EDUCBA

EDUCBA

MENUMENU
  • Free Tutorials
  • Free Courses
  • Certification Courses
  • 360+ Courses All in One Bundle
  • Login
Home Data Science Data Science Tutorials IoT Tutorial IoT Features
Secondary Sidebar
IoT Tutorial
  • Basic
    • Introduction to IOT
    • What is IOT
    • What is IoT Technology
    • IoT Careers
    • Benefits of IoT
    • IoT Features
    • Applications of IoT
    • IoT Disadvantages
    • Uses of IoT
    • IoT Tools
    • IoT Connectivity
    • Components of IoT
    • IoT Products
    • IoT Standards
    • IoT Module
    • IoT Platform
    • IoT Companies
    • IoT in Education
    • IoT Management
    • IoT in Transportation
    • IoT Security Challenges
  • IoT Technology
    • IoT Technology
    • IoT Technologies
    • IoT Devices
    • IoT Ecosystem
    • IoT Communication Protocol
    • IoT Services
    • IoT Software
    • IoT Analytics
    • Intelligent Agents
  • MISC
    • IoT Framework
    • IoT Hardware
    • IoT in Agriculture
    • IoT Projects
    • IoT Protocols
    • IoT Security Issues
    • IoT Architecture
    • IoT Applications
    • Challenges of IoT
    • IoT Boards
    • IoT Cloud Platforms
    • ThingWorx
    • Storage Virtualization
    • Data Storage Devices
  • Interview Questions
    • IoT Interview Questions

Related Courses

IoT Certification Course

Artificial Intelligence Training Course

Machine Learning Courses

IoT Features

By Priya PedamkarPriya Pedamkar

iot features

Overview of IoT Features

Internet of Things (IoT) is a technology of connected smart devices that has incremental use cases across industries. With the increasing use across various industries, it is becoming a necessity to define a common standard of IoT ecosystems. As a design standard, any IoT device comes with some common set of features like connectivity, analytics, endpoint management, etc. Let’s discuss the high-level feature maps of IoT devices.

Features of Internet of Things (IoT)

Any IoT device comes up with the following features:

Start Your Free Data Science Course

Hadoop, Data Science, Statistics & others

All in One Data Science Bundle(360+ Courses, 50+ projects)
Python TutorialMachine LearningAWSArtificial Intelligence
TableauR ProgrammingPowerBIDeep Learning
Price
View Courses
360+ Online Courses | 50+ projects | 1500+ Hours | Verifiable Certificates | Lifetime Access
4.7 (85,992 ratings)

1. Connectivity

In the case of IoT, the most important feature one can consider is connectivity. Without seamless communication among the interrelated components of the IoT ecosystems (i.e sensors, compute engines, data hubs, etc.) it is not possible to execute any proper business use case. IoT devices can be connected over Radio waves, Bluetooth, Wi-Fi, Li-Fi, etc. We can leverage various protocols of internet connectivity layers in order to maximize efficiency and establish generic connectivity across IoT ecosystems and Industry. There may be special cases where the IoT ecosystem is built on-premises or in an intranet.

2. Sensing

We humans can naturally understand and analyze our circumstances easily based on our past experiences with various things or situations. In the case of IoT in order to get the best of it, we need to read the analog signal, convert it in such a way that we can derive meaningful insights out of it. We use Electrochemical, gyroscope, pressure, light sensors, GPS, Electrochemical, pressure, RFID, etc. to gather data based on a particular problem. For example for automotive use cases, we use Light detection sensors along with pressure, velocity and imagery sensors. To make a use case successful we need to choose the proper sensing paradigm.

3. Active Engagements

IoT device connects various products, cross-platform technologies and services work together by establishing an active engagement between them. In general, we use cloud computing in blockchain to establish active engagements among IoT components. In the case of Industry grade, IoT solutions raw analog data need to be acquired, preprocessed and rescale as per business capacity. As per Google, only 50% of structured and 1% of unstructured data is used to make important business decisions. So while designing the IoT ecosystems carriers need to consider the future needs of manipulating such a huge scale of data to satisfy incremental business needs. One can confuse the need of active engagements with scale, practically it means your systems should be able to handle huge data across various technologies, platforms, products, and industries.

4. Scale

IoT devices should be designed in such a way that they can be scaled up or down easily on demand. In general, IoT is being used from smart home automation to automating large factories and work stations, so the use cases vary in scale. A carrier should design their IoT infrastructure depending upon their current and future engagement scale.

5. Dynamic Nature

For any IoT use case, the first and foremost step is to collecting and converting data in such a way that means business decisions can be made out of it. In this whole process, various components of IoT need to change their state dynamically. For example, the input of a temperature sensor will vary continuously based on weather conditions, locations, etc. IoT devices should be designed this keeping in mind.

6. Intelligence

In almost every IoT use cases in today’s world, the data is used to make important business insights and drive important business decisions. We develop machine learning/ deep learning models on top of this massive data to obtain valuable insights. The analog signals are preprocessed and converted to a format on which machine-learning models are trained. We need to keep in mind the proper data infrastructure based on business needs.

7. Energy

From end components to connectivity and analytics layers, the whole ecosystems demand a lot of energy. While designing an IoT ecosystem, we need to consider design methodology such that energy consumption is minimal.

8. Safety

One of the main features of the IoT ecosystem is security. In the whole flow of an IoT ecosystem, sensitive information is passed from endpoints to the analytics layer via connectivity components. While designing an IoT system we need to adhere to proper safety, security measures, and firewalls to keep the data away from misuse and manipulations. Compromising any component of an IoT ecosystem can eventually lead to failure of the whole pipeline.

9. Integration

IoT integrates various cross-domain models to enrich user experience. It also ensures proper trade-off between infrastructure and operational costs.

Conclusions

The expansion and design of optimal IoT systems are still an active area of research, so in practice, not all IoT products come up with these all set of features of the standard. It mainly depends on the use cases and industry where the ecosystem needs to be incorporated. Internet of Things (IoT) is a technology of connected smart devices that has incremental use cases across industries. With the increasing use across various industries, it is becoming a necessity to define a common standard of IoT ecosystems. As a design standard, any IoT device comes with some common set of features like connectivity, analytics, endpoint management, etc. Let’s discuss the high-level feature maps of IoT devices.

Recommended Articles

This is a guide to the IoT Features. Here we discuss the overview and various most important features of an IoT ecosystem one can consider like sensing, connectivity, endpoint management, scalability, etc. You can also go through our other suggested articles to learn more –

  1. IoT Projects
  2. Salesforce IoT Cloud
  3. Learn the Top 6 IoT Cloud Platforms
  4. IoT Connectivity
Popular Course in this category
IoT Training (5 Courses, 2+ Projects)
  5 Online Courses |  2 Hands-on Projects |  44+ Hours |  Verifiable Certificate of Completion
4.5
Price

View Course

Related Courses

Artificial Intelligence AI Training (5 Courses, 2 Project)4.9
Machine Learning Training (20 Courses, 29+ Projects)4.8
1 Shares
Share
Tweet
Share
Primary Sidebar
Footer
About Us
  • Blog
  • Who is EDUCBA?
  • Sign Up
  • Live Classes
  • Corporate Training
  • Certificate from Top Institutions
  • Contact Us
  • Verifiable Certificate
  • Reviews
  • Terms and Conditions
  • Privacy Policy
  •  
Apps
  • iPhone & iPad
  • Android
Resources
  • Free Courses
  • Database Management
  • Machine Learning
  • All Tutorials
Certification Courses
  • All Courses
  • Data Science Course - All in One Bundle
  • Machine Learning Course
  • Hadoop Certification Training
  • Cloud Computing Training Course
  • R Programming Course
  • AWS Training Course
  • SAS Training Course

ISO 10004:2018 & ISO 9001:2015 Certified

© 2022 - EDUCBA. ALL RIGHTS RESERVED. THE CERTIFICATION NAMES ARE THE TRADEMARKS OF THEIR RESPECTIVE OWNERS.

EDUCBA
Free Data Science Course

SPSS, Data visualization with Python, Matplotlib Library, Seaborn Package

*Please provide your correct email id. Login details for this Free course will be emailed to you

By signing up, you agree to our Terms of Use and Privacy Policy.

EDUCBA Login

Forgot Password?

By signing up, you agree to our Terms of Use and Privacy Policy.

EDUCBA
Free Data Science Course

Hadoop, Data Science, Statistics & others

*Please provide your correct email id. Login details for this Free course will be emailed to you

By signing up, you agree to our Terms of Use and Privacy Policy.

EDUCBA

*Please provide your correct email id. Login details for this Free course will be emailed to you

By signing up, you agree to our Terms of Use and Privacy Policy.

Let’s Get Started

By signing up, you agree to our Terms of Use and Privacy Policy.

This website or its third-party tools use cookies, which are necessary to its functioning and required to achieve the purposes illustrated in the cookie policy. By closing this banner, scrolling this page, clicking a link or continuing to browse otherwise, you agree to our Privacy Policy

Loading . . .
Quiz
Question:

Answer:

Quiz Result
Total QuestionsCorrect AnswersWrong AnswersPercentage

Explore 1000+ varieties of Mock tests View more