Human-to-Human Real-Time helper


Since a lot of Chinese immigrants come to this beautiful land and the huge difference between eastern and western culture, new immigrants usually have various kinds of troubles after arrival. The motivation of our application on Android smart phone is based on this scenario. We want to provide a “help app” for new Chinese immigrants to help them get well with surroundings in Auburn.


It is common that new Chinese immigrants are always not very good at speaking English, we want to build a face-to-face communication between customers. Let us assume that one day a new immigrant comes to United States for only one week and, unfortunately, his wallet and the important identify documentation are lost. Even though the policemen can tell him how to handle with this situation, he's still unable to deal with this scenario successfully as a result of a lack of understanding from the policemen. Here our app works. That new immigrant can just log in our app and request a service of finding other Chinese immigrants who are just around him. For that case, those candidates we select would be really helpful and just help them to translate from English to Chinese. Furthermore, if the candidates are very friendly and kindly, they may just take that new immigrant to that specific office to solve this type of issues. As you can imagine, our app really makes an impact on new immigrants' lives.

Figure 1

Figure 2

Figure 3

Figure 4

Our whole system is based on Android platform which is implemented in a lot of smart phones, such as Samsung and HTC. It is in B/S mode in which our client side is installed in customers' smart phone while the server is set in the cloud cluster. The major and significant service shown in Figure 1 that our system would provide is to the real-time help for our customers. As long as the customer becomes the member of our system, he is able to request this service by filling a simple form which contains basic description of the help he needs and the category that service belongs to. According to the information provided by the customer, our system would search our database to find the optimal candidates who is around that that target customer and is capable of reaching him soon. Figure 2 indicates the algorithm we implemented to select optimal candidates. Furthermore, the level of English speaking and the living of years are another two major factors when we consider the optimal candidates. Later after a set of optimal candidates are found, our system would just show the candidates' locations intuitively on the Google map on his smart phone finished by the part of system shown in Figure 3. Now the customer is able to just click any candidate point on the map he trusts and send a message to the helper done by system in Figure 4. Finally the connection between the customer and the helper is built and our service is provided perfectly.


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AU Android Developer Group

Xiao Lin
Kang Sun
Yuanqi Chen
Huaiyuan Zhang
Bin Li


Please list here relevant links (Github, a prototype website, etc.,)


If your project has been nominated for global awards, please indicate here the global award category for which you wish to be considered.