage they actually use, avoiding wasteful over-provisioning.
3. Reduced maintenance cost: The cloud provider handles hardware maintenance, upgrades and repairs — saving the organisation money on IT staff and equipment.
4. Economies of scale: Cloud providers serve millions of users, so the cost per unit of storage is very low.
5. No energy costs: The organisation does not pay for electricity to run and cool its own servers.

Time-Saving:
1. Instant provisioning: Storage can be allocated within minutes, unlike purchasing and setting up physical hardware which takes days or weeks.
2. Automatic backups: Cloud services automatically back up data, saving the time needed for manual backup procedures.
3. Anywhere access: Data stored in the cloud can be accessed from any device at any time, eliminating the time spent transferring files physically.
4. Automatic updates: The cloud provider handles software and security updates automatically.

Conclusion: Since cloud computing eliminates the need for physical infrastructure, reduces operational costs, and provides instant, scalable storage accessible from anywhere, it is indeed both cost-effective and time-saving.

On-Demand Service:

Definition: An on-demand service is one where a user can access and use computing resources (such as processing power, storage, software, or network bandwidth) whenever needed, without requiring prior arrangement or human intervention from the service provider.

The key idea is: *'Use what you need, when you need it, and pay only for what you use.'*

How On-Demand Service is Provided in Cloud Computing:

1. Self-Service Portal: Cloud providers offer web-based dashboards (e.g., AWS Management Console, Google Cloud Console) where users can instantly provision resources like virtual machines, databases, or storage with a few clicks.

2. Virtualisation Technology: Cloud providers use virtualisation to create multiple virtual machines on a single physical server. This allows resources to be allocated and de-allocated dynamically based on user demand.

3. Elasticity and Scalability: If a user's workload increases (e.g., during a sale on an e-commerce site), the cloud automatically scales up resources. When demand drops, resources are scaled down — all without manual intervention.

4. APIs (Application Programming Interfaces): Developers can programmatically request resources using APIs, enabling automated and instant provisioning.

5. Metered Usage: Cloud services use a metered model — usage is continuously monitored and users are billed only for what they consume (similar to electricity billing).

Example: A startup can launch a new web server on Amazon AWS within minutes by selecting the required configuration on the portal — no need to buy hardware or wait for installation.

Conclusion: On-demand service in cloud computing gives users complete flexibility and control over their resource usage, making it highly efficient and economical.

Government-Provided Cloud Computing Platforms:

1. MeghRaj (GI Cloud) — Government of India:
- Launched by the Ministry of Electronics and Information Technology (MeitY).
- Provides cloud infrastructure to various government departments and agencies.
- Aims to utilise and optimise ICT infrastructure and services in the government.
- Services include hosting of government websites, e-governance applications, and data storage.

2. NIC Cloud (National Informatics Centre Cloud):
- Provided by NIC, Government of India.
- Offers IaaS, PaaS and SaaS to central and state government departments.
- Used for hosting critical government applications.

3. DigiLocker:
- A cloud-based platform by the Government of India for storing and sharing official documents digitally (e.g., Aadhaar, driving licence, marksheets).

4. USA — FedRAMP (Federal Risk and Authorization Management Program):
- A US government programme that provides a standardised approach to cloud security for federal agencies.

Conclusion: Government cloud platforms ensure secure, cost-effective and efficient delivery of e-governance services to citizens.

Large-Scale Private Cloud Service Providers:

| Provider | Services Provided |
|---|---|
| Amazon Web Services (AWS) | EC2 (virtual servers), S3 (storage), RDS (database), Lambda (serverless computing), CloudFront (CDN) |
| Microsoft Azure | Virtual Machines, Azure Blob Storage, Azure SQL Database, Azure DevOps, Microsoft 365 |
| Google Cloud Platform (GCP) | Google Compute Engine, Google Cloud Storage, BigQuery (data analytics), Google Kubernetes Engine |
| IBM Cloud | IBM Watson (AI services), Cloud Object Storage, Kubernetes, Blockchain services |
| Salesforce | CRM software as a service, Sales Cloud, Service Cloud, Marketing Cloud |
| Oracle Cloud | Oracle Database Cloud, ERP Cloud, HCM Cloud, Analytics Cloud |

Key Services Offered by These Providers:
- IaaS: Virtual machines, storage, networking (AWS EC2, Azure VMs)
- PaaS: Development platforms, databases (Google App Engine, Azure App Service)
- SaaS: Ready-to-use applications (Gmail, Microsoft 365, Salesforce CRM)
- AI/ML Services: Amazon SageMaker, Google AI Platform, IBM Watson

Conclusion: These providers offer a comprehensive range of cloud services that cater to businesses of all sizes, from startups to large enterprises.

Correct Answer: (d) Infrastructure as a Service (IaaS)

Justification:

IaaS provides the most fundamental cloud computing resources — virtualised computing infrastructure such as:
- Virtual server provisioning (virtual machines)
- On-demand storage (block storage, object storage)
- Networking resources (firewalls, load balancers)

The company wants basic building blocks (virtual servers + storage) that can be combined and customised to deploy their own applications. This is precisely what IaaS offers — the raw infrastructure over which the company can build its own platform and run customised applications.

- PaaS would be correct if they wanted a ready-made development platform.
- SaaS would be correct if they wanted ready-to-use software.
- Application as a Service is not a standard cloud service model.

Therefore, the answer is (d) Infrastructure as a Service (IaaS).

IoT-Enabled Smart School Implementation:

(a) e-Textbooks:
- Digital textbooks can be stored on cloud servers and accessed by students on tablets, laptops or smartphones via the internet.
- IoT-enabled devices can track which chapters a student has read, how much time was spent, and suggest personalised content.
- Updates to textbooks can be pushed automatically to all devices simultaneously.

(b) Smart Boards:
- Interactive smart boards (digital whiteboards) connected to the internet replace traditional blackboards.
- Teachers can display multimedia content, videos, simulations and real-time data.
- Smart boards can be connected to student devices so notes are automatically shared.
- IoT sensors can detect the presence of students and automatically turn on/off the board.

(c) Online Tests:
- Tests can be conducted on cloud-based platforms accessible from any device.
- IoT-enabled systems can automatically distribute question papers, set timers, collect responses and evaluate answers.
- Results can be instantly shared with students, teachers and parents.
- Anti-cheating measures like facial recognition (via IoT cameras) can be implemented.

(d) WiFi Sensors on Classroom Doors:
- Sensors installed on classroom doors can detect when a student enters or exits.
- This data is sent to a central server to automatically record attendance.
- Alerts can be sent to parents if a student is absent or leaves early.
- The system can also control lighting and air conditioning — turning them on when students enter and off when they leave, saving energy.

(e) Sensors in Buses to Monitor Their Location:
- GPS sensors installed in school buses continuously transmit the bus's real-time location to a central server.
- Parents can track the bus location on a mobile app and receive alerts when the bus is near their stop.
- School administrators can monitor bus routes and ensure student safety.
- Alerts can be sent in case of route deviation or emergency.

(f) Wearables (Watches or Smart Belts) for Attendance Monitoring:
- Students wear IoT-enabled smart watches or smart belts embedded with RFID chips or Bluetooth sensors.
- When a student enters the school premises or classroom, the wearable communicates with sensors installed at entry points.
- Attendance is automatically recorded in the school's database.
- Parents receive real-time notifications about their child's arrival and departure.
- The system eliminates manual attendance, saving time and reducing errors.

Conclusion: By integrating IoT devices across all these areas, a school can become truly smart — improving learning outcomes, enhancing safety, saving resources and keeping parents informed in real time.

Using Cloud Services to Launch a Startup with Limited Budget:

The five friends can leverage cloud computing to overcome their budget and infrastructure limitations in the following ways:

1. Infrastructure as a Service (IaaS) — Instead of buying servers:
- They can rent virtual servers and storage from providers like Amazon AWS, Google Cloud or Microsoft Azure.
- They pay only for what they use (pay-as-you-go), avoiding large upfront hardware costs.
- *Example: Host their website or application on AWS EC2 instances.*

2. Platform as a Service (PaaS) — For development:
- They can use platforms like Google App Engine or Heroku to develop, test and deploy their application without managing the underlying infrastructure.
- This saves time and technical effort.

3. Software as a Service (SaaS) — For business tools:
- Instead of buying expensive software, they can use:
- Google Workspace / Microsoft 365 for email, documents and collaboration.
- Zoom / Google Meet for team meetings.
- Slack for team communication.
- Zoho / Salesforce for CRM (Customer Relationship Management).

4. Cloud Storage — For data management:
- Use Google Drive, Dropbox or OneDrive to store and share files securely without buying physical storage devices.

5. Scalability — As the startup grows:
- Cloud services allow them to scale up resources (more servers, more storage) as their user base grows, without any physical infrastructure changes.

6. Security and Backup:
- Cloud providers offer built-in security, data encryption and automatic backups, protecting the startup's data without additional investment.

Financial Benefit:
- No capital expenditure on hardware.
- Low operational costs.
- Free tiers available on AWS, Google Cloud and Azure for startups.

Conclusion: Cloud computing is ideal for startups — it provides enterprise-level infrastructure at minimal cost, allows rapid deployment, and scales with the business, enabling the five friends to focus on their product rather than IT management.

Report: Use of Blockchain Technology in Scholarship Distribution

Introduction:
Scholarship distribution by governments often suffers from problems such as corruption, delayed payments, duplicate beneficiaries, lack of transparency and middlemen siphoning funds. Blockchain technology can address all these issues effectively.

What is Blockchain?
Blockchain is a decentralised, distributed digital ledger that records transactions across a network of computers. Once a record is added, it cannot be altered or deleted, making it tamper-proof and transparent.

How Blockchain Promotes Accountability:
1. Immutable Records: Every scholarship application, approval and payment is recorded as a block in the chain. No one can alter or delete these records, ensuring complete accountability of officials.
2. Smart Contracts: Automated smart contracts can be programmed to release scholarship funds only when predefined conditions are met (e.g., student has passed the required class, income certificate is verified). This removes human discretion and reduces corruption.
3. Audit Trail: Every action taken on a scholarship application is permanently recorded with a timestamp, creating a clear audit trail for government auditors.

How Blockchain Promotes Transparency:
1. Public Ledger: All stakeholders — students, parents, schools, and auditors — can view the status of scholarship applications and disbursements on the blockchain.
2. No Middlemen: Direct transfer of funds from the government to the student's account via blockchain eliminates intermediaries who may misuse funds.
3. Verification of Documents: Student documents (income certificates, caste certificates, marksheets) can be stored on blockchain and verified instantly, preventing submission of fake documents.

How Blockchain Promotes Efficiency:
1. Faster Processing: Smart contracts automate eligibility checks and fund disbursement, reducing processing time from weeks to hours.
2. Elimination of Duplicates: Each student has a unique digital identity on the blockchain, preventing the same student from claiming multiple scholarships fraudulently.
3. Reduced Paperwork: Digital storage of all documents on blockchain eliminates physical paperwork, saving time and resources.
4. Real-Time Tracking: Students can track their application status in real time, reducing the need to visit government offices.

Example Implementation:
- Student applies online → Documents verified via blockchain → Smart contract checks eligibility → Funds automatically transferred to student's bank account → Transaction recorded permanently on blockchain → Parents/auditors can verify the transaction.

Conclusion:
Blockchain technology can revolutionise scholarship distribution by creating a system that is transparent (all transactions visible), accountable (immutable records), and efficient (automated processing). It ensures that scholarships reach the rightful beneficiaries without corruption or delay, making government welfare schemes truly effective.

Relationship between IoT and WoT:

IoT (Internet of Things):
IoT refers to a network of physical devices embedded with sensors, software and connectivity that allows them to collect and exchange data over the internet. IoT focuses on connecting devices at the network level using various communication protocols (like MQTT, Zigbee, Bluetooth, etc.).

WoT (Web of Things):
WoT (Web of Things) is an extension of IoT that focuses on integrating IoT devices with the World Wide Web using standard web technologies and protocols (such as HTTP, REST APIs, JSON, etc.).

Relationship between IoT and WoT:

| Aspect | IoT | WoT |
|---|---|---|
| Focus | Connecting physical devices to the internet | Connecting IoT devices to the Web using web standards |
| Protocols | Various (MQTT, CoAP, Zigbee, Bluetooth) | Standard web protocols (HTTP, REST, WebSockets) |
| Accessibility | Devices may use proprietary protocols | Devices are accessible via standard web browsers and APIs |
| Relationship | Foundation/infrastructure layer | Application layer built on top of IoT |

In simple terms:
- IoT is the broader concept of connecting things to the internet.
- WoT is a higher-level approach that makes IoT devices accessible and interoperable through standard web technologies.
- WoT uses IoT as its underlying infrastructure.

Analogy: IoT is like building roads (connectivity infrastructure), while WoT is like building a navigation system (web-based interface) on top of those roads to make them easily usable.

Conclusion: WoT builds upon IoT by adding a web-based layer that makes IoT devices universally accessible, interoperable and easier to integrate into web applications — thus WoT is an evolution and extension of IoT.

Matching the Columns:

| Column A | Column B |
|---|---|
| 1. You got a reminder to take medication | D. Smart Health |
| 2. You got an SMS alert that you forgot to lock the door | C. Home Automation |
| 3. You got an SMS alert that parking space is available near your block | A. Smart Parking |
| 4. You turned off your LED TV from your wrist watch | B. Smart Wearable |

Justification:

1. Smart Health (D): IoT-enabled health devices (like smart pill dispensers or health monitoring apps) send reminders to patients to take their medication at the right time — this is a Smart Health application.

2. Home Automation (C): Smart door locks connected to IoT systems can detect whether the door is locked or unlocked and send SMS alerts to the homeowner — this is a Home Automation application.

3. Smart Parking (A): IoT sensors installed in parking spaces detect whether a space is occupied or vacant and send real-time alerts to drivers about available parking — this is a Smart Parking application.

4. Smart Wearable (B): A smart wristwatch connected to IoT can control home appliances like an LED TV remotely — this is a Smart Wearable application.