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Task Organizer Platform for Class and Group Collaboration

Description

There exist many very effective calendar platforms out there, from Google Calendar, to Microsoft’s Outlook, and various implementations by other service providers. While all those services serve their purpose, they may be missing in the capacity to be easily portable

There exist many very effective calendar platforms out there, from Google Calendar, to Microsoft’s Outlook, and various implementations by other service providers. While all those services serve their purpose, they may be missing in the capacity to be easily portable for some, or the capacity to offer to the user a ranking of their various events and tasks in order of priority. This is that, while some of these services do offer reliable support for portability on smaller devices, it could be even more beneficial to the user to constantly have an idea of which calendar entry they should prioritize at a given point in time, based on the necessities of each entry and regardless of which entry occurs first on a chronologic line. Many of these capacities are missing in the technology currently used at ASU for course management. This project attempts to address this issue by providing a Software Application that offers to store a user’s calendar events and present those events back to the user after arranging them by order of priority. The project makes use of technologies such as Fibrease, Angular and Android to make the service available through a web browser as well as an Android mobile client. We explore possible avenues of implementations to make the services of this platform accessible and usable through other existing platforms such as Blackboard or Canvas. We also consider ways to incorporate this software into the already existing workflow of other web platforms such as Google Calendar, Blackboard or Canvas, by allowing one platform to be aware of any item creation or update from the other platform, and thus removing the necessity of creating one calendar entry multiple times in different platforms.

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Date Created
2019-05

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Developing an iOS Application to Guide Users Around Flooded Areas in Charleston, SC

Description

Charleston, South Carolina currently faces serious annual flooding issues due to tides and rainfall. These issues are expected to get significantly worse within the next few decades reaching a projected 180 days a year of flooding by 2045 (Carter et

Charleston, South Carolina currently faces serious annual flooding issues due to tides and rainfall. These issues are expected to get significantly worse within the next few decades reaching a projected 180 days a year of flooding by 2045 (Carter et al., 2018). Several permanent solutions are in progress by the City of Charleston. However, these solutions are years away at minimum and faced with development issues. This thesis attempts to treat some of the symptoms of flooding, such as navigation, by creating an iPhone application which predicts flooding and helps people navigate around it safely. Specifically, this thesis will take into account rainfall and tide levels to display to users actively flooded areas of downtown Charleston and provide routing to a destination from a user’s location around these flooded areas whenever possible.

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Date Created
2019-05

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Song Sift: Angular Web App to Filter Songs and Create Customizable Playlists via the Spotify API

Description

Although Spotify’s extensive library of songs are often seen broken up by “Top 100” and main lyrical genres, these categories are primarily based on popularity, artist and general mood alone. If a user wanted to create a playlist based on

Although Spotify’s extensive library of songs are often seen broken up by “Top 100” and main lyrical genres, these categories are primarily based on popularity, artist and general mood alone. If a user wanted to create a playlist based on specific or situationally specific qualifiers from their own downloaded library, he/she would have to hand pick songs that fit the mold and create a new playlist. This is a time consuming process that may not produce the most efficient result due to human error. The objective of this project, therefore, was to develop an application to streamline this process, optimize efficiency, and fill this user need.

Song Sift is an application built using Angular that allows users to filter and sort their song library to create specific playlists using the Spotify Web API. Utilizing the audio feature data that Spotify attaches to every song in their library, users can filter their downloaded Spotify songs based on four main attributes: (1) energy (how energetic a song sounds), (2) danceability (how danceable a song is), (3) valence (how happy a song sounds), and (4) loudness (average volume of a song). Once the user has created a playlist that fits their desired genre, he/she can easily export it to their Spotify account with the click of a button.

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2020-05