This topic generally belongs to weather forecasting, how we will implement Big Data computing for future weather prediction so that weather Related Flight Delays get minimized.

1. Big Data To Avoid Weather
Related Flight Delays
Guided by: Presented by:
Mr. Saurav Joshi, Akshat Giri,
Birla Institute Of Applied Sciences, ECE, B.Tech (4th year)
Bhimtal Birla Institute Of Applied Sciences,
Bhimtal

2. OUTLINES
 Introduction
 Big Data
 Why we need Big Data
 Problem with big data
 Objectives and planned Outcomes
 Problem
 Existing Methods
 Brief Work
 Data Mining In Big Data
 Implementation of technology
 Application of Big Data
 Conclusion
 References

3. INTRODUCTION
 This topic generally belongs to weather forecasting, how we will
implement Big Data computing for future weather prediction so that
weather Related Flight Delays get minimized.
 We will see Following Concepts in this session:
• What Is Big Data ?
• How will we use Big Data Computing Method for Future
Weather Prediction ?

4. Big Data
 Big Data is defined as data that is huge in size.
 Examples : stock exchanges, social media sites, etc.
 WHY THE DATA IS SO BIG?
• Increase in number of people in online platforms is one of the
cause.
• Over 2.5 quintillion bytes of data are created every single day,
and it's only going to grow.

5. WHY WE NEED BIG DATA ?
 As we know, Data is the new currency for the future. Data is what
is driving everything.
 For every domain , there should be large amount of data to be
used for new development.
 For solving Business problems, etc..

6. PROBLEMS WITH BIG DATA
 The main problem is to handle such large amount of data and it is
very difficult to analyze
 Processing Data is a big deal as real world data are very
complex.
 It is very expensive

7. Application OF BIG DATA
 Customer purchase habits Analysis
 Improve company revenue and lower costs
 Market analysis
 Fraud detection

8. OBJECTIVES
 The chief goal is to enable airlines to anticipate and deal with
delays before they happen.
 Big Data Management System Provides Weather Companies to
get previous decades weather trends and patterns. By analyzing
these Large Data Sets, Weather predictions are becoming more
accurate and being quicker

9. PROBLEM
 As we know because of bad weather everyday lots of Flights get
canceled or delayed around the world.
 Delays are costly for airlines as well as for the passengers. In
2010 study commissioned by USA’s Federal Aviation
Administration estimated that flight delays cost the airline industry
$8 billion a year. Delays cost passengers even more — nearly
$17 billion.

10. EXISTING METHOD
 Prediction of Weather through Satellite is most commonly used
method of weather prediction.
Problem
 A seven-day and five-day forecast can be accurate to some
extant. However, a 10-day or longer forecast is only right about
half the time.
Solution
 Big Data Computing method will overcome this limitation of
Satellite system , So that future weather become easy to predict.

11. BRIEF WORKING
Research In The University Of Michigan
 The students from the University of Michigan started a research
which helps in understanding the weather of a particular place.
 They've gathered more than 10 years of hour-by-hour weather
observations and domestic flight data, and are using advanced
data analytics to spot patterns and help airlines manage more
efficiently
 This is a very creative and new process. It could lead to
understanding similarities in the weather in the past years. It
could be of help in predicting the weather in the future. With the
help of this data, the flights can be cautious of bad weather in
advance.

12. BRIEF WORKING
Research In The University Of Michigan

13. DATA MINING IN BIG DATA
 Generally, data mining is the process of analyzing data from
different perspectives and summarizing it into useful information -
information that can be used to increase revenue, cuts costs, or
both.
 Data mining software is one of a number of analytical tools for
analyzing data. It allows users to analyze data from many
different dimensions or angles, categorize it, and summarize the
relationships identified.
 Technically, data mining is the process of finding correlations or
patterns among dozens of fields in large relational databases.

14. IMPLEMENTATION OF
TECHNOLOGY
STEP BY STEP OPERATION
 Data Collection
 Pre-processing
 Data Mining
 Prediction of Future Weather using ANN by Back Propagation
Algorithm
 Classification

15. Continue…..
 Data Collection: First of all Data is collected from different
platforms like satellite, ground sensors, etc.
 Data Pre – processing: Now that data is collected, Data
preprocessing takes place : removing unwanted data, missing
data management, feature engineering, etc.
 Back propagation : In order to perform a Back Propagation
Algorithm a program or logic has to be created. What will be the
change on other parameters by changing any one parameter,
will be observed.
 Classification: At last, what will be the weather in future after
some period, the Classification method will take place. In
Classification method, whether it will be sunny day, rainy or
cloudy day what will be the change in wind speed, humidity etc
is predicted.

16. DATA FLOW DIAGRAM

17. CONCLUSION
 10 years from now the Aviation industry will be much bigger.
Therefore, travelling in Airplanes will become more cheaper, large
amount of people will travel in airplanes, this will leads to the
difficulties for the Airport management if any delay occur due to
the weather.
 I think this technology will enable passengers as well as airlines
to better manage the whole travel process. We will see fewer
delays and a less stressful travel experience in the years to
come.

18. REFERENCES
 https://news.umich.edu/how-big-data-could-reduce-weather-
related-flight-delays/
 https://www.dummies.com/programming/big-data/data-
science/big-data-and-weather
 https://www.nationalgeographic.com/environment/urban-
expeditions/transportation/air-travel-fuel-emissions-environment/ -
forecasting/

19. THANK YOU!