SolarScope | An Interactive Tool for Solar Energy and Bushfire Risk Insights

Purpose

SolarScope is a web-based analytics platform developed to support informed decision-making around solar energy potential and bushfire risk awareness. It is designed to help users upload, visualize, and analyze daily global solar exposure data obtained from the Australian Bureau of Meteorology (BoM)’s Climate Data Online service. By focusing on real measurements from weather stations located in areas of interest, the system enables targeted environmental insight.

Design and Use

SolarScope is built with a user-centric, modular architecture using Flask for the backend and JavaScript/Chart.js on the frontend. The design supports the following core functionalities:

Data Upload & Storage:

Users can upload CSV files containing daily solar exposure readings (MJ/m²) from local weather stations. Each dataset is tagged with location metadata (city, latitude, longitude) and stored securely in a database.

Access Control & Sharing:

Uploaded files can be marked as private, shared, or public. Shared files allow selected users to collaborate, while public files contribute to broader regional comparisons.

Interactive Visualisation:

Users can select one or more datasets to explore trends over time — daily, monthly, yearly — using dynamic charts. The platform provides automated recommendations for solar farm suitability based on long-term solar exposure averages.

Analysis & Reporting:

The platform performs in-browser or server-side analysis to detect:

• Seasonal patterns
• Outliers in solar data
• Residential solar panel suitability
• Bushfire risk alerts (based on consecutive high-exposure days during peak months)
• Forecasted bushfire risk (via regression modeling)

Export Capabilities:

Charts and insights can be exported as PDF or PNG, including contextual summaries that assist with planning, reporting, or stakeholder communication.

User Management:

Features include secure login, password recovery via security questions, profile editing, and email updates.

MasterGroup62

UWA ID	Name	GitHub Username
2******7	Nancy Rao	flappyfishhh
24486055	Ethan Zhang	EthanZ-SH
24284623	Joshua Wang	JoJohowl
24289358	Chamodhi Withana Gamage	chamodhii

Launching the Application

Step 1: Clone the Repository

git clone https://github.com/flappyfishhh/cits5505-masters62.git

Step 2: Navigate to the Project Directory

cd cits5505-masters62/

Step 3: Create a Virtual Environment

python -m venv venv

Step 4: Activate the Virtual Environment

• On Windows:

venv\Scripts\activate

• On macOS/Linux:

source venv/bin/activate

Step 5: Install Python Dependencies

pip install -r requirements.txt

Step 6: Initialize the Database

Run database migrations to set up the database schema:

flask db upgrade

(Optional) Step7: Seed the Database with Sample Data

Use the provided seed_data.py script to populate the database with sample users, files, and uploads.

python seed_data.py

Step 8: Start the Application

flask run

Visit the app at: http://127.0.0.1:5000/

Running Tests

This project includes both unit and end-to-end (E2E) tests using Pytest and Selenium.

Our Selenium tests use webdriver_manager.chrome, which automatically downloads the correct ChromeDriver when you run pytest.

If you're using a different browser or prefer manual setup, ensure the correct driver is installed and in your system PATH:

• For Chrome: Download ChromeDriver
• For Firefox: Download GeckoDriver

Run All Tests

pytest

This project includes a pytest.ini configuration file to manage test discovery and reporting.

Test Structure

The test suite is organized as follows:

• tests/
  • conftest.py – Shared fixtures for unit and Selenium tests
  • selenium/ – End-to-end browser-based tests
  • unit/ – Unit tests for backend functionality
  • assets/ – CSV test data for file upload & visualization

We use a daemon thread to run the test server during Selenium testing. It shuts down automatically when tests finish.

Tools

• seed_data.py

  Populates the database with sample users, solar data files, and uploads. Useful for testing, demonstration, or quickly initializing development data.

  python seed_data.py

• pytest.ini

  Configuration file for pytest. It manages test discovery, markers, output formatting, and other testing behaviors to ensure consistent results across environments.

• conftest.py

  Contains shared fixtures used across unit and Selenium tests. Required for consistent test environment setup.

• reset_dev_db.sh

  Shell script to reset the development database. It drops all data, reapplies migrations, and restores a clean schema state.

  chmod +x reset_dev_db.sh && ./reset_dev_db.sh