IOT - Chap 1: Introduction to IoT

Internet of Things (IOT)

is a revolutionary technology that connects everyday objects to the internet, enabling them to collect, exchange, and process data. It allows devices such as sensors, appliances, and industrial machines to communicate with each other, leading to automation, real-time monitoring, and improved efficiency. It is widely used across various industries, including smart homes, healthcare, agriculture, and manufacturing, making systems more intelligent and responsive. As IoT continues to evolve, it plays a crucial role in transforming how people interact with technology, improving convenience, productivity, and decision-making.

Things (in IoT)

These are not necessarily referring to a computer. anything, such as a device that can communicate with a network and exchange data with other devices via the network, is known to as a thing.

anywhere, anytime, in anyway and anyhow

As a whole, things are defined to be anything that can be use (5 A's)

• Creating deeper and more worthwhile connections between people.

  Most people now depend on the Internet for almost everything, and this is not expected to change any time soon.

• Converting information into knowledge in order to improve decision-making.

  Massive amounts of raw data are produced by sensors for analysis, but there is no common format for storing and processing it.

• Supplying the right person with the right information.

  We must send information to the appropriate individual if we want to learn something new and gain something from it.

• Using the appropriate technology at the appropriate time and place. Smart devices are also being used more frequently throughout our everyday lives.

Pillars of IoT

• Interconnectivity

• Interoperability

• Heterogeneity

• Complexity

• Scalability

Characteristics of IoT

Interconnectivity

IoT devices ought to be linked to the IoT infrastructure. It should always be ensured that anyone, anywhere, at any time, may connect. As an illustration, the connection between individuals using internet-enabled devices like smartphones and other gadgets, as well as the connection between Internet-enabled devices like routers, gateways, sensors, etc.

Interoperability

To enable communication between IoT devices and other systems as well as among themselves, standardized protocols and technologies are used. One of the essential elements of the Internet of Things is interoperability. It refers to the capacity for various IoT systems and devices to exchange data and connect with one another, regardless of the technology involved.

MQTT (Message Queuing Telemetry Transport)

A publish/subscribe protocol used to connect IoT devices.

CoAP (Constrained Application Protocol)

For Internet of Things devices with low resources, a lightweight communication protocol.

Bluetooth Low Energy (BLE)

A wireless communication technology that is employed by Internet of Things devices that need less power.

Wi-Fi

A wireless communication technology used by Internet of Things devices that need fast data transfer rates.

Zigbee

A wireless communication technology for Internet of Things devices that is low-power and inexpensive.

Heterogeneity.

IoT cannot exist in a homogeneous state. To function in the IoT network, it should be hybrid and support devices from many manufacturers. IoT does not belong to anyone. When several domains combine, IoT becomes a reality.

Complexity.

IoT devices should dynamically adapt to the various settings and contexts. Consider a security camera. It should be flexible enough to operate in many environments and lighting conditions (morning, afternoon, night).

Scalability.

Every day, more and more objects are being connected to the Internet of Things. An IoT setup should therefore be able to handle the enormous expansion. Because of how much data is produced as a result, it needs to be handled carefully.

• Things/Device

• Gateway

• Cloud

• Data Processing

• User Interface

Components of IoT

Things/Device.

Sensors and actuators are installed in these. In contrast to actuators, which carry out the action, sensors gather data from the environment and provide it to the gateway (as directed after processing of data).

Gateway.

Data from the sensors is sent to the __ where some form of pre-processing is also carried out. Moreover, it adds a layer of protection to the network and the data being transmitted.

Cloud.

After collection, the data is uploaded to the __ Simply said, a cloud is a collection of servers that are constantly connected to the internet.

Data Processing.

The data after being received in the cloud, __ is done. Various algorithms are applied here for proper analysis of data (techniques like Machine Learning and etc. are even applied).

User Interface.

The user's end application enables them to monitor or handle the data.

• Perception/Sensing Layer.

• Network Layer.

• Data Processing Layer.

• Application Layer.

Architecture of IoT

IoT Technical Set-up

refers to the essential components, hardware, software, and network infrastructure required to deploy and operate an IoT system. It involves multiple layers, ensuring seamless connectivity, data processing, and application integration.

Sensors.

Hardware that detects changes in the environment and translates the changes to an analog / digital format. Examples are pressure / ultrasonic range / proximity / GPS.

Gateways.

Hardware to which the sensor is connected. The gateway is responsible for preprocessing the data and providing connectivity to the stream processing system. Examples are smartphone, Raspberry PI, and Arduino

Stream Data Processing.

The process of processing event data.

Data Storage.

After the data has been processed, the raw or aggregated data has to be stored for further analysis.

Data Analysis.

Aggregate, correlate, classify, filter the data and find patterns in it.

event

in IoT refers to any significant occurrence or change detected by an IoT device or system. It represents a piece of information generated by a sensor, actuator, or software process in response to a specific condition.

event stream

is a continuous flow of events generated by multiple IoT devices over time. Instead of handling events one by one, event streams enable real-time monitoring and processing of data in a sequential and time-sensitive manner.

Processing Event Stream

involves handling continuous data flows from multiple IoT devices in real-time. The goal is to collect, analyze, and respond to incoming events efficiently.

• Sense, Analyze, Respond

There are three main approaches to processing event streams:

Event Stream Processing (ESP)

refers to the real-time processing of continuous event streams, where each event is analyzed as it arrives. The focus is on handling high-speed, high-volume data streams with minimal delay.

Complex Event Processing (CEP)

goes beyond individual event processing by analyzing multiple events from different sources to identify patterns, trends, correlations, or anomalies. It enables real-time decision-making based on event relationships

• Data Collection

• Data Transmission

• Data Preprocessing

• Data Storage

• Data Analysis

• Data Visualization

• Automated Actions and Responses

Stages of Data Processing in IoT

Stages of Data Processing in IoT

• Data Collection

IoT devices (such as sensors, RFID tags, wearables, and cameras) gather raw data from the environment. Data can include temperature, humidity, motion, GPS location, and other parameters. Example - A weather station collects temperature, humidity, and air pressure data every minute.

Stages of Data Processing in IoT

• Data Transmission

The collected data is transmitted from IoT devices to cloud servers, gateways, or edge devices using communication protocols. Wireless technologies such as Wi-Fi, Bluetooth, Zigbee, LoRa, and cellular (4G/5G) are commonly used. Example - A smart meter in a home sends electricity usage data to the utility provider via an IoT gateway using MQTT protocol.

Stages of Data Processing in IoT

• Data Preprocessing

Raw data is cleaned, formatted, and filtered to remove errors, outliers, or unnecessary information before processing. This helps reduce noise and improve accuracy. Example - A smart fitness tracker removes inconsistent heart rate readings caused by sudden movements

Stages of Data Processing in IoT

• Data Storage

Processed data is stored in databases for historical analysis, reporting, and future reference. Storage can be cloud-based (AWS, Azure, Google Cloud), on-premises, or in edge data centers. Example - A smart city traffic management system stores vehicle count and speed data in a time-series database for trend analysis.

Stages of Data Processing in IoT

• Data Analysis

IoT data is analyzed using rule-based logic, machine learning, or AI algorithms to identify patterns, anomalies, and insights. Decisions can be automated based on the analyzed data. Example - A predictive maintenance system analyzes vibration data from industrial machines and detects early signs of mechanical failure.

Stages of Data Processing in IoT

• Data Visualization

Data insights are displayed in dashboards, graphs, and reports for monitoring and user interaction. Helps in understanding patterns, trends, and system performance. Example - A smart farming dashboard shows real-time soil moisture levels, allowing farmers to make irrigation decisions.

Stages of Data Processing in IoT

• Automated Actions and Responses

Based on the processed data, IoT systems trigger automated responses or alerts. Actions can be predefined (rule-based) or dynamically decided using AI. Example - A smart irrigation system automatically turns on sprinklers when soil moisture drops below a set threshold.