Merge branch 'develop' of https://github.com/COS301-SE-2024/occupi in…

…to develop

documentation/occupi-docs/pages/_meta.json

@@ -2,6 +2,10 @@
   "index": "Introduction",
   "api-documentation": "Api documentation",
   "coding-standards": "Coding Standards",
+  "installation": {
+    "title": "Installation",
+    "type": "page"
+  },
   "srs": {
     "title": "Software Requirements Specification",
     "type": "page"

documentation/occupi-docs/pages/installation.mdx

@@ -0,0 +1,127 @@
+### Occupi Installation Manual
+
+---
+
+### Mobile
+
+---
+
+#### Introduction
+Occupi is an advanced occupancy prediction application designed to help organizations manage and optimize office space usage efficiently. Available on both Android and iOS platforms, the app leverages AI and machine learning to provide accurate predictions of office capacity, allowing for informed decision-making regarding space allocation and management. This manual will guide you through the necessary steps to install the Occupi mobile application on your device and ensure all system components are properly configured.
+
+#### Prerequisites
+Before installing Occupi, ensure the following prerequisites are met:
+
+1. **Supported Devices**:
+   - Android: Version 8.0 (Oreo) or higher
+   - iOS: Version 13.0 or higher
+
+2. **Internet Connectivity**:
+   - A stable internet connection is required for installation and regular use of the application.
+
+3. **Mobile Device Permissions**:
+   - Location Services: Must be enabled for real-time occupancy tracking.
+   - Notifications: Enabled to receive alerts and updates.
+
+**Installing Prerequisites**:
+- For Android devices, ensure Google Play Services are up to date.
+- For iOS devices, ensure the latest version of iOS is installed.
+- Follow your device's standard procedure to enable location services and notifications under Settings.
+
+#### Installation
+Follow these steps to install the Occupi mobile app:
+
+1. **Android Installation**:
+   - Open the Google Play Store on your Android device.
+   - Search for "Occupi."
+   - Tap on the app and select "Install."
+   - Once installed, open the app to begin setup.
+
+2. **iOS Installation**:
+   - Open the App Store on your iOS device.
+   - Search for "Occupi."
+   - Tap on the app and select "Get."
+   - Authenticate if necessary, and the app will begin downloading and installing.
+   - Once installed, open the app to begin setup.
+
+#### Deployment/Running
+Once the Occupi app is installed, follow these steps to run it:
+
+1. **Launching the App**:
+   - Locate the Occupi icon on your device’s home screen and tap to open it.
+
+2. **Initial Setup**:
+   - The app will prompt you to enable necessary permissions, such as location services and notifications.
+   - Log in with your credentials or sign up if you are a new user.
+
+3. **Backend Connection**:
+   - The app will automatically connect to the backend server to sync data. Ensure you have a stable internet connection.
+
+4. **Using Occupi**:
+   - After the initial setup, you can start using the app to monitor and predict office occupancy.
+   - For detailed instructions on using Occupi, refer to the [User Manual](#).
+
+---
+
+### Occupi Web Interface Installation Manual
+
+---
+
+#### Introduction
+The Occupi web interface is designed for admin users to manage office occupancy, view detailed predictions, and configure settings for the mobile application. This web-based platform is compatible with all major browsers, with optimal performance on Google Chrome, Microsoft Edge, and Firefox. This manual will guide you through the necessary steps to access and set up the Occupi web interface on your preferred browser.
+
+#### Prerequisites
+Before accessing the Occupi web interface, ensure the following prerequisites are met:
+
+1. **Supported Browsers**:
+   - Google Chrome: Latest version
+   - Microsoft Edge: Latest version
+   - Firefox: Latest version
+
+2. **Admin Access**:
+   - Ensure you have valid admin credentials to log in to the web interface.
+
+3. **Internet Connectivity**:
+   - A stable internet connection is required to access and use the web interface effectively.
+
+**Installing Prerequisites**:
+- **Browser Installation**:
+  - **Google Chrome**:
+    - Visit [Google Chrome Download](https://www.google.com/chrome/) and follow the instructions to download and install the latest version.
+  - **Microsoft Edge**:
+    - Visit [Microsoft Edge Download](https://www.microsoft.com/edge) and follow the instructions to download and install the latest version.
+  - **Firefox**:
+    - Visit [Firefox Download](https://www.mozilla.org/firefox/new/) and follow the instructions to download and install the latest version.
+- **Internet Connectivity**:
+  - Ensure your device is connected to a reliable internet network.
+
+#### Installation
+Since the Occupi web interface is a browser-based platform, no traditional installation is required. However, follow these steps to set up and access the web interface:
+
+1. **Open Your Preferred Browser**:
+   - Launch Google Chrome, Microsoft Edge, or Firefox on your device.
+
+2. **Access the Occupi Web Interface**:
+   - In the browser's address bar, enter the following URL: `https://admin.occupi.com`
+   - Press Enter to load the login page.
+
+3. **Logging In**:
+   - Enter your admin credentials (username and password) on the login page.
+   - Click "Login" to access the dashboard.
+
+#### Deployment/Running
+Once logged in, you can start using the Occupi web interface:
+
+1. **Navigating the Dashboard**:
+   - After logging in, you will be directed to the admin dashboard, where you can view occupancy data, manage settings, and generate reports.
+
+2. **Admin Controls**:
+   - Use the sidebar to navigate through different sections, including Occupancy Predictions, User Management, and Settings.
+
+3. **Saving and Bookmarking**:
+   - To quickly access the Occupi web interface in the future, bookmark the URL (`https://admin.occupi.com`) in your browser.
+
+4. **Using the Interface**:
+   - For detailed instructions on using the Occupi web interface, refer to the [Admin User Manual](#).
+
+---

python-code/app.py

@@ -1,12 +1,15 @@
 from flask import Flask, request, jsonify
 import logging
+from flask_cors import CORS
 from datetime import datetime, timedelta
 from prediction import get_prediction
 import joblib
 
 # Initialize the Flask application
 app = Flask(__name__)
 
+CORS(app, resources={r"/*": {"origins": ["https://dev.occupi.tech", "https://app.occupi.tech"]}})
+
 # Load the scaler
 scaler = joblib.load('attendance_scaler.pkl')
 
@@ -35,8 +38,6 @@ def predict():
         day_of_month = current_date.day
         weekend = is_weekend(current_date)
         special_event = is_special_event(current_date)
-        # Set factor based on special event
-        # factor = 1.5 if special_event else 1.0
 
         predicted_class, predicted_attendance_level = get_prediction(day_of_week, month, day_of_month, weekend, special_event, scaler)
 
@@ -74,9 +75,6 @@ def predict_week():
             weekend = is_weekend(date)
             special_event = is_special_event(date)
 
-            # Set factor based on special event
-            # factor = 1.5 if special_event else 1.0
-
             # Get prediction
             predicted_class, predicted_attendance_level = get_prediction(day_of_week, month, day_of_month, weekend, special_event, scaler)
 
@@ -97,5 +95,126 @@ def predict_week():
         logging.error(f"Error in predict_week endpoint: {str(e)}")
         return jsonify({"error": str(e)}), 500
 
+@app.route('/predict_date', methods=['GET'])
+def predict_date():
+    try:
+        # Get the date from query parameters
+        date_str = request.args.get('date')
+        if not date_str:
+            return jsonify({"error": "Date parameter is required"}), 400
+
+        # Parse the date
+        date = datetime.strptime(date_str, '%Y-%m-%d')
+
+        # Extract day of the week, month, and day of the month
+        day_of_week = date.weekday()
+        month = date.month
+        day_of_month = date.day
+        weekend = is_weekend(date)
+        special_event = is_special_event(date)
+
+        # Get prediction
+        predicted_class, predicted_attendance_level = get_prediction(day_of_week, month, day_of_month, weekend, special_event, scaler)
+
+        return jsonify({
+            'Date': date_str,
+            'Day_of_Week': day_of_week,
+            'Month': month,
+            'Day_of_month': day_of_month,
+            'Is_Weekend': weekend,
+            'Special_Event': special_event,
+            'Predicted_Class': predicted_class,
+            'Predicted_Attendance_Level': predicted_attendance_level
+        })
+    except Exception as e:
+        logging.error(f"Error in predict_date endpoint: {str(e)}")
+        return jsonify({"error": str(e)}), 500
+
+@app.route('/predict_week_from_date', methods=['GET'])
+def predict_week_from_date():
+    try:
+        # Get the date from query parameters
+        date_str = request.args.get('date')
+        if not date_str:
+            return jsonify({"error": "Date parameter is required"}), 400
+
+        # Parse the date
+        start_date = datetime.strptime(date_str, '%Y-%m-%d')
+
+        predictions = []
+        for i in range(7):
+            # Calculate the date for each day of the week
+            date = start_date + timedelta(days=i)
+
+            # Extract day of the week, month, and day of the month
+            day_of_week = date.weekday()
+            month = date.month
+            day_of_month = date.day
+            weekend = is_weekend(date)
+            special_event = is_special_event(date)
+
+            # Get prediction
+            predicted_class, predicted_attendance_level = get_prediction(day_of_week, month, day_of_month, weekend, special_event, scaler)
+
+            # Append the results
+            predictions.append({
+                'Date': date.strftime('%Y-%m-%d'),
+                'Day_of_Week': day_of_week,
+                'Month': month,
+                'Day_of_month': day_of_month,
+                'Is_Weekend': weekend,
+                'Special_Event': special_event,
+                'Predicted_Class': predicted_class,
+                'Predicted_Attendance_Level': predicted_attendance_level
+            })
+
+        return jsonify(predictions)
+    except Exception as e:
+        logging.error(f"Error in predict_week_from_date endpoint: {str(e)}")
+        return jsonify({"error": str(e)}), 500
+
+@app.route('/predict_7_days', methods=['GET'])
+def predict_week_from_date():
+    try:
+        # Get the date from query parameters
+        date_str = request.args.get('date')
+        if not date_str:
+            return jsonify({"error": "Date parameter is required"}), 400
+
+        # Parse the date
+        start_date = datetime.strptime(date_str, '%Y-%m-%d')
+
+        predictions = []
+        for i in range(7):
+            # Calculate the date for each day of the week
+            date = start_date + timedelta(days=i)
+
+            # Extract day of the week, month, and day of the month
+            day_of_week = date.weekday()
+            month = date.month
+            day_of_month = date.day
+            weekend = is_weekend(date)
+            special_event = is_special_event(date)
+
+            # Get prediction
+            predicted_class, predicted_attendance_level = get_prediction(day_of_week, month, day_of_month, weekend, special_event, scaler)
+
+            # Append the results
+            predictions.append({
+                'Date': date.strftime('%Y-%m-%d'),
+                'Day_of_Week': day_of_week,
+                'Month': month,
+                'Day_of_month': day_of_month,
+                'Is_Weekend': weekend,
+                'Special_Event': special_event,
+                'Predicted_Class': predicted_class,
+                'Predicted_Attendance_Level': predicted_attendance_level
+            })
+
+        return jsonify(predictions)
+    except Exception as e:
+        logging.error(f"Error in predict_week_from_date endpoint: {str(e)}")
+        return jsonify({"error": str(e)}), 500
+
 if __name__ == '__main__':
     app.run(debug=True, host='0.0.0.0', port=9000)

python-code/docker-compose_1.yml

@@ -0,0 +1,36 @@
+version: '3.8'
+
+services:
+  attendance-model:
+    build: 
+      context: .
+      dockerfile: Dockerfile
+    container_name: attendance-model
+    networks:
+      - webnet
+    ports:
+      - "9000:9000"
+    extra_hosts:
+      - "host.docker.internal:host-gateway"
+    restart: on-failure:5
+    depends_on:
+      - model
+
+  model:
+    image: tensorflow/serving:latest
+    container_name: model
+    environment:
+      MODEL_NAME: attendance_model
+    volumes:
+      - /models/attendance_model:/models/attendance_model  # Ensure this path is correct
+    ports:
+      - "8501:8501"
+    command: >
+      sh -c 'tensorflow_model_server --port=8501 --model_name=attendance_model --model_base_path=/models/attendance_model'
+    networks:
+      - webnet
+    restart: on-failure:5
+
+networks:
+  webnet:
+    external: true

python-code/requirements.txt

@@ -7,3 +7,4 @@ scikit-learn
 seaborn
 matplotlib
 gunicorn
+flask-cors