diff --git a/ALONSO_2023_MONZA_RACE b/ALONSO_2023_MONZA_RACE
new file mode 100644
index 0000000..43a7223
--- /dev/null
+++ b/ALONSO_2023_MONZA_RACE
@@ -0,0 +1,16585 @@
+,lap_number,total_laps,speed,overall_time,throttle,brake,tire_compound,tire_life_laps,track_temperature,rainfall
+0,1.0,51.0,0.0,0 days 01:22:21.734000,23.0,False,MEDIUM,1.0,42.5,False
+1,1.0,51.0,0.0,0 days 01:22:21.894000,23.0,False,MEDIUM,1.0,42.5,False
+2,1.0,51.0,4.0,0 days 01:22:22.214000,26.0,False,MEDIUM,1.0,42.5,False
+3,1.0,51.0,14.0,0 days 01:22:22.494000,24.0,False,MEDIUM,1.0,42.5,False
+4,1.0,51.0,24.0,0 days 01:22:22.774000,24.0,False,MEDIUM,1.0,42.5,False
+5,1.0,51.0,31.0,0 days 01:22:22.974000,26.0,False,MEDIUM,1.0,42.5,False
+6,1.0,51.0,38.0,0 days 01:22:23.254000,36.0,False,MEDIUM,1.0,42.5,False
+7,1.0,51.0,50.0,0 days 01:22:23.494000,41.0,False,MEDIUM,1.0,42.5,False
+8,1.0,51.0,58.0,0 days 01:22:23.694000,44.0,False,MEDIUM,1.0,42.5,False
+9,1.0,51.0,71.0,0 days 01:22:23.974000,55.0,False,MEDIUM,1.0,42.5,False
+10,1.0,51.0,88.0,0 days 01:22:24.414000,64.0,False,MEDIUM,1.0,42.5,False
+11,1.0,51.0,100.0,0 days 01:22:24.734000,69.0,False,MEDIUM,1.0,42.5,False
+12,1.0,51.0,109.0,0 days 01:22:24.974000,78.0,False,MEDIUM,1.0,42.5,False
+13,1.0,51.0,124.0,0 days 01:22:25.254000,97.0,False,MEDIUM,1.0,42.5,False
+14,1.0,51.0,133.0,0 days 01:22:25.414000,100.0,False,MEDIUM,1.0,42.5,False
+15,1.0,51.0,139.0,0 days 01:22:25.654000,100.0,False,MEDIUM,1.0,42.5,False
+16,1.0,51.0,153.0,0 days 01:22:25.894000,100.0,False,MEDIUM,1.0,42.5,False
+17,1.0,51.0,170.0,0 days 01:22:26.253000,100.0,False,MEDIUM,1.0,42.5,False
+18,1.0,51.0,182.0,0 days 01:22:26.613000,100.0,False,MEDIUM,1.0,42.5,False
+19,1.0,51.0,189.0,0 days 01:22:26.773000,100.0,False,MEDIUM,1.0,42.5,False
+20,1.0,51.0,192.0,0 days 01:22:26.934000,100.0,False,MEDIUM,1.0,42.5,False
+21,1.0,51.0,202.0,0 days 01:22:27.174000,100.0,False,MEDIUM,1.0,42.5,False
+22,1.0,51.0,202.0,0 days 01:22:27.374000,100.0,False,MEDIUM,1.0,42.5,False
+23,1.0,51.0,211.0,0 days 01:22:27.614000,100.0,False,MEDIUM,1.0,42.5,False
+24,1.0,51.0,220.0,0 days 01:22:27.894000,100.0,False,MEDIUM,1.0,42.5,False
+25,1.0,51.0,225.0,0 days 01:22:28.334000,100.0,False,MEDIUM,1.0,42.5,False
+26,1.0,51.0,228.0,0 days 01:22:28.654000,100.0,False,MEDIUM,1.0,42.5,False
+27,1.0,51.0,228.0,0 days 01:22:28.854000,100.0,False,MEDIUM,1.0,42.5,False
+28,1.0,51.0,252.0,0 days 01:22:29.174000,100.0,False,MEDIUM,1.0,42.5,False
+29,1.0,51.0,262.0,0 days 01:22:29.614000,99.0,False,MEDIUM,1.0,42.5,False
+30,1.0,51.0,266.0,0 days 01:22:29.774000,100.0,False,MEDIUM,1.0,42.5,False
+31,1.0,51.0,271.0,0 days 01:22:30.254000,100.0,False,MEDIUM,1.0,42.5,False
+32,1.0,51.0,274.0,0 days 01:22:30.534000,100.0,False,MEDIUM,1.0,42.5,False
+33,1.0,51.0,277.0,0 days 01:22:30.734000,100.0,False,MEDIUM,1.0,42.5,False
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+35,1.0,51.0,279.0,0 days 01:22:31.254000,0.0,True,MEDIUM,1.0,42.5,False
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+37,1.0,51.0,269.0,0 days 01:22:31.734000,38.0,False,MEDIUM,1.0,42.5,False
+38,1.0,51.0,268.0,0 days 01:22:31.974000,0.0,True,MEDIUM,1.0,42.5,False
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+60,1.0,51.0,61.0,0 days 01:22:38.294000,0.0,True,MEDIUM,1.0,42.5,False
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+63,1.0,51.0,60.0,0 days 01:22:39.054000,0.0,False,MEDIUM,1.0,42.5,False
+64,1.0,51.0,55.0,0 days 01:22:39.373000,7.0,False,MEDIUM,1.0,42.5,False
+65,1.0,51.0,56.0,0 days 01:22:39.653000,11.0,False,MEDIUM,1.0,42.5,False
+66,1.0,51.0,58.0,0 days 01:22:39.853000,18.0,False,MEDIUM,1.0,42.5,False
+67,1.0,51.0,60.0,0 days 01:22:40.054000,31.0,False,MEDIUM,1.0,42.5,False
+68,1.0,51.0,68.0,0 days 01:22:40.414000,44.0,False,MEDIUM,1.0,42.5,False
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diff --git a/fetch_data.ipynb b/fetch_data.ipynb
new file mode 100644
index 0000000..9e77b79
--- /dev/null
+++ b/fetch_data.ipynb
@@ -0,0 +1,649 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "9a9714f8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "core           INFO \tLoading data for Italian Grand Prix - Race [v3.6.1]\n",
+      "req            INFO \tUsing cached data for session_info\n",
+      "req            INFO \tUsing cached data for driver_info\n",
+      "req            INFO \tUsing cached data for session_info\n",
+      "req            INFO \tUsing cached data for driver_info\n",
+      "req            INFO \tUsing cached data for session_status_data\n",
+      "req            INFO \tUsing cached data for lap_count\n",
+      "req            INFO \tUsing cached data for track_status_data\n",
+      "req            INFO \tUsing cached data for session_status_data\n",
+      "req            INFO \tUsing cached data for lap_count\n",
+      "req            INFO \tUsing cached data for track_status_data\n",
+      "req            INFO \tUsing cached data for _extended_timing_data\n",
+      "req            INFO \tUsing cached data for timing_app_data\n",
+      "core           INFO \tProcessing timing data...\n",
+      "req            INFO \tUsing cached data for _extended_timing_data\n",
+      "req            INFO \tUsing cached data for timing_app_data\n",
+      "core           INFO \tProcessing timing data...\n",
+      "req            INFO \tUsing cached data for car_data\n",
+      "req            INFO \tUsing cached data for car_data\n",
+      "req            INFO \tUsing cached data for position_data\n",
+      "req            INFO \tUsing cached data for position_data\n",
+      "req            INFO \tUsing cached data for weather_data\n",
+      "req            INFO \tUsing cached data for race_control_messages\n",
+      "core        WARNING \tDriver 1 completed the race distance 06:25.888000 before the recorded end of the session.\n",
+      "core        WARNING \tDriver 11 completed the race distance 06:19.824000 before the recorded end of the session.\n",
+      "core        WARNING \tDriver 55 completed the race distance 06:14.695000 before the recorded end of the session.\n",
+      "core        WARNING \tDriver 16 completed the race distance 06:14.511000 before the recorded end of the session.\n",
+      "core        WARNING \tDriver 63 completed the race distance 06:07.860000 before the recorded end of the session.\n",
+      "core        WARNING \tDriver 44 completed the race distance 05:48.209000 before the recorded end of the session.\n",
+      "req            INFO \tUsing cached data for weather_data\n",
+      "req            INFO \tUsing cached data for race_control_messages\n",
+      "core        WARNING \tDriver 1 completed the race distance 06:25.888000 before the recorded end of the session.\n",
+      "core        WARNING \tDriver 11 completed the race distance 06:19.824000 before the recorded end of the session.\n",
+      "core        WARNING \tDriver 55 completed the race distance 06:14.695000 before the recorded end of the session.\n",
+      "core        WARNING \tDriver 16 completed the race distance 06:14.511000 before the recorded end of the session.\n",
+      "core        WARNING \tDriver 63 completed the race distance 06:07.860000 before the recorded end of the session.\n",
+      "core        WARNING \tDriver 44 completed the race distance 05:48.209000 before the recorded end of the session.\n",
+      "core        WARNING \tDriver 23 completed the race distance 05:40.782000 before the recorded end of the session.\n",
+      "core        WARNING \tDriver 4 completed the race distance 05:40.439000 before the recorded end of the session.\n",
+      "core        WARNING \tDriver 14 completed the race distance 05:39.594000 before the recorded end of the session.\n",
+      "core        WARNING \tDriver 23 completed the race distance 05:40.782000 before the recorded end of the session.\n",
+      "core        WARNING \tDriver 4 completed the race distance 05:40.439000 before the recorded end of the session.\n",
+      "core        WARNING \tDriver 14 completed the race distance 05:39.594000 before the recorded end of the session.\n",
+      "core           INFO \tFinished loading data for 20 drivers: ['1', '11', '55', '16', '63', '44', '23', '4', '14', '77', '40', '81', '2', '24', '10', '18', '27', '20', '31', '22']\n",
+      "core           INFO \tFinished loading data for 20 drivers: ['1', '11', '55', '16', '63', '44', '23', '4', '14', '77', '40', '81', '2', '24', '10', '18', '27', '20', '31', '22']\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Created dataframe with 16584 rows\n",
+      "Total laps in race: 51.0\n",
+      "Laps covered: 1.0 to 51.0\n",
+      "Tire life range: 1.0 to 33.0 laps\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>lap_number</th>\n",
+       "      <th>total_laps</th>\n",
+       "      <th>speed</th>\n",
+       "      <th>overall_time</th>\n",
+       "      <th>throttle</th>\n",
+       "      <th>brake</th>\n",
+       "      <th>tire_compound</th>\n",
+       "      <th>tire_life_laps</th>\n",
+       "      <th>track_temperature</th>\n",
+       "      <th>rainfall</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0 days 01:22:21.734000</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>MEDIUM</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>42.5</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0 days 01:22:21.894000</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>MEDIUM</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>42.5</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0 days 01:22:22.214000</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>MEDIUM</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>42.5</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>0 days 01:22:22.494000</td>\n",
+       "      <td>24.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>MEDIUM</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>42.5</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>24.0</td>\n",
+       "      <td>0 days 01:22:22.774000</td>\n",
+       "      <td>24.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>MEDIUM</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>42.5</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>0 days 01:22:22.974000</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>MEDIUM</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>42.5</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>0 days 01:22:23.254000</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>MEDIUM</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>42.5</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>50.0</td>\n",
+       "      <td>0 days 01:22:23.494000</td>\n",
+       "      <td>41.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>MEDIUM</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>42.5</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>58.0</td>\n",
+       "      <td>0 days 01:22:23.694000</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>MEDIUM</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>42.5</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>1.0</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>71.0</td>\n",
+       "      <td>0 days 01:22:23.974000</td>\n",
+       "      <td>55.0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>MEDIUM</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>42.5</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   lap_number  total_laps  speed           overall_time  throttle  brake  \\\n",
+       "0         1.0        51.0    0.0 0 days 01:22:21.734000      23.0  False   \n",
+       "1         1.0        51.0    0.0 0 days 01:22:21.894000      23.0  False   \n",
+       "2         1.0        51.0    4.0 0 days 01:22:22.214000      26.0  False   \n",
+       "3         1.0        51.0   14.0 0 days 01:22:22.494000      24.0  False   \n",
+       "4         1.0        51.0   24.0 0 days 01:22:22.774000      24.0  False   \n",
+       "5         1.0        51.0   31.0 0 days 01:22:22.974000      26.0  False   \n",
+       "6         1.0        51.0   38.0 0 days 01:22:23.254000      36.0  False   \n",
+       "7         1.0        51.0   50.0 0 days 01:22:23.494000      41.0  False   \n",
+       "8         1.0        51.0   58.0 0 days 01:22:23.694000      44.0  False   \n",
+       "9         1.0        51.0   71.0 0 days 01:22:23.974000      55.0  False   \n",
+       "\n",
+       "  tire_compound  tire_life_laps  track_temperature  rainfall  \n",
+       "0        MEDIUM             1.0               42.5     False  \n",
+       "1        MEDIUM             1.0               42.5     False  \n",
+       "2        MEDIUM             1.0               42.5     False  \n",
+       "3        MEDIUM             1.0               42.5     False  \n",
+       "4        MEDIUM             1.0               42.5     False  \n",
+       "5        MEDIUM             1.0               42.5     False  \n",
+       "6        MEDIUM             1.0               42.5     False  \n",
+       "7        MEDIUM             1.0               42.5     False  \n",
+       "8        MEDIUM             1.0               42.5     False  \n",
+       "9        MEDIUM             1.0               42.5     False  "
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\"\"\"\n",
+    "FastF1 Data Fetcher for HPC F1 AI Strategy System\n",
+    "\n",
+    "Downloads telemetry and race data from a specific F1 session to simulate\n",
+    "live telemetry streaming from a Raspberry Pi \"racecar\" to the HPC layer.\n",
+    "\n",
+    "Usage:\n",
+    "    python fetch_race_data.py --year 2024 --race \"Monaco\" --driver VER --output data/\n",
+    "\"\"\"\n",
+    "import fastf1\n",
+    "import pandas as pd\n",
+    "\n",
+    "# 1. Load the session\n",
+    "session = fastf1.get_session(2023, 'Monza', 'R')\n",
+    "session.load(telemetry=True, laps=True, weather=True)\n",
+    "\n",
+    "# 2. Pick the driver\n",
+    "driver_laps = session.laps.pick_drivers('ALO')\n",
+    "\n",
+    "# Get total number of laps in the race (maximum lap number from all drivers)\n",
+    "total_laps = session.laps['LapNumber'].max()\n",
+    "\n",
+    "# 3. Collect all telemetry data with lap information\n",
+    "telemetry_list = []\n",
+    "\n",
+    "for lap_idx in driver_laps.index:\n",
+    "    lap = driver_laps.loc[lap_idx]\n",
+    "    lap_number = lap['LapNumber']\n",
+    "    tire_compound = lap['Compound']\n",
+    "    tire_life = lap['TyreLife']  # Number of laps on current tires\n",
+    "    \n",
+    "    # Get telemetry for this lap\n",
+    "    car_data = lap.get_car_data()\n",
+    "    \n",
+    "    if car_data is not None and len(car_data) > 0:\n",
+    "        # Add lap number, tire compound, and tire life to each telemetry point\n",
+    "        car_data['LapNumber'] = lap_number\n",
+    "        car_data['Compound'] = tire_compound\n",
+    "        car_data['TyreLife'] = tire_life\n",
+    "        telemetry_list.append(car_data)\n",
+    "\n",
+    "# 4. Combine all telemetry data\n",
+    "all_telemetry = pd.concat(telemetry_list, ignore_index=True)\n",
+    "\n",
+    "# 5. Get weather data\n",
+    "weather = session.weather_data\n",
+    "\n",
+    "# 6. Merge telemetry with weather based on timestamp\n",
+    "# First, ensure both have SessionTime column\n",
+    "all_telemetry['SessionTime'] = pd.to_timedelta(all_telemetry['SessionTime'])\n",
+    "weather['SessionTime'] = pd.to_timedelta(weather['Time'])\n",
+    "\n",
+    "# Merge using merge_asof for time-based joining\n",
+    "all_telemetry = all_telemetry.sort_values('SessionTime')\n",
+    "weather = weather.sort_values('SessionTime')\n",
+    "\n",
+    "merged_data = pd.merge_asof(\n",
+    "    all_telemetry,\n",
+    "    weather[['SessionTime', 'TrackTemp', 'Rainfall']],\n",
+    "    on='SessionTime',\n",
+    "    direction='nearest'\n",
+    ")\n",
+    "\n",
+    "# 7. Create final dataframe with requested columns\n",
+    "final_df = pd.DataFrame({\n",
+    "    'lap_number': merged_data['LapNumber'],\n",
+    "    'total_laps': total_laps,  # Total laps in the race\n",
+    "    'speed': merged_data['Speed'],\n",
+    "    'overall_time': merged_data['SessionTime'],\n",
+    "    'throttle': merged_data['Throttle'],\n",
+    "    'brake': merged_data['Brake'],\n",
+    "    'tire_compound': merged_data['Compound'],\n",
+    "    'tire_life_laps': merged_data['TyreLife'],  # Number of laps on current tires\n",
+    "    'track_temperature': merged_data['TrackTemp'],\n",
+    "    'rainfall': merged_data['Rainfall']\n",
+    "})\n",
+    "\n",
+    "print(f\"Created dataframe with {len(final_df)} rows\")\n",
+    "print(f\"Total laps in race: {total_laps}\")\n",
+    "print(f\"Laps covered: {final_df['lap_number'].min()} to {final_df['lap_number'].max()}\")\n",
+    "print(f\"Tire life range: {final_df['tire_life_laps'].min()} to {final_df['tire_life_laps'].max()} laps\")\n",
+    "final_df.head(10)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "45d27f05",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Dataframe Info:\n",
+      "Total telemetry points: 16584\n",
+      "\n",
+      "Column types:\n",
+      "lap_number                   float64\n",
+      "total_laps                   float64\n",
+      "speed                        float64\n",
+      "overall_time         timedelta64[ns]\n",
+      "throttle                     float64\n",
+      "brake                           bool\n",
+      "tire_compound                 object\n",
+      "tire_life_laps               float64\n",
+      "track_temperature            float64\n",
+      "rainfall                        bool\n",
+      "dtype: object\n",
+      "\n",
+      "Basic statistics:\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>lap_number</th>\n",
+       "      <th>total_laps</th>\n",
+       "      <th>speed</th>\n",
+       "      <th>overall_time</th>\n",
+       "      <th>throttle</th>\n",
+       "      <th>tire_life_laps</th>\n",
+       "      <th>track_temperature</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>16584.000000</td>\n",
+       "      <td>16584.0</td>\n",
+       "      <td>16584.000000</td>\n",
+       "      <td>16584</td>\n",
+       "      <td>16584.000000</td>\n",
+       "      <td>16584.000000</td>\n",
+       "      <td>16584.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>25.891341</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>235.570188</td>\n",
+       "      <td>0 days 01:59:34.577446394</td>\n",
+       "      <td>72.291546</td>\n",
+       "      <td>15.339243</td>\n",
+       "      <td>42.908816</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>14.710977</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>76.948906</td>\n",
+       "      <td>0 days 00:21:30.065940875</td>\n",
+       "      <td>40.561237</td>\n",
+       "      <td>8.558018</td>\n",
+       "      <td>0.897756</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0 days 01:22:21.734000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>40.800000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>13.000000</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>180.000000</td>\n",
+       "      <td>0 days 01:40:53.558000</td>\n",
+       "      <td>40.000000</td>\n",
+       "      <td>8.000000</td>\n",
+       "      <td>42.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>26.000000</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>245.000000</td>\n",
+       "      <td>0 days 01:59:31.222000</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>15.000000</td>\n",
+       "      <td>43.100000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>39.000000</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>309.000000</td>\n",
+       "      <td>0 days 02:18:13.365000</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>21.000000</td>\n",
+       "      <td>43.600000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>51.000000</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>351.000000</td>\n",
+       "      <td>0 days 02:36:49.228000</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>33.000000</td>\n",
+       "      <td>44.400000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         lap_number  total_laps         speed               overall_time  \\\n",
+       "count  16584.000000     16584.0  16584.000000                      16584   \n",
+       "mean      25.891341        51.0    235.570188  0 days 01:59:34.577446394   \n",
+       "std       14.710977         0.0     76.948906  0 days 00:21:30.065940875   \n",
+       "min        1.000000        51.0      0.000000     0 days 01:22:21.734000   \n",
+       "25%       13.000000        51.0    180.000000     0 days 01:40:53.558000   \n",
+       "50%       26.000000        51.0    245.000000     0 days 01:59:31.222000   \n",
+       "75%       39.000000        51.0    309.000000     0 days 02:18:13.365000   \n",
+       "max       51.000000        51.0    351.000000     0 days 02:36:49.228000   \n",
+       "\n",
+       "           throttle  tire_life_laps  track_temperature  \n",
+       "count  16584.000000    16584.000000       16584.000000  \n",
+       "mean      72.291546       15.339243          42.908816  \n",
+       "std       40.561237        8.558018           0.897756  \n",
+       "min        0.000000        1.000000          40.800000  \n",
+       "25%       40.000000        8.000000          42.500000  \n",
+       "50%      100.000000       15.000000          43.100000  \n",
+       "75%      100.000000       21.000000          43.600000  \n",
+       "max      100.000000       33.000000          44.400000  "
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Display dataframe info and sample statistics\n",
+    "print(\"Dataframe Info:\")\n",
+    "print(f\"Total telemetry points: {len(final_df)}\")\n",
+    "print(f\"\\nColumn types:\")\n",
+    "print(final_df.dtypes)\n",
+    "print(f\"\\nBasic statistics:\")\n",
+    "final_df.describe()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "2fbcd2f9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "final_df.to_csv(\"ALONSO_2023_MONZA_RACE\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "729fb12e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Tire compound usage throughout the race:\n",
+      "    lap_number tire_compound  tire_life_laps\n",
+      "0          1.0        MEDIUM             1.0\n",
+      "1          2.0        MEDIUM             2.0\n",
+      "2          3.0        MEDIUM             3.0\n",
+      "3          4.0        MEDIUM             4.0\n",
+      "4          5.0        MEDIUM             5.0\n",
+      "5          6.0        MEDIUM             6.0\n",
+      "6          7.0        MEDIUM             7.0\n",
+      "7          8.0        MEDIUM             8.0\n",
+      "8          9.0        MEDIUM             9.0\n",
+      "9         10.0        MEDIUM            10.0\n",
+      "10        11.0        MEDIUM            11.0\n",
+      "11        12.0        MEDIUM            12.0\n",
+      "12        13.0        MEDIUM            13.0\n",
+      "13        14.0        MEDIUM            14.0\n",
+      "14        15.0        MEDIUM            15.0\n",
+      "15        16.0        MEDIUM            16.0\n",
+      "16        17.0        MEDIUM            17.0\n",
+      "17        18.0        MEDIUM            18.0\n",
+      "18        19.0        MEDIUM            19.0\n",
+      "19        20.0        MEDIUM            20.0\n",
+      "20        21.0        MEDIUM            21.0\n",
+      "21        22.0          HARD             4.0\n",
+      "22        23.0          HARD             5.0\n",
+      "23        24.0          HARD             6.0\n",
+      "24        25.0          HARD             7.0\n",
+      "25        26.0          HARD             8.0\n",
+      "26        27.0          HARD             9.0\n",
+      "27        28.0          HARD            10.0\n",
+      "28        29.0          HARD            11.0\n",
+      "29        30.0          HARD            12.0\n",
+      "30        31.0          HARD            13.0\n",
+      "31        32.0          HARD            14.0\n",
+      "32        33.0          HARD            15.0\n",
+      "33        34.0          HARD            16.0\n",
+      "34        35.0          HARD            17.0\n",
+      "35        36.0          HARD            18.0\n",
+      "36        37.0          HARD            19.0\n",
+      "37        38.0          HARD            20.0\n",
+      "38        39.0          HARD            21.0\n",
+      "39        40.0          HARD            22.0\n",
+      "40        41.0          HARD            23.0\n",
+      "41        42.0          HARD            24.0\n",
+      "42        43.0          HARD            25.0\n",
+      "43        44.0          HARD            26.0\n",
+      "44        45.0          HARD            27.0\n",
+      "45        46.0          HARD            28.0\n",
+      "46        47.0          HARD            29.0\n",
+      "47        48.0          HARD            30.0\n",
+      "48        49.0          HARD            31.0\n",
+      "49        50.0          HARD            32.0\n",
+      "50        51.0          HARD            33.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Show tire compound changes and stint information\n",
+    "print(\"Tire compound usage throughout the race:\")\n",
+    "tire_changes = final_df.groupby(['lap_number', 'tire_compound', 'tire_life_laps']).size().reset_index(name='count')\n",
+    "tire_changes = tire_changes.groupby(['lap_number', 'tire_compound', 'tire_life_laps']).first().reset_index()[['lap_number', 'tire_compound', 'tire_life_laps']]\n",
+    "print(tire_changes.drop_duplicates())\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d9ebc90c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "base",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/scripts/simulate_pi_stream.py b/scripts/simulate_pi_stream.py
index 2499c3a..4370d4b 100644
--- a/scripts/simulate_pi_stream.py
+++ b/scripts/simulate_pi_stream.py
@@ -1,96 +1,137 @@
 """
 Raspberry Pi Telemetry Stream Simulator
 
-Replays downloaded FastF1 data as if it's coming from a live Raspberry Pi sensor.
-Sends data to the HPC simulation layer via HTTP POST.
+Reads the ALONSO_2023_MONZA_RACE CSV file row by row and simulates
+live telemetry streaming from a Raspberry Pi sensor.
+Sends data to the HPC simulation layer via HTTP POST at intervals
+determined by the time differences between consecutive rows.
 
 Usage:
-    python simulate_pi_stream.py --data data/race_data/VER_telemetry.json --speed 1.0
+    python simulate_pi_stream.py --data ALONSO_2023_MONZA_RACE --speed 1.0
 """
 
 import argparse
-import json
 import time
 import sys
 from pathlib import Path
-from typing import Dict, List, Any
-
+from typing import Dict, Any
+import pandas as pd
 import requests
 
 
-def load_telemetry(filepath: Path) -> List[Dict[str, Any]]:
-    """Load telemetry data from JSON file."""
-    with open(filepath, 'r') as f:
-        data = json.load(f)
-    print(f"✓ Loaded {len(data)} telemetry points from {filepath}")
+def load_telemetry_csv(filepath: Path) -> pd.DataFrame:
+    """Load telemetry data from CSV file."""
+    df = pd.read_csv(filepath, index_col=0)
+    
+    # Convert overall_time to timedelta if it's not already
+    if df['overall_time'].dtype == 'object':
+        df['overall_time'] = pd.to_timedelta(df['overall_time'])
+    
+    print(f"✓ Loaded {len(df)} telemetry points from {filepath}")
+    print(f"   Laps: {df['lap_number'].min():.0f} → {df['lap_number'].max():.0f}")
+    print(f"   Duration: {df['overall_time'].iloc[-1]}")
+    
+    return df
+
+
+def row_to_json(row: pd.Series) -> Dict[str, Any]:
+    """Convert a DataFrame row to a JSON-compatible dictionary."""
+    data = {
+        'lap_number': int(row['lap_number']) if pd.notna(row['lap_number']) else None,
+        'total_laps': int(row['total_laps']) if pd.notna(row['total_laps']) else None,
+        'speed': float(row['speed']) if pd.notna(row['speed']) else 0.0,
+        'throttle': float(row['throttle']) if pd.notna(row['throttle']) else 0.0,
+        'brake': bool(row['brake']),
+        'tire_compound': str(row['tire_compound']) if pd.notna(row['tire_compound']) else 'UNKNOWN',
+        'tire_life_laps': float(row['tire_life_laps']) if pd.notna(row['tire_life_laps']) else 0.0,
+        'track_temperature': float(row['track_temperature']) if pd.notna(row['track_temperature']) else 0.0,
+        'rainfall': bool(row['rainfall'])
+    }
     return data
 
 
 def simulate_stream(
-    telemetry: List[Dict[str, Any]],
+    df: pd.DataFrame,
     endpoint: str,
     speed: float = 1.0,
     start_lap: int = 1,
     end_lap: int = None
 ):
     """
-    Simulate live telemetry streaming.
+    Simulate live telemetry streaming based on actual time intervals in the data.
     
     Args:
-        telemetry: List of telemetry points
+        df: DataFrame with telemetry data
         endpoint: HPC API endpoint URL
         speed: Playback speed multiplier (1.0 = real-time, 2.0 = 2x speed)
         start_lap: Starting lap number
         end_lap: Ending lap number (None = all laps)
     """
     # Filter by lap range
-    filtered = [p for p in telemetry if p['lap'] >= start_lap]
+    filtered_df = df[df['lap_number'] >= start_lap].copy()
     if end_lap:
-        filtered = [p for p in filtered if p['lap'] <= end_lap]
+        filtered_df = filtered_df[filtered_df['lap_number'] <= end_lap].copy()
     
-    if not filtered:
+    if len(filtered_df) == 0:
         print("❌ No telemetry points in specified lap range")
         return
     
+    # Reset index for easier iteration
+    filtered_df = filtered_df.reset_index(drop=True)
+    
     print(f"\n🏁 Starting telemetry stream simulation")
     print(f"   Endpoint: {endpoint}")
     print(f"   Laps: {start_lap} → {end_lap or 'end'}")
     print(f"   Speed: {speed}x")
-    print(f"   Points: {len(filtered)}")
-    print(f"   Duration: {filtered[-1]['timestamp_ms'] / 1000.0:.1f}s\n")
+    print(f"   Points: {len(filtered_df)}")
     
-    start_time = time.time()
-    start_ts = filtered[0]['timestamp_ms']
+    total_duration = (filtered_df['overall_time'].iloc[-1] - filtered_df['overall_time'].iloc[0]).total_seconds()
+    print(f"   Duration: {total_duration:.1f}s (real-time) → {total_duration / speed:.1f}s (playback)\n")
     
     sent_count = 0
     error_count = 0
+    current_lap = start_lap
     
     try:
-        for i, point in enumerate(filtered):
-            # Calculate when this point should be sent
-            point_offset = (point['timestamp_ms'] - start_ts) / 1000.0 / speed
-            target_time = start_time + point_offset
+        for i in range(len(filtered_df)):
+            row = filtered_df.iloc[i]
             
-            # Wait until the right time
-            sleep_time = target_time - time.time()
-            if sleep_time > 0:
-                time.sleep(sleep_time)
+            # Calculate sleep time based on time difference to next row
+            if i < len(filtered_df) - 1:
+                next_row = filtered_df.iloc[i + 1]
+                time_diff = (next_row['overall_time'] - row['overall_time']).total_seconds()
+                sleep_time = time_diff / speed
+                
+                # Ensure positive sleep time
+                if sleep_time < 0:
+                    sleep_time = 0
+            else:
+                sleep_time = 0
+            
+            # Convert row to JSON
+            telemetry_point = row_to_json(row)
             
             # Send telemetry point
             try:
                 response = requests.post(
                     endpoint,
-                    json=point,
+                    json=telemetry_point,
                     timeout=2.0
                 )
                 
                 if response.status_code == 200:
                     sent_count += 1
-                    if sent_count % 100 == 0:
-                        elapsed = time.time() - start_time
-                        progress = (i + 1) / len(filtered) * 100
-                        print(f"  📡 Lap {point['lap']}: {sent_count} points sent "
-                              f"({progress:.1f}% complete, {elapsed:.1f}s elapsed)")
+                    
+                    # Print progress updates
+                    if row['lap_number'] > current_lap:
+                        current_lap = row['lap_number']
+                        progress = (i + 1) / len(filtered_df) * 100
+                        print(f"  📡 Lap {int(current_lap)}: {sent_count} points sent "
+                              f"({progress:.1f}% complete)")
+                    elif sent_count % 500 == 0:
+                        progress = (i + 1) / len(filtered_df) * 100
+                        print(f"  📡 Lap {int(row['lap_number'])}: {sent_count} points sent "
+                              f"({progress:.1f}% complete)")
                 else:
                     error_count += 1
                     print(f"  ⚠ HTTP {response.status_code}: {response.text[:50]}")
@@ -98,35 +139,47 @@ def simulate_stream(
             except requests.RequestException as e:
                 error_count += 1
                 if error_count % 10 == 0:
-                    print(f"  ⚠ Connection error ({error_count} total): {e}")
+                    print(f"  ⚠ Connection error ({error_count} total): {str(e)[:50]}")
+            
+            # Sleep until next point should be sent
+            if sleep_time > 0:
+                time.sleep(sleep_time)
         
         print(f"\n✅ Stream complete!")
         print(f"   Sent: {sent_count} points")
         print(f"   Errors: {error_count}")
-        print(f"   Duration: {time.time() - start_time:.1f}s")
         
     except KeyboardInterrupt:
         print(f"\n⏸ Stream interrupted by user")
-        print(f"   Sent: {sent_count}/{len(filtered)} points")
+        print(f"   Sent: {sent_count}/{len(filtered_df)} points")
 
 
 def main():
     parser = argparse.ArgumentParser(
-        description="Simulate Raspberry Pi telemetry streaming"
+        description="Simulate Raspberry Pi telemetry streaming from CSV data"
     )
-    parser.add_argument("--data", type=str, required=True, help="Path to telemetry JSON file")
+    parser.add_argument("--data", type=str, default="ALONSO_2023_MONZA_RACE",
+                        help="Path to telemetry CSV file")
     parser.add_argument("--endpoint", type=str, default="http://localhost:8000/telemetry",
                         help="HPC API endpoint")
-    parser.add_argument("--speed", type=float, default=1.0, help="Playback speed (1.0 = real-time)")
+    parser.add_argument("--speed", type=float, default=1.0, 
+                        help="Playback speed (1.0 = real-time, 10.0 = 10x speed)")
     parser.add_argument("--start-lap", type=int, default=1, help="Starting lap number")
     parser.add_argument("--end-lap", type=int, default=None, help="Ending lap number")
     
     args = parser.parse_args()
     
     try:
-        telemetry = load_telemetry(Path(args.data))
+        # Handle relative paths from the project root
+        data_path = Path(args.data)
+        if not data_path.is_absolute():
+            # Try relative to script location first
+            script_dir = Path(__file__).parent.parent
+            data_path = script_dir / args.data
+        
+        df = load_telemetry_csv(data_path)
         simulate_stream(
-            telemetry,
+            df,
             args.endpoint,
             args.speed,
             args.start_lap,
@@ -134,6 +187,7 @@ def main():
         )
     except FileNotFoundError:
         print(f"❌ File not found: {args.data}")
+        print(f"   Tried: {data_path}")
         sys.exit(1)
     except Exception as e:
         print(f"❌ Error: {e}")