We developed the web application using HTML5, CSS3, Javascript and Bootstrap. The web application contains responsive web pages for searching the 		landmark, Description of landmark, Booking page and final ticket receipt and PDF page.  

	Web Pages:

	(1.) Search/Home page 

The homepage of the website is designed using HTML and jQuery. The styling of the contents in the homepage is done using bootstrap. The homepage consists 	  of a search bar on the top from where the user can search for different tourist locations. However, it also displays all the 40 tourist locations in the 	   form of a card view so that user can have a gist of all the places that are available on the website.


	(2.) Login page 

    We have used AWS Cognito to provide login and user management capability to our application. We have used default login, sign-up and forgot password pages   	     for both android and web application. Since we are using Cognito we are able to achieve two-factor authentication and login management without writing   	      single piece of code, but once user have logged in we maintain user token which helps in user management throughout the application.   

	(3.) Description Page

   	After searching for a particular location, the user can now see a detailed view of that searched location. It gives the user a significant amount 
   	of details of the searched location. After this the user can proceed to the ticket booking part. 
  

	(4.) Booking Details Page 

The booking details page provides a interface for users to enter details related to the travel. It takes in booking information using which it can book 	ticket for user. It validates the users by calling validation service and once validated it books tickets for the user. 


	(5.) Tickets page 

    Once the payment is validated, the ticket is generated and shown to the user as below. The user can even download the ticket in the pdf form offline. 

The Cloud5409 Tourism Mobile Application follows a thin client architecture that does all the processing on the server side. The application is composed 	 of various independent modules that communicate with a specific microservice.The mobile application uses Volley library to communicate with the 		microservices. It is an HTTP library that performs basic networking operations including establishing connections and sending requests to and fro from the 	   server.

	Android App Activities:

	(1.) User Query Submission Activity:  

	This is the starting point of the application where the user will search for a specific place or landmark by submitting a query. A get request is made 		using Volley and alongside with the submitted query as endpoint. The search microservice on receiving the request prepares the response corresponding to 	 the submitted query. The response is returned in the form of JSONArray which is then populated in the dropdown menu. When the user will clicks on a 		specific item from the dropdown, the application then redirects to Landmark Information activity. 

	(2.) Landmark Information Activity:  

	This activity will be responsible for communication with the description microservice that will return the response for a particular place or landmark as 	  submitted prior by the user during search.

	(3.) User Authentication using AWS Cognito Cognito Mobile SDK:  

	Before the integrating the AWS Cognito Service into the mobile application, user-pool was created to enable sign-in and sign-up services in the android. 	 After the user pool generation on AWS Cognito, the generated Cognito client ID, Cognito Client secret, Cognito Web domain can be used to create the 		instance of Auth with the userpool configuration and android app can be pointed to hosted UI pages of AWS Cognito. After UI pages are hosted, 			authentication handler is invoked which is responsible for validating the user on successful authentication, after user has entered their credentials on 	 sign-in page or have registered themselves if they are first-time user. After the successful authentication, a unique token is created associated with the 	    user. With the generated unique token, user could then proceed for booking ticket activity.  

	We broke down the project into microservices to achieve a microservice architecture. Micorservice architecture helps the application to be loosely 		coupled,isolated, robust and scale easily when required. All the microservices are written using Python. We divided the application into following 		microservice: 


	(1.) Search service 

	The data for 40 tourist places in Canada is stored in the AWS DynamoDB. The search API is implemented in Python Flask. Whenever a user searches a 		location, then the search API running on the Docker is called. This API returns all the details of the searched location for example, name of the place, 	 id, city and the detailed description of that place. 

	(2.) Description service

	The description service provides detaisl for all the tourist places. It fetces detail of a particular location and provides these details  to user 		interface and mobile application. It communicates with dynamo database to get relevant details. 

	(3.) Validation service

	The validation service performs varios validation on fileds like card number, source location, destination location, user name, date of travel, card 		expiry month, year and cvv number of the card. If the payment details is valid the booking is done for that user. 

	(4.) Booking service

	The booking service is used for booking users ticket. It talks with dynamo database to store relevant fields and these fields can then be used to  		generate ticket which is done by the next service. 

	(5.) Ticket Generation service 

	After the payment made by the user is validated, the details of that particular user are stored in a different table in AWS DynamoDB. Ticket Generation 	API then fetches the user’s booking details from this table and returns the JSON result to the client side. This JSON response is then used to generate 	the UI of the ticket. This microservice is implemented in python Flask.  

	(6.) PDF Generation service 

	For ticket generation, we have created REST API as microservices in Spring Boot. Application has generalized template in PDF format which can be edited 	in future as per the requirements without affecting the other part of the application. To fill the PDF form programmatically in the application, we used 	 iTextPdf library in Java. All business logic in a ticket generation service API is covered with unit test. Following is the image for PDF. 

	(7.) Location service:

This API returns all the 40 tourist locations stored in the database as a JSON array. This is used to populate the card view of the all the tourist 		places on the home page. 

	(8.) Encryption/Decryption

All the communications performed between the client and cloud are secured. The encryption algorithm used in monoalphabetic cipher. Monoalphabetic cipher 	 is a substitution cipher which is based on a cipher key. The cipher alphabet for each alphabet in the plain text is fixed prior to the start of the 		encryption process. For example, if encrypted alphabet for “A” is “M” then everywhere in the plain text “A” will be substituted by “M”. The security of 	monoalphabetic cipher depends upon the secrecy of the key and hoe difficult a key is chosen.An advancement of monoalphabetic cipher is Polyalphabetic 	 	 cipher where the same alphabet is substituted by different alphabets at different places in the plain text. 

As per the requirement of the project we were able to use many cloud services provided by Amazon Web Servies. We used the umbrella service Elastic Bean 	Stalk for docker orchestration, Cognito for user management, Dynamo DB for database, Elastic Container Service for load balancing and application 		autoscaling and S3 for static file storage. 

(1.) Multicontainer for microservices:

All the micro services which we talked about in earlier section runs inside individual isolated docker environment. All the services are developed using 	 Python except two services. The PDF generation service and the UI service is built in Java and HTML respectively. All this microservice run using Elastic 	   Beanstalk (EBS). We generate a detailed configuration file, using which the EBS comes to know how many containers we have and how do deploy and run them. 	     For all the microservice we have built a Docker image which is pushed to Docker hub account. The EBS services internally uses Elastic Container Service 	     (ECS) which spawns dockers and maintains them. Docker pulls the images which we have deployed and runs it.  

(2.) AWS Cognito

AWS Cognito is a user management service provided by Amazon Web Service. It allows us to create multiple user groups so that we can allow users to 		register with our application. Amazon Cognito provides users sign-up and sign-in user to mobile and web app. One of the biggest benefits of using this 		service is that we can scale up the app as our app grows and expand to reach a wider audience.  

(3.) Amazon S3 

Amazon S3 is a simple storage service, it provides S3 bucket and Application load balancer. The S3 bucket is a static store provided by Amazon AWS, it can 	   store files that are static in nature like web pages, images, etc. The mobile application, web application and all 40 landmark information is hosted on 	   this platform, users can interact with our application by requesting for resources from S3 bucket.  

(4.) Amazon Dynamo DB 

We are using Amazon DynamoDB for our application, it is document type database with NoSql database support that provides fast and predictable performance 	  with seamless scalability. It provides infinite scalability with read-write I/O running on IOPS-optimized solid-state drives. It can support scalar, 		multi-valued and document type of data. Like relational database it can provides support for ACID properties for a transaction.