Discount for near traffic spot

AirbnbMapVisualiser.py

@@ -6,8 +6,10 @@ from sentence_transformers import SentenceTransformer, util
 from geopy.distance import geodesic
 import logging
 
+# Import the TrafficSpotManager from TrafficSpot module
 from TrafficSpot import TrafficSpotManager
 
+
 class AirbnbMapVisualiser:
     def __init__(self):
         self.connection_params = {
@@ -25,7 +27,7 @@ class AirbnbMapVisualiser:
             getmode=oracledb.SPOOL_ATTRVAL_WAIT
         )
 
-        # Initialize TrafficSpotManager
+        # Initialize TrafficSpotManager with minimal data
         self.traffic_manager = TrafficSpotManager(self.connection_params)
         logging.info(f"Traffic spots initialized, {len(self.traffic_manager.traffic_spots)} spots loaded")
 
@@ -298,6 +300,7 @@ class AirbnbMapVisualiser:
             return [0.0] * len(df)
 
     def sort_by_relevance(self, df, search_query):
+        """Sort listings by relevance using sentence transformer comparison"""
         if not search_query:
             return df
 
@@ -365,7 +368,7 @@ class AirbnbMapVisualiser:
         return df.sort_values('relevance_score', ascending=False)
 
     def create_map_and_data(self, neighborhood="Sha Tin", show_traffic=True, center_lat=None, center_lng=None,
-                            selected_id=None, search_query=None):
+                            selected_id=None, search_query=None, current_page=1, items_per_page=3):
         listings = self.get_neighborhood_listings(neighborhood)
 
         if not listings:
@@ -400,26 +403,65 @@ class AirbnbMapVisualiser:
             tiles='OpenStreetMap'
         )
 
-        # First add all traffic spots if enabled
-        if show_traffic:
-            self.traffic_manager.add_spots_to_map(m)
+        # Calculate pagination indices
+        total_items = len(df)
+        start_idx = (current_page - 1) * items_per_page
+        end_idx = min(start_idx + items_per_page, total_items)
+
+        # Get the current page's listings
+        current_page_df = df.iloc[start_idx:end_idx]
+
+        # Create a list to store all traffic spots we need to display
+        all_traffic_spots_to_display = set()
+
+        # Find nearest traffic spots for ALL listings
+        all_nearest_traffic_spots = {}
+
+        # First find all nearest traffic spots
+        for idx, row in df.iterrows():
+            nearest_spot, distance = self.find_nearest_traffic_spot(row['latitude'], row['longitude'])
+            if nearest_spot:
+                all_nearest_traffic_spots[row['id']] = (nearest_spot, distance)
+                all_traffic_spots_to_display.add(nearest_spot.key)
 
         # Create a feature group for connection lines
         lines_group = folium.FeatureGroup(name="Connection Lines")
         m.add_child(lines_group)
 
-        # Add Airbnb markers
+        # Display all traffic spots
+        if show_traffic and all_traffic_spots_to_display:
+            self.traffic_manager.add_spots_to_map(m, all_traffic_spots_to_display)
+
+        # Add all Airbnb markers and connection lines
         for idx, row in df.iterrows():
             marker_id = f"marker_{row['id']}"
             reviews = self.get_listing_reviews(row['id'])
             review_button_key = f"review_btn_{row['id']}"
 
-            # Find nearest traffic spot within 1 km
-            nearest_spot, distance = self.find_nearest_traffic_spot(row['latitude'], row['longitude'])
-
-            # Add traffic spot information to popup if found
+            # Get traffic spot info if available for this listing
             traffic_spot_info = ""
-            if nearest_spot:
+            discount_info = ""
+            discounted_price = row['price']
+
+            # Check if this listing has a nearest traffic spot
+            if row['id'] in all_nearest_traffic_spots:
+                nearest_spot, distance = all_nearest_traffic_spots[row['id']]
+
+                # Get discount rate and apply to price
+                discount_rate = nearest_spot.get_discount_rate()
+                if discount_rate > 0:
+                    discounted_price = row['price'] * (1 - discount_rate)
+                    discount_percentage = int(discount_rate * 100)
+
+                    # Format discount info
+                    discount_info = f"""
+                        <div style='background-color: #e8f5e9; padding: 8px; margin: 10px 0; border-radius: 4px; border-left: 4px solid #4caf50;'>
+                            <p style='margin: 2px 0; font-weight: bold; color: #2e7d32;'>🎉 {discount_percentage}% ENV PROTECTION DISCOUNT!</p>
+                            <p style='margin: 2px 0;'>Original: ${row['price']:.0f} → Now: ${discounted_price:.0f}</p>
+                            <p style='margin: 2px 0; font-size: 0.85em;'>Avg. {nearest_spot.avg_vehicle_count:.1f} vehicles per observation</p>
+                        </div>
+                    """
+
                 # Format distance for display (convert to meters if less than 1km)
                 distance_str = f"{distance:.2f} km" if distance >= 0.1 else f"{distance * 1000:.0f} meters"
 
@@ -433,7 +475,7 @@ class AirbnbMapVisualiser:
                     </div>
                 """
 
-                # Add a line connecting Airbnb to nearest traffic spot
+                # Add connection lines for ALL listings with nearby traffic spots
                 folium.PolyLine(
                     locations=[
                         [row['latitude'], row['longitude']],
@@ -460,13 +502,19 @@ class AirbnbMapVisualiser:
                     </div>
                 """
 
+            # Show price with strikethrough if discounted
+            price_display = f"<strong>Price:</strong> ${row['price']:.0f}"
+            if discount_info:
+                price_display = f"<strong>Price:</strong> <span style='text-decoration: line-through;'>${row['price']:.0f}</span> <span style='color: #2e7d32; font-weight: bold;'>${discounted_price:.0f}</span>"
+
             popup_content = f"""
                 <div style='min-width: 280px; max-width: 320px; padding: 15px;'>
                     <h4 style='margin: 0 0 10px 0; color: #2c3e50;'>{escape(str(row['name']))}</h4>
                     <p style='margin: 5px 0;'><strong>Host:</strong> {escape(str(row['host_name']))}</p>
                     <p style='margin: 5px 0;'><strong>Room Type:</strong> {escape(str(row['room_type']))}</p>
-                    <p style='margin: 5px 0;'><strong>Price:</strong> ${row['price']:.0f}</p>
+                    <p style='margin: 5px 0;'>{price_display}</p>
                     <p style='margin: 5px 0;'><strong>Reviews:</strong> {row['number_of_reviews']:.0f}</p>
+                    {discount_info}
                     {traffic_spot_info}
                     {relevance_info}
                 </div>
@@ -506,7 +554,7 @@ class AirbnbMapVisualiser:
             </script>
         """).add_to(m)
 
-        # Add layer control to toggle traffic spots and connection lines
+        # Add layer control to toggle connection lines
         folium.LayerControl().add_to(m)
 
         return m, df

TrafficSpot.py

@@ -2,8 +2,10 @@ import folium
 import oracledb
 import logging
 import base64
+import numpy as np
 from html import escape
 from datasets import load_dataset
+from datetime import datetime, timedelta
 
 
 class TrafficSpot:
@@ -12,14 +14,60 @@ class TrafficSpot:
         self.latitude = float(latitude) if latitude is not None else None
         self.longitude = float(longitude) if longitude is not None else None
         self.dataset_rows = dataset_rows or []  # List of matching dataset rows (up to 5)
+        self.avg_vehicle_count = self.calculate_avg_vehicle_count()
 
     def is_valid(self):
         return self.latitude is not None and self.longitude is not None
 
+    def calculate_avg_vehicle_count(self):
+        """Calculate average vehicle count from the recent data"""
+        if not self.dataset_rows:
+            return 0
+
+        # Extract vehicle counts from dataset rows
+        vehicle_counts = [row.get('vehicle_count', 0) for row in self.dataset_rows if 'vehicle_count' in row]
+
+        # If no valid counts are found, return 0
+        if not vehicle_counts:
+            return 0
+
+        # Calculate and return the average
+        return np.mean(vehicle_counts)
+
+    def get_discount_rate(self):
+        """Calculate discount rate based on average vehicle count"""
+        if self.avg_vehicle_count < 2:
+            return 0.20  # 20% discount
+        elif self.avg_vehicle_count < 5:
+            return 0.10  # 10% discount
+        else:
+            return 0.0  # No discount
+
+    def get_discount_info(self):
+        """Get discount information as a formatted string"""
+        discount_rate = self.get_discount_rate()
+
+        if discount_rate <= 0:
+            return "No traffic discount available"
+
+        return f"{int(discount_rate * 100)}% discount! Low traffic area"
+
     def create_popup_content(self):
+        discount_info = self.get_discount_info()
+        discount_display = ""
+
+        if "discount" in discount_info.lower() and "no" not in discount_info.lower():
+            discount_display = f"""
+                <div style='background-color: #e8f5e9; padding: 5px; margin: 5px 0; border-radius: 4px; border-left: 3px solid #4caf50;'>
+                    <p style='margin: 2px 0; color: #2e7d32;'><strong>🎉 {discount_info}</strong></p>
+                    <p style='margin: 2px 0; font-size: 0.9em;'>Avg. {self.avg_vehicle_count:.1f} vehicles per observation</p>
+                </div>
+            """
+
         html = f"""
             <div style='min-width: 150px; padding: 10px;'>
                 <p style='margin: 5px 0;'><strong>Location ID:</strong> {escape(str(self.key))}</p>
+                {discount_display}
         """
 
         if self.dataset_rows:
@@ -58,10 +106,18 @@ class TrafficSpot:
 
     def add_to_map(self, folium_map):
         if self.is_valid():
+            # Choose color based on traffic level
+            if self.avg_vehicle_count < 2:
+                color = 'blue'  # Low traffic - 20% discount
+            elif self.avg_vehicle_count < 5:
+                color = 'orange'  # Medium traffic - 10% discount
+            else:
+                color = 'purple'  # High traffic - no discount
+
             folium.Marker(
                 location=[self.latitude, self.longitude],
                 popup=self.create_popup_content(),
-                icon=folium.Icon(color='blue', icon='camera'),
+                icon=folium.Icon(color=color, icon='camera'),
             ).add_to(folium_map)
 
 
@@ -69,20 +125,30 @@ class TrafficSpotManager:
     def __init__(self, connection_params):
         self.connection_params = connection_params
         self.traffic_spots = []
-        self.load_traffic_spots()
+        self.spot_dict = {}  # For quick lookup by key
+        # Only load limited spots when initialized
+        self.load_limited_traffic_spots()
 
-    def load_traffic_spots(self):
+    def load_limited_traffic_spots(self, limit=10):
+        """Load only a very limited set of traffic spots initially"""
         try:
             dataset = load_dataset("slliac/traffic-analysis", split="train")
             dataset_list = [row for row in dataset]
             dataset_list.sort(key=lambda x: x['capture_time'], reverse=True)
 
+            # Limit to just a few samples
             dataset_dict = {}
+            unique_count = 0
             for row in dataset_list:
                 loc_id = row['location_id']
+                if unique_count >= limit:
+                    break
+
                 if loc_id not in dataset_dict:
                     dataset_dict[loc_id] = []
-                if len(dataset_dict[loc_id]) < 2:
+                    unique_count += 1
+
+                if len(dataset_dict[loc_id]) < 10:  # Store up to 10 records for averaging
                     dataset_dict[loc_id].append(row)
 
             unique_locations = list(dataset_dict.keys())
@@ -111,20 +177,99 @@ class TrafficSpotManager:
                     for spot in spots
                 ]
 
+                # Build lookup dictionary
+                for spot in self.traffic_spots:
+                    self.spot_dict[spot.key] = spot
+
                 conn.commit()
-                logging.info(f"Loaded {len(self.traffic_spots)} traffic spots")
+                logging.info(f"Loaded {len(self.traffic_spots)} limited traffic spots")
 
         except Exception as e:
             logging.error(f"Error loading traffic spots: {str(e)}")
             self.traffic_spots = []
+            self.spot_dict = {}
+
+    def load_specific_traffic_spots(self, keys):
+        """Load specific traffic spots by their keys"""
+        # Filter out keys we already have
+        needed_keys = [key for key in keys if key not in self.spot_dict]
+
+        if not needed_keys:
+            return
+
+        try:
+            dataset = load_dataset("slliac/traffic-analysis", split="train")
+            dataset_list = [row for row in dataset]
+            dataset_list.sort(key=lambda x: x['capture_time'], reverse=True)
+
+            dataset_dict = {}
+            for row in dataset_list:
+                loc_id = row['location_id']
+                if loc_id in needed_keys:
+                    if loc_id not in dataset_dict:
+                        dataset_dict[loc_id] = []
+                    if len(dataset_dict[loc_id]) < 10:  # Store up to 10 records for averaging
+                        dataset_dict[loc_id].append(row)
+
+            # Only load if we have keys to load
+            if needed_keys:
+                with oracledb.connect(**self.connection_params) as conn:
+                    cursor = conn.cursor()
+
+                    # Prepare placeholders for the IN clause
+                    placeholders = ','.join([':' + str(i + 1) for i in range(len(needed_keys))])
+
+                    query = f"""
+                        SELECT KEY, LATITUDE, LONGITUDE 
+                        FROM TD_TRAFFIC_CAMERA_LOCATION 
+                        WHERE KEY IN ({placeholders})
+                        AND LATITUDE IS NOT NULL 
+                        AND LONGITUDE IS NOT NULL
+                    """
 
-    def add_spots_to_map(self, folium_map):
-        for spot in self.traffic_spots:
-            spot.add_to_map(folium_map)
+                    cursor.execute(query, tuple(needed_keys))
+                    spots = cursor.fetchall()
+
+                    new_spots = [
+                        TrafficSpot(
+                            spot[0],
+                            spot[1],
+                            spot[2],
+                            dataset_dict.get(spot[0])
+                        )
+                        for spot in spots
+                    ]
+
+                    # Add to our collections
+                    for spot in new_spots:
+                        self.spot_dict[spot.key] = spot
+                        self.traffic_spots.append(spot)
+
+                    conn.commit()
+                    logging.info(f"Loaded {len(new_spots)} additional traffic spots")
+
+        except Exception as e:
+            logging.error(f"Error loading specific traffic spots: {str(e)}")
+
+    def add_spots_to_map(self, folium_map, spot_keys=None):
+        """Add only specific spots to map"""
+        if spot_keys is None:
+            # If no keys specified, add all loaded spots
+            for spot in self.traffic_spots:
+                spot.add_to_map(folium_map)
+        else:
+            # Add only the specified spots
+            for key in spot_keys:
+                if key in self.spot_dict:
+                    self.spot_dict[key].add_to_map(folium_map)
 
     def get_spot_by_key(self, key):
-        """Get a traffic spot by its key"""
-        for spot in self.traffic_spots:
-            if spot.key == key:
-                return spot
-        return None
+        """Get a traffic spot by its key, loading it if necessary"""
+        if key in self.spot_dict:
+            return self.spot_dict[key]
+
+        # Try to load it if we don't have it
+        self.load_specific_traffic_spots([key])
+
+        # Return if found, None otherwise
+        return self.spot_dict.get(key)

app.py

@@ -63,6 +63,7 @@ def render_review_dialog():
         else:
             st.info("No reviews available for this listing.")
 
+
 def main():
     st.set_page_config(
         layout="wide",
@@ -94,6 +95,10 @@ def main():
         st.session_state.current_review_listing = None
     if 'current_review_listing_name' not in st.session_state:
         st.session_state.current_review_listing_name = None
+    if 'show_traffic_explanation' not in st.session_state:
+        st.session_state.show_traffic_explanation = False
+    if 'show_search_explanation' not in st.session_state:
+        st.session_state.show_search_explanation = False
 
     # Initialize visualizer with loading message for tokenizer
     if 'visualizer' not in st.session_state:
@@ -108,6 +113,57 @@ def main():
         st.error("Error initializing the application. Please refresh the page.")
         return
 
+    # Show explanations if requested
+    if st.session_state.show_traffic_explanation:
+        with st.expander("📊 Traffic-Based Discount System", expanded=True):
+            st.markdown("""
+                ### How HKUST BNB+ Acheived (E)SG , use Traffic Spot from Department of Transport and do traffic analysis hence provided discount according 
+                to the average traffic on the previous days.
+
+                We use real-time traffic data to offer you the best possible rates:
+
+                * **Blue Camera Icons**: Areas with very low traffic (less than 2 vehicles detected)
+                  * Enjoy a peaceful stay with **20% DISCOUNT** on these properties!
+
+                * **Orange Camera Icons**: Areas with moderate traffic (2-5 vehicles detected)
+                  * Get a **10% DISCOUNT** on these properties!
+
+                * **Purple Camera Icons**: Areas with heavier traffic (more than 5 vehicles)
+                  * Standard rates apply for these properties
+                  
+                Look for the blue connecting lines on the map to see which traffic spot affects each property!
+                
+                Remark : Currently only few traffic spot avaliable, in the future will provide more.
+            """)
+            if st.button("Close", key="close_traffic_btn"):
+                st.session_state.show_traffic_explanation = False
+                st.rerun()
+
+    if st.session_state.show_search_explanation:
+        with st.expander("🔍 Smart Search System", expanded=True):
+            st.markdown("""
+                ### How HKUST BNB+ Acheived E(S)G , use keyword to provided semantic relevance analysis to matches the require need from HKUST Student
+
+                Our advanced search technology goes beyond simple keyword matching to understand the meaning behind your search terms:
+
+                When you search for terms like "quiet," "convenient," or "spacious," our system:
+                1. Analyzes both listing titles and actual guest reviews
+                2. Understands the context and meaning (not just matching exact words)
+                3. Ranks listings based on overall relevance to your search
+
+                **Search Match Types:**
+                * **"Strong match in title and reviews"** - Perfect matches in both property description and guest experiences
+                * **"Strong match in listing title"** - Property description matches your needs very well
+                * **"Strong match in reviews"** - Guest experiences align perfectly with what you're looking for
+                * **"Better match in listing title/reviews"** - One source is more relevant than the other
+                * **"Moderate semantic match"** - Some relevance but not a perfect match
+
+                This helps you find properties that truly match what you're looking for, even if they don't use the exact words in your search!
+            """)
+            if st.button("Close", key="close_search_btn"):
+                st.session_state.show_search_explanation = False
+                st.rerun()
+
     with st.sidebar:
         st.markdown(
             '<p class="sidebar-header">HKUST BNB+<BR/></p>',
@@ -133,6 +189,22 @@ def main():
         )
         show_traffic = st.checkbox("Show Traffic Cameras", value=True)
 
+        st.markdown('<hr style="margin: 20px 0; border: none; border-top: 1px solid #e0e0e0;">', unsafe_allow_html=True)
+
+        # Help section in sidebar
+        st.markdown("### 💡 Help & Information")
+
+        col1, col2 = st.columns(2)
+        with col1:
+            if st.button("Green Discount", key="traffic_info_btn"):
+                st.session_state.show_traffic_explanation = True
+                st.rerun()
+
+        with col2:
+            if st.button("Semantic Search", key="search_info_btn"):
+                st.session_state.show_search_explanation = True
+                st.rerun()
+
         if st.button("Reset All", key="reset_btn"):
             st.session_state.center_lat = None
             st.session_state.center_lng = None
@@ -140,6 +212,8 @@ def main():
             st.session_state.current_page = 1
             st.session_state.search_query = ""
             st.session_state.show_review_dialog = False
+            st.session_state.show_traffic_explanation = False
+            st.session_state.show_search_explanation = False
             st.rerun()
 
     # Create map and get data - pass current page information
@@ -221,7 +295,6 @@ def main():
                     st.session_state.scroll_to_review = True
                     st.rerun()
 
-
         st.markdown('</div>', unsafe_allow_html=True)
 
         # Pagination controls

style.css

@@ -417,4 +417,4 @@
     padding: 0 2px;
     border-radius: 2px;
     font-weight: bold;
-}
+}