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• IoT device refers to a network of physical objects with sensors, software, and other technologies that connect and exchange data with other devices via the internet.
• IoT devices range from ordinary household objects to industrial tools, connecting everyday items like smartwatches, smart TVs, and cars to the internet through embedded devices.

Applications of IoT

• IoT can be applied in various sectors, including:
• Agriculture
• Asset tracking
• Energy
• Safety and security
• Defense
• Embedded applications
• Education
• Healthcare
• Telemedicine
• Smart city initiatives

Characteristics of IoT

• Connectivity: IoT ensures anyone, anywhere, anytime connectivity.
• Intelligence and Identity: Knowledge extraction from generated data is crucial, and each IoT device has a unique identity for tracking.
• Scalability: The increasing number of connected devices requires appropriate handling.
• Dynamic and Self-Adapting: IoT devices adapt dynamically to changing contexts and scenarios.
• Architecture: IoT architecture should be hybrid, supporting products from different manufacturers to function within the IoT network.
• Safety: IoT prioritizes safety, addressing concerns related to sensitive personal details and equipment when connected to the internet.

Things in IoT

• "Things" in IoT refers to a variety of devices capable of exchanging data with other connected devices.
• Data can be stored in a centralized server (cloud), processed, and control actions initiated. Devices involved in this process are known as "Things".
• Thing = Hardware (h/w) + Software (s/w) + Service

Examples of "Things"

• Industrial motors
• Wearables (e.g., smartwatches)
• Shoes
• Heart monitoring implants (e.g., pacemakers)

IoT Stack

• The IoT stack has clearly defined layers:
• Layer 7: Application Layer
• Layer 6: User Experience Layer
• Layer 5: Session Layer
• Layer 4: RF Layer
• Layer 3: H/W Interface Layer
• Layer 2: Processing and Control Layer
• Layer 1: Sensor Layer

Layer 1: Sensor Layer

• Concerned with physical components, mainly sensors.
• Responsible for data collection.
• Sensors form the core component of this layer.
• Examples include temperature, pressure, and humidity sensors.

Layer 2: Processing and Control Action Layer

• Comprises core components for IoT.
• Processes data collected from sensors.
• Microcontrollers (µC) are used to determine if the data is meaningful.
• The µC or processors are found in this layer.
• µC receives data from the sensors.

Layer 3: H/W Interface Layer

• Involves handshaking.
• Includes hardware components and communication standards like RS232, CAN, SPI, occupy this layer.
• All components ensure flawless communication.
• CAN (Controlled Area Network Protocol) is used for microcontroller devices.
• SPI (Serial Peripheral Interface) is used in embedded systems for short-distance wired communication between integrated circuits (ICs).

Layer 4: RF Layer

• The protocol used for communication and transport of data based on RF is listed in this layer.
• Common protocols include WiFi, NFC, RFID, and Bluetooth.
• This layer can include LiFi as an effective alternative to RF protocols.
• NFC (Near Field Communication) provides short-range wireless communication.
• RFID (Radio Frequency Identification) is used for identification.

Layer 5: Session/Message Layer

• Session management is as important in IoT as it is in general networking, guided by the OSI layer.
• Protocols oversee how messages are broadcasted to the cloud.
• Includes messaging protocols like MQTT and COAP.
• MQTT (Message Queuing Telemetry Transport)
• COAP (Constrained Application Protocol)

Layer 6: Used Experience Layer

• Fully concerned with the end-user experience.
• Should include object-oriented programming languages and scripting languages.
• Showcase rich UI features and designs to provide a pleasing experience while using the service.

Layer 7: Application Layer

• Focuses on possible applications built with support from the other layers.
• Can range from simple automation to smart city applications.

IoT Enabling Technologies

• IoT is a collection of many technologies and devices.
• The simplest of sensors, embedded systems, data analytics, mobile internet security aspects, and protocols involving cloud storage have all become enabling technologies.
• Enabling technologies fall under categories like:
• Technologies that help in acquiring/sensing data.
• Technologies that help in analyzing/processing data.
• Technologies that help in taking control action.
• Technologies that help in enhancing security/privacy.

Sensors

• Sensors are at the heart of any IoT application.
• They sense the environment and retrieve data.
• They are the starting point of any IoT application.

Cloud Computing

• Cloud serves as an affordable, effective, and efficient medium for data storage.
• Cloud services are categorized as follows:
• IaaS (Infrastructure-as-a-Service)
• Provides virtualized computing resources over the internet.
• Users manage machines, select OS and applications, and pay for use.
• PaaS (Platform-as-a-Service)
• Cloud service provides hardware and software tools needed for application development to users over the internet.
• Users build, manage, and maintain applications as per requirements.
• SaaS (Software-as-a-Service)
• A complete software application is provided to the user.
• Availed through monthly or yearly subscriptions.

Big Data Analytics

• IoT collects data from various sensor nodes, and handling this massive data is fundamental for application success.
• Data is everywhere and is obtained from every function of operation.
• Governed by the following 4 Vs of big data:
• Volume:
• Huge volume of data is generated every minute.
• Cloud storage and hardware storage have become affordable storage solutions.
• Variety:
• Data no longer comes from a single source.
• Data is in different formats and must be interpreted systematically.
• Velocity:
• The rate at which new data is created.
• The rate at which data is generated is very fast.
• Veracity:
• The data's nature alters dynamically and ambiguity is often seen.

Embedded Computing Boards

• An important component to bring IoT design to reality.
• Examples include:
• Raspberry Pi
• Arduino
• Node MCU

Communication Protocols

• Protocols are the pillars for good IoT infrastructure and are very important in communication.

IoT Challenges

• Building an IoT application involves many technical and non-technical challenges.
• Security:
• With many devices used in IoT, user data becomes vulnerable to theft.
• Privacy:
• One could be tracked/monitored by anyone with internet access.
• Data extraction with consistency from complex environments
• Sensing data from complex environments is a significant challenge.
• Internet availability 24/7 may not be easy.
• Data extraction and storage in the cloud can be challenging.

IoT Levels

• Based on the architectural approach, IoT can be classified into 5 levels (Level 1 to Level 5).

Level 1

• Minimal complexity and easiest to build.
• Application has one sensor (a device to sense), e.g., a temperature or pressure sensor.
• Data sensed is stored, and analysis is done locally.
• The data generated in this level of applications is not huge.
• Based on analysis, the control action can be triggered through a mobile application.

Level 2

• Data is more voluminous, and cloud storage is preferred.
• Frequency of sensing done by the sensor is fast.
• More frequent sensing compared to Level 1.
• Analysis is carried out locally, while the cloud is meant for storage only.
• Sensors read room temperature with better pace and data than Level 1, then data goes to the cloud for storage.

Level 3

• Data is voluminous, frequency of sensing done by the sensor fast, and data stored on the cloud.
• Analysis is carried out on the cloud.

Level 4

• Multiple independent nodes are present.
• Nodes upload data to the cloud.
• All sensors upload the dead sensory data.
• Cloud storage preferred as data is huge.
• Analysis is carried out on the cloud, and based on the analysis, contraction occurs.

Level 5

• The amount of data is extensive and dense so multiple nodes involved in application Categorized under Level 5 and these nodes are independent of each other.
• For applications completely cloud-oriented, it is computationally intensive in real-time.
• Based on the data analysis, control actions can be triggered through web or mobile applications.