Sprint 3 Review

This sprint we did the following:

Rebuilt the backend response in different endpoints.
Redeployed all the infrastructure, because the services were down.
Changed the credentials needed for the Redis.
Developed the frontend needed to show in real time the information (bikes available and the ones disabled).
Developed a serverless function which retrieves the data on real time and calculates a new output every time we want to consult the web page.

Plan Week 10

This week we will:

This week we are going to do the following:
- Plot the clusters via Data IQ using Gaussian Mixture for clustering the arrivals.
- Create tests in backend
- Integrate CI/CD

This week we will do the following:

Make a PoC using Random Forest
- Develop in Python a Markov Chain with the datasets disposed
Test backend service
- Do unit testing
- Do integration testing
Complete the Homepage view (frontend)
- Only boilerplate
- UX is the priority
Configure CircleCI
- For automating tests
- In a short term will help to deploy
Configure TCP sockets in backend
- Impment TCP Connection Address in GO

This week we will do the following:

Research using Data IQ
- Analyze the distribution of the data
Make a PoC using Random Forest
- Develop in Python a Markov Chain with the datasets disposed
Define endpoints needed for backend
- Make a PoC for every endpoint using Redis
- Testcases included
- Try to do a TDD strategy
Complete the Homepage view (frontend)
- Only boilerplate
- UX is the priority
Configure CircleCI
- For automating tests
- In a short term will help to deploy
Configure TCP sockets in backend
- Impment TCP Connection Address in GO

This week we are going to do the following

Frontend Boilerplate
- This week we will start doing scaffolding in the homepage, and maybe in one or two more views. (Samuel)
Define Backend models/entities
- There are about 3 to 4 entities, we will define each one with their respective properties this week. (Victor and Estefany)
Define Web HTTP frameworks for Go backend service
- We are considering to use Gorilla, Gin, Revel or whatever framework which fits better for our project. (Julia)
Create A Multinomial Logisitic Regression model
- This will be a rebalanced model, which will be developed together with the team from Bosch. (Victor)
Do a presentation of our currently deliverables in Bosch. (Victor)

The plan for this week is the follwoing:

Definition of variables
- Define variables that will be the output from the Machine Learning Predictive Model (we have identified 6 variables) for the microservice. (Victor)
Matlab – data analyzed
- Make a PoC about using matlab to retrieve and process the data. (Victor)
Domain requirements
- Identify the required modules, entities and domains. (Victor and Julia)
Proposal Technologies
- List the technologies that we will use. (Samuel and Julia)
Bakckend architecture
- Identify the backend architecture needed for the real scope which we want to achieve. (Estefy and Samuel)
Mockups
- Create some mockups for the frontend. (Samuel and Julia)

According to this week plan…

We created two Github Repositories for our project. One for back end and another for front end. You can find them in the following links:

Also, we have a first approach for the system architecture. We will discuss it more into detail the next session:

And this is the list of requirements we have so far:
- ML algorithms implemented (Matlab/ python).
- Data with useful information.
- Display data by time/ location.
- Data persistence.
- Use of sockets for real time updates.
- Usage trends.
- Devops environment.
- Software testing.
- Software simulation using python and SUMO.
In order to do this project we have been authorized (from Bosch) to include other classmates from different subjects.