AIRLINE CUSTOMER MODEL WITH AUTOMATED MESSAGE ALERT

Project Title

AIRLINE CUSTOMER MODEL WITH AUTOMATED MESSAGE ALERT

Project Area of Specialization Artificial IntelligenceProject Summary

Project Summary:

Pricing in the airline industry is often compared to a brain game between carriers and passengers where each party pursues the best rates. Carriers love selling tickets at the highest price possible — while still not losing consumers to competitors. Passengers are crazy about buying flights at the lowest cost available — while not missing the chance to get on board. All this makes flight prices fluctuant and hard to predict. But nothing is impossible for people armed with intellect and algorithms. There are two main use cases of flight price prediction in the travel industry. OTAs and other travel platforms integrate this feature to attract more visitors looking for the best rates. Airlines employ the technology to forecast rates of competitors and adjust their pricing strategies accordingly.

Project Objectives

Project Objectives:

The aim is to develop a community to facilitate people travelling both on domestic as well as international routes with better prices as well as a more predictable flight schedule.

Predict the optimal ticket purchase time.

To propose a model that recommends the user whether to buy a ticket or to wait at a particular point of time.

? Forecast ticket prices of a particular flight.

To develop a model that predicts the lowest price available for a given itinerary (a specific flight on a given route for a particular departure date). To be a bit more precise, given the current day and a specific itinerary, the model predicts the lowest prices available for consecutive days.

? Notifying the users regarding a predicted flight delay.

Flight delay is inevitable and it plays an important role in both profits and loss of the airlines. An accurate estimation of flight delay is critical for airlines because the results can be applied to increase customer satisfaction and incomes of airline agencies.

Project Implementation Method

Project Implementation:

The airline industry is considered as one of the most sophisticated industry in using complex pricing strategies. Nowadays, ticket prices can vary dynamically and significantly for the same flight, even for nearby seats in the same plane. The ticket price of a specific flight can change up to 7 times a day. Customers are seeking to get the lowest price for their ticket, while airline companies are trying to keep their overall revenue as high as possible and maximize their profit. However, mismatches between available seats and passenger demand usually leads to either the customer paying more or the airlines company losing revenue.

Data Collection:

Data collection is a systematic process of gathering observations or measurements. Whether you are performing research for business, governmental or academic purposes, data collection allows you to gain first-hand knowledge and original insights into your research problem.

Data Exploration:

The goal here is to find out more about the data and become a subject matter export on the dataset you're working with.

1. What question(s) are you trying to solve?

2. What kind of data do we have and how do we treat different types?

3. What's missing from the data and how do you deal with it?

4. Where are the outliers and why should you care about them?

5. How can you add, change or remove features to get more out of your data?

Data Visualization:

Data visualization is the practice of translating information into a visual context, such as a map or graph, to make data easier for the human brain to understand and pull insights from. The main goal of data visualization is to make it easier to identify patterns, trends and outliers in large data sets. The term is often used interchangeably with others, including information graphics, information visualization and statistical graphics.

Feature Engineering:

Feature engineering is the process of selecting, manipulating, and transforming raw data into features that can be used in supervised learning. In order to make machine learning work well on new tasks, it might be necessary to design and train better features. As you may know, a “feature” is any measurable input that can be used in a predictive model — it could be the color of an object or the sound of someone’s voice. Feature engineering, in simple terms, is the act of converting raw observations into desired features using statistical or machine learning approaches.

Feature engineering is a machine learning technique that leverages data to create new variables that aren’t in the training set. It can produce new features for both supervised and unsupervised learning, with the goal of simplifying and speeding up data transformations while also enhancing model accuracy. Feature engineering is required when working with machine learning models. Regardless of the data or architecture, a terrible feature will have a direct impact on your model.

Benefits of the Project

The tourism industry is changing fast and this is attracting a lot more travelers each year. The airline industry is considered as one of the most sophisticated industry in using complex pricing strategies. Now-a-days flight prices are quite unpredictable. The ticket prices change frequently. Customers are seeking to get the lowest price for their ticket, while airline companies are trying to keep their overall revenue as high as possible. Using technology it is actually possible to reduce the uncertainty of flight prices. So here we will be predicting the flight prices using efficient machine learning techniques.

Technical Details of Final Deliverable

• A booking system which takes into account the concepts of probability and statistics and machine learning algorithms to analyze the parameters which affect the flight prices and delays.
• The operating system will be connected with a peripheral device which would be a fingerprint scanner for the authentication of the customers. The fingerprint scanner would be integrated with the booking system.
• A circuitry comprising of Arduino and GSM module for One Time Passwords (OTP) and to notify the customers about predicted flight delays.

Final Deliverable of the Project HW/SW integrated systemCore Industry TransportationOther IndustriesCore Technology Artificial Intelligence(AI)Other TechnologiesSustainable Development Goals Decent Work and Economic Growth, Industry, Innovation and InfrastructureRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	31500
Arduino Boards	Equipment	2	750	1500
GSM modules	Equipment	2	15000	30000