EDUCBA

EDUCBA

MENUMENU
  • Explore
    • Lifetime Membership
    • All in One Bundles
    • Fresh Entries
    • Finance
    • Data Science
    • Programming and Dev
    • Excel
    • Marketing
    • HR
    • PDP
    • VFX and Design
    • Project Management
    • Exam Prep
    • All Courses
  • Blog
  • Enterprise
  • Free Courses
  • Login
Home Data Science Data Science Tutorials IoT Tutorial IoT Analytics

IoT Analytics

Priya Pedamkar
Article byPriya Pedamkar

Updated August 10, 2023

IoT Analytics

Introduction to IoT Analytics

In the era of the internet, where there are more than 6 billion connected devices, and petabyte-scale data is flowing in seconds, IoT or Internet of Things analytics is the next big thing. Before we discuss the analytics part, let’s look at the definition of IoT from Wikipedia ‘The Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. Now the data collected by these devices can also be used to make decisions without manual intervention or rule-based applications. Let’s discuss how they are taking place in the industry.

ADVERTISEMENT
Popular Course in this category
IOT System Course Bundle - 7 Courses in 1

Start Your Free Data Science Course

Hadoop, Data Science, Statistics & others

Why do we Use IoT Analytics and its Real-World Applications?

It is a field of data science where data from sensors and connected electromechanical systems are analyzed and converted to valuable business insights. Industry grade IoT applications are called as IIot(Industrial Internet of Things).

Let’s see the Industrial applications of IoT analytics.

1. Manufacturing Industry

It has been changing the industry landscape for manufacturing sectors. Smart sensory data are used to prevent faults or breakdowns, requirement analysis, and resource optimization. IoT solutions help organizations in smart asset management, performance monitoring, which reduces asset downtime and increases hardware longevity. It also enables manufacturers with a lower time to marketability and large-scale customizations. For example, IoT helped bike manufacturer Harley Davidson to reduce the time to produce a complete bike from days to hours.

2. Healthcare

The popularity of smart wearables is increasing day by day. This enables researchers with more and more data to incorporate IoT solutions. Data from wearables are used to prevent heart attacks. IoT-based solutions with nanotechnology are even used to monitor cancerous cells inside the body.

3. Home Automation

Switching on the air conditioner before arriving home or switching off lights from a different location is no longer science fiction, It’s already commercially available. IoT analytics is used to make decisions and optimize power consumption automatically. Google Home, Amazon echo, etc., are examples of some of the IoT-based home automation devices where analytics and machine learning are used heavily.

4. Automobile and Transportation

In the internet era, automobiles are also considered gadgets where upgrades can be made on-demand. They are being used for collision prevention, smart parking, and even for self-driving cars. The whole research area of self-driving cars is based on deep learning models based on data obtained from IoT devices like LIDERs and image sensors.

5. Insurance

As an Industry, Insurance seats on a gold mine of data, insurers slowly started adhering to analytics in their industry solutions. As per the Gartner report, it will change the industry landscape by 2020. IoT solutions can be used for automated claims processing, automated reserve setting, damage assessment, etc. In the case of automobile claims, image data based on deep learning solutions are incorporated.

6. Weather Forecast

One of the most important use cases of it is in weather forecasting. Weather stations and satellites collect atmospheric data every second. This data can be used to forecast extreme weather conditions like floods, drought much earlier. IoT solutions are also being used for automatically controlling the water levels in dams.

7. Energy Sector

It is helping energy sectors with valuable insights on power consumption, automated hardware maintenance, dynamic pricing, etc. The traditional power and energy sources and comparatively newer sectors like solar energy, wind energy, and waste recycling are getting benefited from it.

8. Telecommunication

The hardware deployment and maintenance cost for the telecommunication sector is always a pain for the telecom industry. It is helping telecom players to analyze bandwidth consumption, tower management, fault analysis, automated hardware maintenance with very little or no manual interference.

Trends

After the .com boom and the rising of connected devices, the use of it is also increasing. Let’s take a look at the worldwide google trends on IoT analytics from 2004 to 2019.

IOT Analytics Trends

Typical IoT Analytics Flow

Typical analytics use the following steps:

1. Data Collection: A collection of data from IoT sources like audio, image, light sensors. Handling streaming data is a great challenge for IoT applications.

2. Preprocessing of Data: The preprocessing of collected data is a tricky part of machine learning use cases. Suppose the feature engineering for heartbeat sensor data will be much different from the data collected in weather stations. But that’s where the art part of data science/Analytics lies.

3. Analyzing Data: Thorough exploratory data analysis is done in this step of the IoT analytics use case.

4. Train and Test: After preprocessing, and EDA, various machine learning and deep learning models are trained as per use case and business requirements. Business and technical KPIs are decided upon a case basis. Based model is chosen through cross-validation, and offline and online testing is performed.

5. Deployment and Prediction: This is the part where systems act upon the insights gathered from the analytics solution. Based on the model performance, it is retrained or recalibrated.

Deployment and Prediction

The flow of a typical IoT analytics use case.

Conclusion

This article discussed the high-level view of IoT analytics, its industrial use cases, global trends in IoT analytics, and sample workflow of an IoT analytics use case. Despite the increasing demand and applications of it, there is another face of it. The concern of privacy can not be denied at all. Strong and balanced data governance is needed to build and maintain a sustainable end-to-end IoT ecosystem.

Recommended Articles

This is a guide to IoT Analytics. Here we discuss the introduction and the use of IoT Analytics and its Real-World applications. You can also go through our other suggested articles to learn more –

  1. IoT Framework
  2. IoT Interview Questions
  3. Benefits of IoT
  4. Top 3 Disadvantages of IoT in Detailed
ADVERTISEMENT
Ai ARTIFICIAL INTELLIGENCE Course Bundle - 7 Courses in 1 | 3 Mock Tests
49+ Hours of HD Videos
7 Courses
3 Mock Tests & Quizzes
Verifiable Certificate of Completion
Lifetime Access
4.5
ADVERTISEMENT
PYTHON for Machine Learning Course Bundle - 39 Courses in 1 | 6 Mock Tests
125+ Hour of HD Videos
39 Courses
6 Mock Tests & Quizzes
Verifiable Certificate of Completion
Lifetime Access
4.8
ADVERTISEMENT
All-in-One Data Science Bundle - 400+ Courses | 550+ Mock Tests | 2000+ Hours | Lifetime |
2000+ Hour of HD Videos
80 Learning Paths
400+ Courses
Verifiable Certificate of Completion
Lifetime Access
4.7
ADVERTISEMENT
MS Excel & VBA for Data Science Course Bundle - 24 Courses in 1 | 10 Mock Tests
87+ Hours of HD Videos
24 Courses
10 Mock Tests & Quizzes
Verifiable Certificate of Completion
Lifetime Access
4.5
Primary Sidebar
Footer
About Us
  • Blog
  • Who is EDUCBA?
  • Sign Up
  • Live Classes
  • 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

© 2023 - EDUCBA. ALL RIGHTS RESERVED. THE CERTIFICATION NAMES ARE THE TRADEMARKS OF THEIR RESPECTIVE OWNERS.

EDUCBA

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

Let’s Get Started

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

EDUCBA
Free Data Science Course

Hadoop, Data Science, Statistics & others

By continuing above step, you agree to our Terms of Use and Privacy Policy.
*Please provide your correct email id. Login details for this Free course will be emailed to you

EDUCBA

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

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

Forgot Password?

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

🚀 Extended Cyber Monday Price Drop! All in One Universal Bundle (3700+ Courses) @ 🎁 90% OFF - Ends in ENROLL NOW