#TakeLessons Booking Monitor#
The project can be broken down in the following manner:
The machine will most likely run best on Ubuntu, with a decent graphics card to handle the CSS3 rendering that we may potentially do.
Aiming to display on a computer that’s at least 720P
This will only be accessible internally (just like Maestro). It can be accessed by anyone in the office.
We will be storing this data into the reporting table, where it will store the following information:
The information will be added when they are booked via Public and Maestro
Pull from the Sale ETL
Create a new machine/storage-location to store these smaller records.
If filtering our data, we can fetch the data in any way we want. There are the optional filters we can have:
This is the data we’ll output to the display, in a JSON format that can be fetched asynchronously
id (int),
student: {
name (string),
},
teacher: {
name (string),
photo_url (string)
},
lesson: {
category (string),
service (string),
},
location: {
product_loc_type (string),
lesson_duration (string),
lat (float),
lng (float),
city (string),
state (string)
},
created_at (timestamp)The cards will be sorted in a FIFO format.
The most recent card will be the largest card, while other cards will shrink down as they are pushed down
The cards should have these requirements:
If there are cards queued up, divide up the time of the cards with this simple algorithm:
tMin = Min time of cards = 10 sec.
tMax = Max time of cards = 60 sec.
total = Total Cards = Actively displayed Card + Queued Cards
timePerCard = max(tMax / total - 5), tMin);
The “5” is the threshold to start doing this algorithm. For instance, we want to make sure we don’t burn through 5 cards immediately. We’ll start using this algorithm after having gained 5 total cards so it gives the illusion that we are still generating bookings.
There are 3 factors that have been identified when adding a new card:
The map will be an SVG image that will be measured precisely so that map markers can be coordinated on it. It must be scalable to be used on any browser, especially an HDTV.
Icons will be placed relative to the map.
Additional effects may be added to make icons look more apparent that it has just been placed.
Icons must be:
Represent each map marker with these symbols (All from the font Elusive)
In-Home: http://www.fontello.com/#search=road
In-Studio: http://www.fontello.com/#search=home
Online: http://www.fontello.com/#search=desktop
Additionally, when a map icon is added, it can create a nice effect where the map tilts based on where the icon hits on the map.
Additional kudos points if we can add Hawaii and Alaska into the corner of the screen, and having icons drop into there. Otherwise, ignore the icons.
The graph will show the number of sales per hour over the course of 24 hours
Allow the user to be able to apply filters to the map, with the provided inputs
Show a running page of social media from Facebook, Twitter, Instagram, and g+ on a separate “screen”
This person will be expected to create an API that will output expected parameters for the front-end developer to use. They also must create an interface for the front-end developer to grab the formatted data from.
Additional: They must be able to hook this into places that generate booking, and store the data into the database.
This person will be responsible for stubbing out data until the API/Backend developer is able to send data with the expected parameters.
They will also manage the card algorithm system as well.
The map developer will be responsible for the coordination of pin icons on a vector-based map. They will need to need to be able to create a library that will allow the front-end card developer to add and remove pins.