kuberkaul/AllYourCheckins
This project generate timelines of FourSquare check-ins while providing other functionality.
With the launch of Apple's IOS and Google's android operating systems the sale of smartphones has increased exponentially. Android emerges at the top in this market since it is open source with permissive licensing which allows the software to be freely modified by enthusiastic developers. Because of this a lot of interesting apps find their way into the Android app store which is currently estimated to hold around 800,000 apps. A lot of these apps make use of the data from the sensors present in device to find out some information about related to the physical environment that the user of the device is in. For instance, GPS data from the device would tell us the exact location of the device and hence of the person using it or a very low light sensor reading would indicate that the user is in relatively less lit place which could mean that he is sleeping or maybe at a presentation. Our application caters to applications of this kind by providing all the sensor information from the user's device on the Cloud, as a service. We have implemented two use cases to show how this service might be utilized. The first use case is called WreckWatch. Here data from the appropriate sensors is continuously monitored and analysed to detect if the phone and hence its user has been in an accident. If such values are detected an alert is sent to the people registered as his emergency contacts via call and SMS requesting them to check on him. The second use case is called “battery alert”. Here whenever the battery level in the device goes below a certain value an alert is sent to people registered as his emergency contacts on the app via call as well as SMS, asking them to get in touch with him soon if they had anything of importance to convey to him. Since the app sends out alerts every time it thinks the user might be in trouble it has been rightfully named “BatSignal”.
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This project generate timelines of FourSquare check-ins while providing other functionality.
Public repository.
This project is based in the google app engine written completely in Python. It uses JW player to stream you tube content which is stored on the blob store in google app engine.It also uses cloud front and Amazon RDS for data storage.Scan through for more details.
README - We have used Google App Engine and the services it offers. We used Google App Engine's Python SDK to create an application and deployed on Google App Engine. The link to our application is : cloud-app-3.appspot.com . The app basically takes the keyword and location and then return the tweets in 2 miles radius of that tweet and extracts sentiments from them using naive bayes and predicts 10 buzz words with their sentiments.