Delos Chang Robin Wang Justice Amoh Aaditya Talwal Maan Tinna
What is our app idea?
We are using continuous sensing and collected Biorhythm data to efficiently provide people with specific information they need, at the time that they need it. We wish to target college students who tend to have a lot of things on their plate, and are notoriously inefficient with their behavior. In other words, we plan to create a Google Now for Dartmouth students.
Here are some components we wish to have in this project, Timely:
(This would include some or all of the following features)
- Nutritional menu - pulled up when an app user is located in a dining facility
- Automatically set an alarm depending on how late you’re up and if you forget to
- Campus events near buildings - Display a list of relevant campus events within a small radius of the user’s location
- Silencing phone when you enter class and unsilencing
- Free food finder - Parsing Campus Free Food Bulletin and provide users with free food options near their area
- Check-in, class election deadline notification
- Greenprint status
- Autobook study rooms
- Checks how long you usually sleep for and tries to warn you if you have class tomorrow
- Sensing sniffling/sneezing/coughing to book Dick’s house appointment
Idea for using live streams of activity and collected Biorhythm data:
We plan to cross-reference location and other data from PACO to provide time-saving, contextual information for the user. Live streams of activity will be combined with the BioRhythm project data to calibrate our predictions so they tailor to the users’ lifestyle seamlessly.
From the public Campus-Events Listserv we can get hold of a database of all events happening on Dartmouth campus. Suppose an app user is walking by the Hopkins Center, which we know from using our location-tracking. The user’s biorhythm data indicates he is stressed so our App pulls up data about campus events at the Hopkins Center that can go towards de-stressing the student user. Now if the user comes out of said Hopkins Center event and his mood is set to happy, then our app can conclude that the previous activity at the Hopkins Center made the app user happy and can suggest similar events when they come up in the future. We can also determine if a student enjoys sporting or art events. For example, if a student seems to exercise quite frequently, he may be interested in sporting events and our app will focus on displaying sporting events to the student.
Here are some components we wish to have in this project, Timely:
(This would include some or all of the following features)
- Nutritional menu - pulled up when an app user is located in a dining facility
- Automatically set an alarm depending on how late you’re up and if you forget to
- Campus events near buildings - Display a list of relevant campus events within a small radius of the user’s location
- Silencing phone when you enter class and unsilencing
- Free food finder - Parsing Campus Free Food Bulletin and provide users with free food options near their area
- Check-in, class election deadline notification
- Greenprint status
- Autobook study rooms
- Checks how long you usually sleep for and tries to warn you if you have class tomorrow
- Sensing sniffling/sneezing/coughing to book Dick’s house appointment
Idea for using live streams of activity and collected Biorhythm data:
We plan to cross-reference location and other data from PACO to provide time-saving, contextual information for the user. Live streams of activity will be combined with the BioRhythm project data to calibrate our predictions so they tailor to the users’ lifestyle seamlessly.
From the public Campus-Events Listserv we can get hold of a database of all events happening on Dartmouth campus. Suppose an app user is walking by the Hopkins Center, which we know from using our location-tracking. The user’s biorhythm data indicates he is stressed so our App pulls up data about campus events at the Hopkins Center that can go towards de-stressing the student user. Now if the user comes out of said Hopkins Center event and his mood is set to happy, then our app can conclude that the previous activity at the Hopkins Center made the app user happy and can suggest similar events when they come up in the future. We can also determine if a student enjoys sporting or art events. For example, if a student seems to exercise quite frequently, he may be interested in sporting events and our app will focus on displaying sporting events to the student.