Bohao Zhang

Our solution is to rethink the role of a navigation app in traveling. We believe it is not only a tool that shows the user the fastest way from point A to B but recreates an adventure with serendipity. Users input their destination and a type of adventure they like. Our algorithm creates a fully featured itinerary that fulfills their needs based upon their personalities. Using Machine Learning, we can generate truly personalised adventures at the click of a button Mapbox and Yelp API. We need at least 70 initial users to feed the algorithm so it can make basic predictions including planning sightseeing and going to a restaurant for our users. Before our first release, Kaleido will obtain the necessary needs of users and quantify them in a tangible way in our algorithm.
The core of our algorithm is to understand and predict people’s familiar needs in an unfamiliar situation. We are proceeding with user testing and insight analysis. We have got so many factors that could affect the prediction of serendipitous travel experience. They could be gender, safety, previous ratings, stamina, weather, and personalities. However, in this early stage, we start by suggesting restaurants and sightseeing locations. I anticipate the start of Kaleido’s service in London for three months and expand the service in major European cities by the end of 2021.

By the end of 2017, tourism represents 292 million jobs and 10.2 percent of global GDP, and the number will keep growing in the long run. If travellers spread out around the world evenly, the industry will be easier to absorb, and travellers will also have a better experience.