The platform integrates weather condition crawler, air quality prediction and personalized travel recommendation technology to bring users a good travel quality and enhance innovative functions such as air pollution. In addition, by combining functions of travel medical treatment, users could quickly search for nearby medical units if they are not familiar with the local map.

In this project, the proposed techniques are summarized as follows.
1. Air quality predictor: The air quality can be predicted by techniques of regression and Long Short Term Memory Network. According to the predicted air quality, the traveler health can be protected.
2. Personalized tourism recommendation: This is performed by user-based collaborative filtering using user content such as profile.

The proposed techniques mainly includes air quality prediction and 
personalized tourism recommendation. It can be used in the following applications.
1.In terms of air quality prediction, it is applicable for all learning places to protect the students’ health. 
2.In terms of personalized tourism recommendation, in addition to the related travel commercial stores, this technique can widely be used in other product recommendation applications.