diff --git a/containers/notebooks/app/continuous_alert.ipynb b/containers/notebooks/app/continuous_alert.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Notebook setup\n",
+    "Run the following cells to initiate notebook"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "from dotenv import load_dotenv\n",
+    "import os\n",
+    "from api import get_token, get_camera_token\n",
+    "from pyroclient import Client\n",
+    "import glob\n",
+    "from PIL import Image\n",
+    "import numpy as np\n",
+    "import io\n",
+    "import requests\n",
+    "import random\n",
+    "import shutil\n",
+    "from utils import read_pred_file\n",
+    "import time"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "API_URL = \"http://api:5050\"\n",
+    "load_dotenv(\"../.env\")\n",
+    "SUPERADMIN_LOGIN = os.environ.get(\"SUPERADMIN_LOGIN\")\n",
+    "SUPERADMIN_PWD = os.environ.get(\"SUPERADMIN_PWD\")\n",
+    "\n",
+    "# Get access token\n",
+    "admin_access_token = get_token(API_URL, SUPERADMIN_LOGIN, SUPERADMIN_PWD)\n",
+    "\n",
+    "# Download some relevant images and predictions\n",
+    "if not os.path.isdir(\"selection-true-positives\"):\n",
+    "    print(\"Images not found, dowloading ...\")\n",
+    "    url = \"https://github.com/pyronear/pyro-envdev/releases/download/v0.0.1/selection-true-positives.zip\"\n",
+    "    output_path = \"selection-true-positives.zip\"\n",
+    "\n",
+    "    response = requests.get(url, stream=True)\n",
+    "    response.raise_for_status()  # Raises an error for bad status codes\n",
+    "\n",
+    "    with open(output_path, 'wb') as f:\n",
+    "        for chunk in response.iter_content(chunk_size=8192):\n",
+    "            f.write(chunk)\n",
+    "\n",
+    "    zip_path = \"selection-true-positives.zip\"\n",
+    "    extract_dir = \"selection-true-positives\"  # Current directory\n",
+    "\n",
+    "    shutil.unpack_archive(zip_path, extract_dir, 'zip')\n",
+    "\n",
+    "    print(\"Extraction completed.\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Send detection continuoulsy\n",
+    "For a given CAMERA_ID, the following cell will continuously send 1 detection periodically (each IMG_FREQ_SECONDS) \n",
+    "\n",
+    "To stop the cell from running you can click on the \"stop\" button in the ribbon above the notebook.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "CAMERA_ID = 1\n",
+    "SEQUENCE_CENTER_AZIMUTH = 180\n",
+    "IMG_FREQ_SECONDS = 30\n",
+    "\n",
+    "\n",
+    "camera_token = get_camera_token(API_URL, CAMERA_ID, admin_access_token)\n",
+    "camera_client  = Client(camera_token, API_URL)\n",
+    "\n",
+    "seq_folder = \"selection-true-positives/2025-06-13T14-50-34_mostazal--2-180_sequence-1195\"\n",
+    "\n",
+    "imgs = glob.glob(f\"{seq_folder}/images/*\")\n",
+    "imgs.sort()\n",
+    "preds = glob.glob(f\"{seq_folder}/labels_predictions/*\")\n",
+    "preds.sort()\n",
+    "\n",
+    "while True:\n",
+    "    for img_file, pred_file in zip(imgs, preds):\n",
+    "        stream = io.BytesIO()\n",
+    "        im = Image.open(img_file)\n",
+    "        im.save(stream, format=\"JPEG\", quality=80)\n",
+    "\n",
+    "        bboxes = read_pred_file(pred_file)\n",
+    "\n",
+    "        response = camera_client.create_detection(stream.getvalue(), SEQUENCE_CENTER_AZIMUTH, bboxes)\n",
+    "        # Force a KeyError if the request failed\n",
+    "        response.json()[\"id\"]\n",
+    "        print(\"detection sent\")\n",
+    "        time.sleep(IMG_FREQ_SECONDS)\n",
+    "    "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.8.20"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}