Travelling and seeing places is an important part of our lives. One cannot believe a place to be true unless one sees it. Anyone can visit any places around the globe but one cannot know the place he/she is going to visit is of his/her interest. This can cause major issues for the traveler. The traveler can see the photos and reviews of the place he/she going to visit but he/she have to go a tons of different platforms and website and have to ask questions to make sure he/she is going to visit the right place. This is very time consuming and take a lot of effort.
People nowadays prefer to travel only places, which are of their interest, they tend to have some prior knowledge of the place they are going to visit. The knowledge of the places can be get from social media and different travelling websites. However, when a random person travel he do not know the website to look for and social media accounts to search for. So, due to this reason he/she may not be able to explore the way he/she want to. Reviews can help to find out the latest trending places and to find out which place is best for them. Reviews affect many things of a place, it can affect the mind-set of a person visiting it, But one can travel unexpectedly that is having no knowledge of place whatsoever, There should be some mechanism to entertain all sort of travelers with proper knowledge and reviews so they can visit the places of their interests.
Travelling industry is progressing rapidly in this modern era. However, the knowledge to travel where and enjoy their valuable time is very less still. This research aids eliminate this issue. This project spots user’s interests using user’s search history with high accuracy and then suggesting places and travel routes to user. It does this process using artificial intelligence, computer vision and data mining techniques.
Firstly, a large dataset is created by mining data of travel locations from google and different websites. Then digital image processing is applied to the pictures of the dataset to obtain better quality images and computer vision algorithm to assign a particular label to all the images. That completes the data preprocessing stage of the project. Then that dataset is used to generate an artificial intelligence recommendation model using collaborative and content-based filtering. After that the frontend and backend of the project is created in react native and Node.js to produce a cross platform mobile app to provide an interface to the user.
Category on interest
Gas Stations
Guest Houses
Historical Places
Hotels
Museums
Parks
Restaurants
Shopping Malls
Swimming Pools
Tourist Attraction
The App would be creation of cross platform mobile app that will be used in iOS and ANDROID. This is mainly because of the fact that majority of people prefer to use mobile apps instead of website. First we will scrap the data then on the basis of scrap data an AI model will be created that will suggest the user the places that match their interest. We will be using maps [3] and React native platform for app creation. We will be using artificial intelligence and machine learning in the app. We believe people will use our system if they want to plan their route of traveling. It will boost the tourism potential of Pakistan and interest in traveling and tourism.
Developed by
Ibad Ur Rehman
Saeed Ahmad
Abbas Ali
People nowadays prefer to travel only places, which are of their interest, they tend to have some prior knowledge of the place they are going to visit. The knowledge of the places can be get from social media and different travelling websites. However, when a random person travel he do not know the website to look for and social media accounts to search for. So, due to this reason he/she may not be able to explore the way he/she want to. Reviews can help to find out the latest trending places and to find out which place is best for them. Reviews affect many things of a place, it can affect the mind-set of a person visiting it, But one can travel unexpectedly that is having no knowledge of place whatsoever, There should be some mechanism to entertain all sort of travelers with proper knowledge and reviews so they can visit the places of their interests.
Travelling industry is progressing rapidly in this modern era. However, the knowledge to travel where and enjoy their valuable time is very less still. This research aids eliminate this issue. This project spots user’s interests using user’s search history with high accuracy and then suggesting places and travel routes to user. It does this process using artificial intelligence, computer vision and data mining techniques.
Firstly, a large dataset is created by mining data of travel locations from google and different websites. Then digital image processing is applied to the pictures of the dataset to obtain better quality images and computer vision algorithm to assign a particular label to all the images. That completes the data preprocessing stage of the project. Then that dataset is used to generate an artificial intelligence recommendation model using collaborative and content-based filtering. After that the frontend and backend of the project is created in react native and Node.js to produce a cross platform mobile app to provide an interface to the user.
Category on interest
Gas Stations
Guest Houses
Historical Places
Hotels
Museums
Parks
Restaurants
Shopping Malls
Swimming Pools
Tourist Attraction
The App would be creation of cross platform mobile app that will be used in iOS and ANDROID. This is mainly because of the fact that majority of people prefer to use mobile apps instead of website. First we will scrap the data then on the basis of scrap data an AI model will be created that will suggest the user the places that match their interest. We will be using maps [3] and React native platform for app creation. We will be using artificial intelligence and machine learning in the app. We believe people will use our system if they want to plan their route of traveling. It will boost the tourism potential of Pakistan and interest in traveling and tourism.
Developed by
Ibad Ur Rehman
Saeed Ahmad
Abbas Ali
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