Team Name: Arnoldillo Team members: Nathan Arnold, Dillon Tate
Individual contributions:
Both: Created database designs and determined attributes; Imported CSV files; Meet together to go over code and discuss planning
Dillon: Created github repositories to share files; implemented APIs.py to handle web requests including getteam, testcount, reset, gethospital; worked on DBtools.py to use for handling database functions; implemented webserver.py to start the server (not used anymore); created APIhelper functions; set up resets and creation of mysql databases;
Nathan: Wrote interactions with MongoDB server (deprecated); Set up web server using Flask; Tested web server and integrated with existing project
Project design: Language: Python
MongoDB: A graph database will be used to store precomputed distances from zip codes to treatment facilities. Given a patient zip code, map to the nearest hospitals with open beds. A node is created for each zip code containing at least one hospital. Node values: distance, zip_to, zip_from
A query to this database would include the current zipcode and return the list of hopsital_ids in order of least to greatest distance.
atlas: reallysecurepwd
A complex event processor will be used to handle the event streams containing patient records. This CEP will be able to detect activity over time intervals to determine if there is an alert state. It will be used to handle the real time reporting APIs.
MySQL: A relational database will be used to keep track of hospital capacity and patient status.
Entity: Patient
Attributes: first_name, last_name, mrn, zip_code, patient_status_code, hospital_id (this will be -1 if not assigned and 0 if home)
Entity: Hospital
Attributes: current_capacity, and all properties included in hospital .csv (hospital_id, zip_code, trauma, etc...)
Relation: Patient <-> hospital