SY_50_WomenSafety

Team 50-SheShield/README.md

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+Problem Statement: Implementing Shesheild, a safety system that detects threats, provides the shortest path to safe zones, enables discreet emergency alerts, and safeguards users from online harassment through real-time monitoring and warnings.
+
+1. Emergency Alert System
+Function: Sends discreet emergency messages and continuously shares the user’s location with listed emergency contacts.
+
+Data Structures Used:
+1. List: Stores emergency contacts for iteration during message dispatch.
+2. Timer/Loop Control: Handles repetitive location sharing at fixed intervals.
+
+2. Online Harassment Detector
+Function: Detects abusive content in messages and offers the recipient options to report, block, or restrict the sender.
+
+Data Structures Used:
+1. Set: Maintains a list of offensive words for fast lookups.
+2. Dictionary: Tracks the number of reports per user.
+3. Set: Stores blocked users for quick access and verification.
+
+3. Safe Zone Navigator
+Function: Guides a user to the nearest safe zone (e.g., police station or hospital) using shortest path algorithms.
+
+Data Structures Used:
+1. Graph (Adjacency List): Models the map with locations and paths.
+2. Priority Queue: Used in Dijkstra’s Algorithm to compute shortest paths.
+3. List/Array: Tracks distances and previous nodes for path reconstruction.
+
+
+Link to video : https://drive.google.com/drive/folders/1bFDvTsIMjSMDcaurcrhHFKaF7auEHTK8?usp=sharing

Team 50-SheShield/Sheshield.py

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+import streamlit as st
+import heapq
+import random
+
+# Predefined locations
+locations = {
+    'Library': {'crime_rate': 0.2},
+    'Cafeteria': {'crime_rate': 0.3},
+    'SafeZone': {'crime_rate': 0.1},
+    'Bookstore': {'crime_rate': 0.25},
+    'Campus Center': {'crime_rate': 0.3},
+    'Hostel': {'crime_rate': 0.75},
+    'Dark Alley': {'crime_rate': 0.9},
+    'Parking Lot': {'crime_rate': 0.85},
+    'Abandoned Building': {'crime_rate': 0.95},
+    'Empty Street': {'crime_rate': 0.8}
+}
+
+# Distances between locations (graph)
+graph = {
+    'Library': {'Cafeteria': 0.5, 'SafeZone': 1.0},
+    'Cafeteria': {'Library': 0.5, 'Hostel': 1.0},
+    'SafeZone': {'Library': 1.0, 'Campus Center': 1.5},
+    'Bookstore': {'Campus Center': 0.7},
+    'Campus Center': {'Bookstore': 0.7, 'SafeZone': 1.5},
+    'Hostel': {'Cafeteria': 1.0, 'Dark Alley': 1.5},
+    'Dark Alley': {'Hostel': 1.5, 'Parking Lot': 1.0},
+    'Parking Lot': {'Dark Alley': 1.0, 'Abandoned Building': 1.0},
+    'Abandoned Building': {'Parking Lot': 1.0, 'Empty Street': 0.5},
+    'Empty Street': {'Abandoned Building': 0.5}
+}
+
+# Dijkstra’s Algorithm
+def dijkstra(graph, start, end):
+    queue = [(0, start)]
+    distances = {start: 0}
+    previous = {start: None}
+
+    while queue:
+        dist, node = heapq.heappop(queue)
+        if node == end:
+            path = []
+            while node:
+                path.append(node)
+                node = previous[node]
+            return path[::-1]
+        for neighbor, weight in graph.get(node, {}).items():
+            new_dist = dist + weight
+            if neighbor not in distances or new_dist < distances[neighbor]:
+                distances[neighbor] = new_dist
+                previous[neighbor] = node
+                heapq.heappush(queue, (new_dist, neighbor))
+    return None
+
+# Safety Check
+def check_safety(location):
+    rate = locations[location]['crime_rate']
+    if rate <= 0.3:
+        return "Safe Zone"
+    elif rate <= 0.7:
+        return "Moderate Risk"
+    else:
+        return "Unsafe Zone"
+
+# Harassment Detection
+class HarassmentMonitor:
+    def __init__(self):
+        if "blocked_users" not in st.session_state:
+            st.session_state.blocked_users = set()
+        if "user_reports" not in st.session_state:
+            st.session_state.user_reports = {}
+        self.abusive_words = {
+    "inappropriate", "offensive", "rude", "harsh", "disrespectful", "insult"
+}
+
+
+    def contains_abusive_word(self, message):
+        lower_msg = message.lower()
+        return any(bad_word in lower_msg for bad_word in self.abusive_words)
+
+    def handle_abusive_message(self, sender, recipient, message):
+        if self.contains_abusive_word(message):
+            st.warning("Message flagged as abusive content.")
+
+            st.markdown("---")
+            st.subheader("Actions you can take:")
+            col1, col2, col3, col4, col5 = st.columns(5)
+
+            # Block
+            if col1.button("\U0001F6D1 Block", key=f"block_{sender}"):
+                st.session_state.blocked_users.add(sender)
+                st.session_state[f"{sender}_action"] = "Blocked"
+
+            # Restrict
+            if col2.button("\U0001F512 Restrict", key=f"restrict_{sender}"):
+                st.session_state[f"{sender}_action"] = "Restricted"
+
+            # Remove
+            if col3.button("\u274E Remove", key=f"remove_{sender}"):
+                st.session_state[f"{sender}_action"] = "Removed"
+
+            # Report
+            if col4.button("\U0001F4E3 Report", key=f"report_{sender}"):
+                st.session_state.user_reports[sender] = st.session_state.user_reports.get(sender, 0) + 1
+                st.session_state[f"{sender}_action"] = "Reported"
+
+            # Ignore
+            if col5.button("\U0001F648 Ignore", key=f"ignore_{sender}"):
+                st.session_state[f"{sender}_action"] = "Ignored"
+
+            # Show status
+            action = st.session_state.get(f"{sender}_action")
+            if action:
+                st.info(f"User **{sender}** has been **{action.lower()}**.")
+
+            # Log
+            with st.expander("View Block/Report Status Log"):
+                st.write("Blocked Users:", list(st.session_state.blocked_users))
+                if sender in st.session_state.user_reports:
+                    st.write(f"{sender} has been reported {st.session_state.user_reports[sender]} times.")
+        else:
+            st.success(f"Message sent to **{recipient}** successfully.")
+
+# Streamlit UI
+def main():
+    st.set_page_config(page_title="SheShield Safety System", page_icon="\U0001F6E1")
+    st.title("\U0001F6E1 SheShield Safety System")
+
+    menu = ["Safety Navigation", "Harassment Detection"]
+    choice = st.sidebar.selectbox("Choose a Feature", menu)
+
+    if choice == "Safety Navigation":
+        st.subheader("\U0001F4CD Safety Navigation System")
+
+        if "selected_location" not in st.session_state:
+            st.session_state.selected_location = None
+
+        st.markdown("### Available Locations:")
+        st.markdown(", ".join([f"**{loc}**" for loc in locations.keys()]))
+
+        st.markdown("### Select Your Current Location:")
+        col_buttons = st.columns(5)
+        for idx, loc in enumerate(locations.keys()):
+            if col_buttons[idx % 5].button(loc):
+                st.session_state.selected_location = loc
+
+        if st.session_state.selected_location:
+            selected_location = st.session_state.selected_location
+            safety = check_safety(selected_location)
+            st.info(f"{selected_location} is classified as: **{safety}**")
+
+            if safety == "Unsafe Zone":
+                if st.button("Find Path to SafeZone"):
+                    path = dijkstra(graph, selected_location, "SafeZone")
+                    if path:
+                        st.success("Shortest path to SafeZone:")
+                        st.markdown(" → ".join(path))
+                        distance = sum([graph[path[i]][path[i + 1]] for i in range(len(path) - 1)])
+                        st.info(f"Distance: **{distance} km**")
+                        crowd = random.randint(3, 20)
+                        st.info(f"People in SafeZone: **{crowd}**")
+                    else:
+                        st.error("No path to SafeZone found.")
+            else:
+                st.success("You are in a safe or moderately safe area.")
+        else:
+            st.warning("Please select your current location from the options above.")
+
+    elif choice == "Harassment Detection":
+        st.subheader("\U0001F4E8 Harassment Detection System")
+        monitor = HarassmentMonitor()
+
+        sender = st.text_input("Sender Username:", placeholder="e.g., User123")
+        recipient = st.text_input("Recipient Username:", placeholder="e.g., Friend456")
+        message = st.text_area("Enter your message:", placeholder="Type here...")
+
+        if st.button("Send Message"):
+            if sender and recipient and message.strip():
+                monitor.handle_abusive_message(sender, recipient, message)
+            else:
+                st.error("Please fill in all fields before sending the message.")
+
+if __name__ == "__main__":
+    main()