IOT

1. Internet of Tings (IOT)
Unit VI

2. What is an Internet of Things (IoT)

3. • Definition: IoT is the connection of everyday objects, devices, and systems
to the internet, enabling data collection and exchange without human
interaction.
• Components: IoT devices contain sensors, software, and connectivity
features to gather and transmit data.
• Interconnectivity: IoT devices communicate with each other to provide
seamless integration and functionality.
• Data Collection and Analysis: IoT systems collect data from sensors and
analyze it to extract insights for decision-making.
• Automation and Control: IoT enables automation of processes and remote
control of devices based on collected data.
• Applications: IoT applications span various industries and domains, including
smart homes, healthcare, agriculture, transportation, and manufacturing.

4. • Advanced Automation and Analytics: IoT leverages technologies like
artificial intelligence, sensors, networking, electronics, and cloud messaging
to deliver comprehensive systems for products or services.
• Transparency, Control, and Performance: IoT systems offer greater
transparency into operations, enhanced control over devices and processes,
and improved performance through data-driven insights and automation.
• Cloud Platform Integration: IoT utilizes cloud platforms to store and
manage data, enabling seamless connectivity and control of interconnected
devices and systems.
• Smart Home Integration: In a smart home scenario, IoT enables the
connection of various appliances, such as air conditioners and lights,
allowing them to communicate with each other and be managed centrally
through a cloud-based platform.
• Car Connectivity: IoT extends to vehicles, enabling connectivity features
such as tracking fuel levels, monitoring speed, and tracking the location of
the car in real-time.

5. Example
Controlling Room Temperature

6. How does Internet of Thing (IoT) Work?

7. Use of the IoT concept for streetlights in a city.

8. • Device Interaction: IoT devices, such as smartphones, smartwatches, sensors, and electronic appliances,
securely communicate with each other and with IoT platforms. These devices are equipped with sensors and
connectivity features that allow them to collect data and transmit it over the internet.
• Data Collection: IoT devices continuously collect data from their surroundings or from user interactions. This
data can include environmental information, usage patterns, health metrics, and more. The collected data is
then transmitted to the IoT platform for further processing and analysis.
• Data Processing and Analysis: The IoT platform receives data from multiple devices and performs data
processing and analysis tasks. This may involve identifying patterns, detecting anomalies, and extracting
valuable insights from the data. Advanced technologies such as artificial intelligence and machine learning may
be employed to analyze the data efficiently.
• Data Transfer and Integration: After processing the data, the IoT platform transfers the most valuable insights
or actionable information to various applications or devices. This information can be used to trigger automated
actions, provide real-time alerts, or generate personalized recommendations.
• Application Integration: The processed data is integrated with applications or services that can utilize the
insights for various purposes. These applications may include smart home control systems, healthcare
monitoring apps, industrial automation software, and more. By integrating with applications, IoT enables
seamless interaction and automation across different domains.
• Feedback Loop: IoT systems often incorporate a feedback loop mechanism, where the actions taken based on
the processed data are monitored and evaluated. This feedback loop helps improve the accuracy and
effectiveness of future decisions and actions

9. Features of IOT
• Connectivity: Establishing connections between IoT devices and platforms,
enabling reliable and secure communication for data exchange.
• Analyzing: Real-time analysis of collected data to derive insights and build
effective business intelligence for informed decision-making.
• Integrating: Integration of various models and technologies within IoT to
enhance user experience and overall system functionality.
• Artificial Intelligence: Incorporating AI to make IoT devices smart and enable
them to make autonomous decisions, such as ordering supplies when needed.
• Sensing: Utilizing sensor devices to detect and measure changes in the
environment, enabling the transformation of passive networks into active
networks.
• Active Engagement: Facilitating active engagement between connected
technologies, products, or services to enhance functionality and user
interaction.
• Endpoint Management: Ensuring proper management of IoT endpoints to
prevent system failures and address potential issues, such as automatically
ordering supplies when the user is absent.

10. Architecture of Internet of Things (IoT)

11. • Sensing Layer – The sensing layer is the first layer of the IoT architecture and is
responsible for collecting data from different sources. This layer includes sensors and
actuators that are placed in the environment to gather information about temperature,
humidity, light, sound, and other physical parameters. These devices are connected to the
network layer through wired or wireless communication protocols
• Network Layer – The network layer of an IoT architecture is responsible for providing
communication and connectivity between devices in the IoT system. It includes protocols
and technologies that enable devices to connect and communicate with each other and
with the wider internet. Examples of network technologies that are commonly used in IoT
include WiFi, Bluetooth, Zigbee, and cellular networks such as 4G and 5G
• Data processing Layer – The data processing layer of IoT architecture refers to the
software and hardware components that are responsible for collecting, analyzing, and
interpreting data from IoT devices. This layer is responsible for receiving raw data from
the devices, processing it, and making it available for further analysis or action. The data
processing layer includes a variety of technologies and tools, such as data management
systems, analytics platforms, and machine learning algorithms. These tools are used to
extract meaningful insights from the data and make decisions based on that data

12. • Application Layer – The application layer of IoT architecture is the
topmost layer that interacts directly with the end-user. It is
responsible for providing user-friendly interfaces and functionalities
that enable users to access and control IoT devices.
• This layer includes various software and applications such as mobile
apps, web portals, and other user interfaces that are designed to
interact with the underlying IoT infrastructure. It also includes
middleware services that allow different IoT devices and systems to
communicate and share data seamlessly.
• The application layer also includes analytics and processing
capabilities that allow data to be analyzed and transformed into
meaningful insights. This can include machine learning algorithms,
data visualization tools, and other advanced analytics capabilities.

13. IoT Conceptual Framework
• The following equation describes a simple conceptual framework of
IoT:
• Physical object + Controller,Sensor and Actuators + Internet =
Internet of Things
• IoT consists of an internetwork of devices and physical objects
wherein a number of objects can
• gather the data at remote locations and communicate to units for
managing, acquiring, organizing
• and analyzing the data in the processes and services.
• The equation below conceptually represents the actions and
communication of data at successive
• levels in IoT consisting of internetworked devices and objects.

14. • Gather + Enrich + Stream + Manage + Acquire + Organise and
Analyse = Internet of Things with connectivity to data centre,
enterprise or cloud server
• The above equation is an IoT conceptual framework for the
enterprise processes and services based on a suggested IoT
architecture given by Oracle. The steps are as follows:
• 1. At level 1 data of the devices (things) using sensors or the
things gather the pre data from the internet.
• 2. A sensor connected to a gateway, functions as a smart
sensor(with computing and communication capacity). The data
then enriches at level 2, for example by transcoding at the
gateway. Transcoding means coding or decoding before data
transfer between two entities.
• 3. A communication management subsystem sends or receives
data streams at level3

15. • Device management, identity management
and access management subsystems receive
the
• device’s data at level 4.
• 5. A data store or database acquires the data
at level 5.
• 6. Data routed from the devices and things
organizes and analyses at level 6. For example,
• data is analyzed for collecting business
intelligence in business processes

16. • Device management, identity management and
access management subsystems receive the
device’s data at level 4.
• 5. A data store or database acquires the data at
level 5.
• 6. Data routed from the devices and things
organises and analyses at level 6. For example,
data is analysed for collecting business
intelligence in business processes.

17. Gather + Consolidate + Connect + Collect + Assemble + Manage
and Analyse = Internet of Things with connectivity to cloud
server
• Equation represents a complex conceptual framework for IoT using cloud-
platformbased processes and services. The steps are as follows:
• Levels 1 and 2 consist of a sensor network to gather and consolidate the
data. First level gathers the data of the things (devices) using sensors
circuits. The sensor connects to a gateway. Data then consolidates at the
second level, for example, transformation at the gateway at level 2.
• The gateway at level 2 communicates the data streams between levels 2 and
3. The system uses a communication-management subsystem at level 3.
• An information service consists of connect, collect, assemble and manage
subsystems at levels 3 and 4. The services render from level 4.
• Real time series analysis, data analytics and intelligence subsystems are also
at levels 4 and 5. A cloud infrastructure, a data store or database acquires
the data at level 5.

19. IoT ARCHITECTURAL VIEW

20. Oracle suggested IoT architecture

21. An architecture has the following features:
• The architecture serves as a reference in applications of IoT in services
and business processes.
• A set of sensors which are smart, capture the data, perform necessary
data element analysis and transformation as per device application
framework and connect directly to a communication manager.
• A set of sensor circuits is connected to a gateway possessing separate
data capturing, gathering, computing and communication capabilities.
The gateway receives the data in one form at one end and sends it in
another form to the other end.
• The communication-management subsystem consists of protocol
handlers, message routers and message cache.
• This management subsystem has functionalities for device identity
database, device identity management and access management.
• Data routes from the gateway through the Internet and data centre to
the application server or enterprise server which acquires that data.
• Organization and analysis subsystems enable the services, business
processes, enterprise integration and complex processes

22. TECHNOLOGY BEHIND IoT
• Device Platform:
• This is the foundation of IoT, consisting of
hardware components like microcontrollers
(e.g., Arduino, Raspberry Pi) and software (e.g.,
RIOT OS, Contiki OS) that enable devices to
gather data, process it, and communicate with
other devices or the cloud.
• Development environments (IDEs) facilitate the
creation of firmware and APIs for these devices.

23. • Connecting and Networking:
– Encompasses various communication protocols (e.g., ZigBee,
Bluetooth, WiFi) and network technologies (e.g., Powerline Ethernet,
6LowPAN) that facilitate connectivity between IoT devices and the
internet.
– These protocols and circuits enable devices to interconnect and
communicate efficiently, forming the backbone of IoT networks.
• Server and Web Programming:
– Involves the development of server-side applications and web
services that handle data received from IoT devices.
– These applications process, store, and manage data, providing
interfaces for users and other systems to interact with IoT devices and
their data.

24. • Cloud Platform:
– Cloud platforms (e.g., AWS IoT, Azure, IBM BlueMix) provide scalable
storage, computing resources, and services tailored for IoT
applications.
– They enable data storage, analysis, and processing at scale, offering
tools for prototype and product development in the IoT space.
• Online Transactions Processing and Analytics:
– Involves the processing of transactions, data analytics, and knowledge
discovery to derive insights from IoT-generated data.
– Machine learning algorithms and software (e.g., GROK from Numenta
Inc.) play a crucial role in analyzing streaming data, detecting
anomalies, and driving actions based on insights gained from IoT
data.

25. Server-end Technology
• IoT servers are application servers, enterprise servers, cloud
servers, data centres and databases. Servers offer the
following software components
• Online Platforms:
• Online platforms serve as the foundation for hosting IoT
applications and services. These platforms provide the
necessary infrastructure, such as computing resources,
storage, and networking, to deploy and manage IoT solutions.
• They often include features for scalability, reliability, and
security to support the diverse requirements of IoT
deployments.

26. • Device Identification and Identity Management:
• IoT servers handle device identification and manage their identities
within the system. This involves assigning unique identifiers to devices,
managing device credentials, and enforcing access control policies.
• Identity management ensures that only authorized devices can access
resources and services within the IoT network, enhancing security and
protecting against unauthorized access.
• Data Processing and Analysis:
– IoT servers are responsible for collecting, aggregating, integrating,
organizing, and analyzing data generated by IoT devices. This includes
processing data streams in real-time, storing data for historical analysis, and
performing advanced analytics to derive insights.
– Data processing and analysis enable organizations to extract valuable
information from IoT data, identify trends, detect anomalies, and make data-
driven decisions to optimize operations and improve efficiency.
• Web Applications, Services, and Business Processes:
– IoT servers host web applications and services that provide user interfaces
for interacting with IoT systems. These applications enable users to monitor
devices, access data, configure settings, and initiate actions remotely.

27. Major Components of IoT System
• Major components of IoT devices are:
• 1) Physical object with embedded software into a hardware.
• 2) Hardware consisting of a microcontroller, firmware, sensors,
control unit, actuators and communication module.
• 3) Communication module: Software consisting of device APIs
and device interface for communication over the network and
communication circuit/port(s), and middleware for creating
communication stacks using 6LowPAN, CoAP, LWM2M, IPv4,
IPv6 and other protocols.
• 4) Software: for actions on messages, information and
commands which the devices receive and then output to the
actuators, which enable actions such as glowing LEDs, robotic
hand movement etc.

28. Sensors and Control Units
• Sensors are electronic devices that detect and measure physical phenomena
in the environment.
• They play a crucial role in IoT by providing data inputs for monitoring and
controlling various aspects of the physical world.
• Sensors can measure a wide range of parameters including temperature,
pressure, humidity, light intensity, proximity, acceleration, GPS signals,
magnetic fields, and more.
• There are two main types of sensors:
– Analog Sensors: These sensors provide continuous analog signals as output, which
represent the measured physical quantity. Examples include thermistors,
photoconductors, pressure gauges, and Hall sensors.
– Digital Sensors: These sensors provide digital outputs, typically in the form of binary
data, to the control unit. Examples include touch sensors, proximity sensors, metal
sensors, traffic presence sensors, encoders for measuring angles and displacements,
etc.

29. • Control Units:
• Control units, often comprising Microcontroller Units (MCUs) or custom
chips, are responsible for processing sensor data and controlling
connected devices in IoT systems.
• Microcontrollers, such as ATmega, ARM Cortex, and LPC series, are
commonly used control units in IoT applications.
• An MCU integrates a processor, memory, and various hardware units
necessary for interfacing with sensors and actuators, as well as for
executing control algorithms.
• Key components of an MCU include firmware, timers, interrupt
controllers, functional IO units, and application-specific circuits such as
Analog to Digital Converters (ADC) and Pulse Width Modulators (PWM).
• Control units receive data from sensors, process it based on predefined
algorithms or logic, and initiate appropriate actions or responses to
control the connected devices.