Project Title

IoT Web Application - COSC310

Getting Started with Flask Application

To run the Flask application on your local machine, follow these steps:

1. Open your terminal.
2. Install the required libraries by using pip install -r requirements.txt
3. Initalize the database by running pytest
4. Navigate to the project directory using cd src.
5. Finally, start the Flask application with the command flask --app flaskr run.

User Requirements

• Common users will start by signing into their account
• If the user doesn’t have an account, they will be prompted to make one
• Users are also offered to upgrade their account for a price
• Users can select a dataset from a preset list
• Users can filter the dataset they chose as they see necessary
• Users will select the sensor or sensors that they want to visualize
• Users select the type of visualization they want for the sensor(s)
• Users set the axis parameters for the data they chose
• The user can set high and low limits to be alerted if they are breached
• The user can set alarm management options to avoid alarm issues
• The user can select an advanced Machine Learning Algorithm to predict future values of a sensor using other sensor values which is accompanied by a confidence interval for all predicted data
• Results will be displayed for the user in Visualization
• The user can export the visualization
• The user will be able to see the alarm log if any went off
• The user can export the alarm log
• Users can Sign out at any time, which kills their current data
• Premium users will have all the functionality of the common user but be able to upload their dataset

Functional Requirements

• The program will provide the user with data analysis and the data set selected
• The user will be able to create alarms based on historical data
• The program will visualize data pre- and post-analysis for the user
• The program will predict future trends within the data the user provides
• The UI will be intuitive and easy for the user to interact with

Non-Functional Requirements

• The transition between sending a pull request and accessing data will be seamless
• The webpage should run on any modern device, including mobile.
• The prediction algorithm should not take more than 1 minute to process future data
• User input data must be securely stored, as it could include confidential information
• The webpage must be able to handle multiple user interactions at the same time