{ "id": "sZRsdOerPYjPfRAJ", "meta": { "templateCredsSetupCompleted": true }, "name": "Railway Station Queue Predictor \u2014 Form + Smart Wait Time + ChatGPT AI Advisory + Gmail + Sheets", "tags": [], "nodes": [ { "id": "be16ddb5-255c-4d20-ac28-e8e73fb7f540", "name": "Overview", "type": "n8n-nodes-base.stickyNote", "position": [ -1600, -80 ], "parameters": { "color": 4, "width": 536, "height": 1372, "content": "## Railway Station Queue Predictor \u2014 Form + Smart Wait Time + ChatGPT AI Advisory + Gmail + Sheets\n\nFor Indian train travelers who want to know how early to reach the station and how to skip the worst queues. The traveler fills a short form with their train and station details. A built-in prediction algorithm (no external API) estimates crowd level, platform wait, ticket-counter queue, security time, and the ideal arrival time. A ChatGPT AI model then writes a friendly, plain-English advisory with station-specific tips. The traveler gets a colour-coded email alert, and every prediction is logged to Google Sheets.\n\n## What each node does\n- **1. Form \u2014 Traveler Train Details** collects train number, station, travel date and time, class, e-ticket status, and passenger count\n- **2. Code \u2014 Predict Queue Wait Times** runs the rule-based algorithm and returns crowd score, all wait times, alert level, and the recommended arrival time\n- **3. HTTP \u2014 AI Write Advisory** sends the prediction to a ChatGPT AI model and gets back a short traveler advisory\n- **4. Code \u2014 Parse Advisory and Alert Colors** merges the advisory and assigns the colour-coded alert level\n- **5. Code \u2014 Build HTML Email** builds the full colour-coded alert email\n- **6. Sheets \u2014 Log Prediction** appends the prediction to the log (parallel branch)\n- **7. Gmail \u2014 Send Queue Alert to Traveler** emails the alert to the traveler (parallel branch)\n\n## How the prediction works\nThe algorithm in node 2 scores expected crowding from day of week, time of day, festival season, station size, train type, and class of travel. Alert levels: GREEN (light), YELLOW (moderate), ORANGE (busy), RED (very crowded). It is a rule-based estimate, not live station data.\n\n## Google Sheet setup\nCreate a Google Sheet, add a tab named **Predictions**, and put these column headers in row 1:\nDate, Train Number, Train Name, Station, Travel Date, Departure Time, Class, Passengers, Has E-Ticket, Crowd Score, Alert Level, Platform Wait (min), Ticket Queue (min), Security Time (min), Total Buffer (min), Optimal Arrival, Traveler Email, Advisory Sent\n\n## Set up steps\n1. **OpenAI** \u2014 in **3. HTTP \u2014 AI Write Advisory**, connect your OpenAI API credential. A ChatGPT AI model is used for the advisory\n2. **Google Sheets** \u2014 in **6. Sheets \u2014 Log Prediction**, connect Google Sheets OAuth2 and replace `YOUR_QUEUE_LOG_SHEET_ID` with your sheet ID (from the sheet URL after /d/)\n3. **Gmail** \u2014 in **7. Gmail \u2014 Send Queue Alert to Traveler**, connect Gmail OAuth2. The recipient comes from the form\n4. Activate the workflow, open the Form URL, enter train details, and submit. The alert is emailed and logged instantly" }, "typeVersion": 1 }, { "id": "e29779ae-ac73-4a1e-bc32-496fb658e411", "name": "Section \u2014 Form and Prediction Algorithm", "type": "n8n-nodes-base.stickyNote", "position": [ -1008, 48 ], "parameters": { "color": 5, "width": 484, "height": 324, "content": "## Form and Prediction Algorithm\nTraveler fills train details. Code calculates crowd score, platform wait, ticket queue, security time, and the optimal arrival time \u2014 all without any external API." }, "typeVersion": 1 }, { "id": "2fba56e1-5ac8-4d3d-994b-60065f1c73f7", "name": "Section \u2014 AI Advisory and Alert Level", "type": "n8n-nodes-base.stickyNote", "position": [ -512, 48 ], "parameters": { "color": 6, "width": 452, "height": 372, "content": "## AI Advisory and Alert Level\nThe ChatGPT AI model writes a friendly traveler advisory with station tips. Code parses the response and assigns the colour-coded alert level." }, "typeVersion": 1 }, { "id": "2d161391-2d4f-4fa4-9962-63fc1151b407", "name": "Section \u2014 Build Email, Log, and Send", "type": "n8n-nodes-base.stickyNote", "position": [ 0, -144 ], "parameters": { "color": 4, "width": 660, "height": 628, "content": "## Build Email, Log, and Send\nCode builds the colour-coded HTML email. Two parallel branches run: Sheets logs the prediction, and Gmail sends the alert to the traveler." }, "typeVersion": 1 }, { "id": "0fb166ca-0a2d-4ba6-bd80-a53080bbfb2f", "name": "1. Form \u2014 Traveler Train Details", "type": "n8n-nodes-base.formTrigger", "position": [ -928, 192 ], "parameters": { "options": { "path": "railway-queue-predictor", "buttonLabel": "Predict My Queue Times", "appendAttribution": false }, "formTitle": "Railway Queue Predictor", "formFields": { "values": [ { "fieldLabel": "Your Name", "placeholder": "e.g. Rahul Kumar", "requiredField": true }, { "fieldLabel": "Your Email", "placeholder": "your@email.com \u2014 advisory will be sent here", "requiredField": true }, { "fieldLabel": "Train Number", "placeholder": "e.g. 12301 or 22691", "requiredField": true }, { "fieldLabel": "Train Name", "placeholder": "e.g. Rajdhani Express, Shatabdi, Duronto, Express", "requiredField": true }, { "fieldLabel": "Departure Station Code", "placeholder": "e.g. NDLS, CSMT, HWH, MAS, SBC, ADI, PUNE, LKO", "requiredField": true }, { "fieldLabel": "Travel Date", "placeholder": "YYYY-MM-DD e.g. 2025-07-15", "requiredField": true }, { "fieldLabel": "Train Departure Time", "placeholder": "HH:MM in 24hr format e.g. 06:30 or 17:45", "requiredField": true }, { "fieldType": "dropdown", "fieldLabel": "Class of Travel", "fieldOptions": { "values": [ { "option": "SL \u2014 Sleeper Class" }, { "option": "3A \u2014 AC 3 Tier" }, { "option": "2A \u2014 AC 2 Tier" }, { "option": "1A \u2014 AC First Class" }, { "option": "CC \u2014 Chair Car" }, { "option": "2S \u2014 Second Sitting" } ] }, "requiredField": true }, { "fieldType": "dropdown", "fieldLabel": "Do you have IRCTC e-ticket on app?", "fieldOptions": { "values": [ { "option": "Yes \u2014 I have digital ticket on IRCTC app" }, { "option": "No \u2014 I need to collect physical ticket or PRS printout" } ] }, "requiredField": true }, { "fieldLabel": "Number of Passengers", "placeholder": "e.g. 1, 2, 4", "requiredField": true } ] }, "formDescription": "Enter your train details to get a predicted crowd and wait time report for your departure station. You will receive a personalized advisory email with tips to avoid queues." }, "typeVersion": 2.2 }, { "id": "ed593746-0cf1-47df-8bcb-f46871f38d3f", "name": "2. Code \u2014 Predict Queue Wait Times", "type": "n8n-nodes-base.code", "position": [ -688, 192 ], "parameters": { "jsCode": "// RAILWAY STATION QUEUE PREDICTION ALGORITHM\n// Predicts crowd levels and wait times based on multiple factors\n// No external API needed \u2014 rule-based scoring system\n\nconst row = $json;\n\n// --- Extract form inputs ---\nconst travelerName = (row['Your Name'] || '').trim();\nconst email = (row['Your Email'] || '').trim();\nconst trainNo = (row['Train Number'] || '').trim();\nconst trainName = (row['Train Name'] || '').trim();\nconst stationCode = (row['Departure Station Code'] || '').trim().toUpperCase();\nconst travelDate = (row['Travel Date'] || '').trim();\nconst departureTime = (row['Train Departure Time'] || '').trim();\nconst travelClass = (row['Class of Travel'] || '').trim();\nconst hasETicket = (row['Do you have IRCTC e-ticket on app?'] || '').startsWith('Yes');\nconst passengers = parseInt(row['Number of Passengers']) || 1;\n\nif (!email || !trainNo || !stationCode || !travelDate || !departureTime) {\n throw new Error('Train number, station code, travel date, departure time, and email are all required.');\n}\n\n// --- Parse travel date and time ---\nconst travelDateObj = new Date(travelDate);\nconst dayOfWeek = travelDateObj.getDay(); // 0=Sun, 6=Sat\nconst month = travelDateObj.getMonth() + 1; // 1-12\nconst [depHour, depMin] = departureTime.split(':').map(Number);\nconst depMinutes = (depHour * 60) + (depMin || 0);\n\n// --- FACTOR 1: Day of week multiplier ---\nconst dayMultiplier =\n dayOfWeek === 0 ? 1.35 :\n dayOfWeek === 1 ? 1.25 :\n dayOfWeek === 5 ? 1.20 :\n dayOfWeek === 6 ? 1.30 :\n 1.0;\n\n// --- FACTOR 2: Time of day multiplier ---\nconst timeMultiplier =\n (depMinutes >= 300 && depMinutes < 540) ? 1.35 :\n (depMinutes >= 960 && depMinutes < 1260) ? 1.30 :\n (depMinutes >= 1260 || depMinutes < 300) ? 1.15 :\n 1.0;\n\n// --- FACTOR 3: Season/festival multiplier ---\nconst seasonMultiplier =\n (month === 10 || month === 11) ? 1.40 :\n (month === 12 || month === 1) ? 1.25 :\n (month === 5 || month === 6) ? 1.30 :\n month === 3 ? 1.20 :\n 1.0;\n\n// --- FACTOR 4: Station size multiplier ---\nconst stationMultipliers = {\n 'NDLS': 1.50, 'DLI': 1.40, 'CSMT': 1.45, 'BCT': 1.35,\n 'HWH': 1.40, 'SDAH': 1.25, 'MAS': 1.35, 'SBC': 1.30,\n 'ADI': 1.30, 'PUNE': 1.25, 'LKO': 1.30, 'PNBE': 1.35,\n 'JP': 1.25, 'HYB': 1.30, 'SC': 1.25\n};\nconst stationMult = stationMultipliers[stationCode] || 1.15;\n\n// --- FACTOR 5: Train type multiplier ---\nconst trainNameLower = trainName.toLowerCase();\nconst trainMultiplier =\n (trainNameLower.includes('rajdhani') || trainNameLower.includes('shatabdi') || trainNameLower.includes('tejas') || trainNameLower.includes('vande')) ? 0.75 :\n (trainNameLower.includes('duronto') || trainNameLower.includes('gatimaan')) ? 0.80 :\n (trainNameLower.includes('superfast') || trainNameLower.includes('sf')) ? 1.05 :\n (trainNameLower.includes('express')) ? 1.10 :\n 1.20;\n\n// --- FACTOR 6: Class multiplier ---\nconst classCode = travelClass.split('\u2014')[0].trim();\nconst classMultiplier =\n classCode === 'SL' ? 1.40 :\n classCode === '2S' ? 1.30 :\n classCode === 'CC' ? 1.10 :\n classCode === '3A' ? 0.90 :\n classCode === '2A' ? 0.80 :\n classCode === '1A' ? 0.70 :\n 1.0;\n\n// --- COMBINED CROWD SCORE ---\nconst baseCrowdScore = 50;\nconst rawScore = baseCrowdScore * dayMultiplier * timeMultiplier * seasonMultiplier * stationMult * trainMultiplier * classMultiplier;\nconst crowdScore = Math.min(Math.round(rawScore), 100);\n\n// --- WAIT TIME CALCULATIONS (in minutes) ---\nconst platformWait = Math.round((crowdScore / 100) * 25 + 5);\nconst ticketQueue = hasETicket ? 0 : Math.round((crowdScore / 100) * 35 + 5);\nconst hasSecurityCheck = ['NDLS', 'DLI', 'CSMT', 'HWH', 'MAS', 'SBC'].includes(stationCode);\nconst securityTime = hasSecurityCheck ? Math.round((crowdScore / 100) * 20 + 5) : 0;\nconst platformWalk = stationMult > 1.35 ? 12 : stationMult > 1.25 ? 8 : 5;\nconst totalBuffer = platformWait + ticketQueue + securityTime + platformWalk + (passengers > 3 ? 10 : 0);\n\n// --- Optimal arrival time ---\nconst optimalArrivalMinutes = depMinutes - totalBuffer;\nconst optHour = Math.floor(((optimalArrivalMinutes % 1440) + 1440) % 1440 / 60);\nconst optMin = Math.floor(((optimalArrivalMinutes % 1440) + 1440) % 1440 % 60);\nconst optimalArrival = String(optHour).padStart(2,'0') + ':' + String(optMin).padStart(2,'0');\n\n// --- ALERT LEVEL ---\nconst alertLevel =\n crowdScore >= 80 ? 'RED' :\n crowdScore >= 60 ? 'ORANGE' :\n crowdScore >= 40 ? 'YELLOW' :\n 'GREEN';\n\n// --- BUILD CONTEXT FOR AI ---\nconst predictionContext = [\n 'Traveler: ' + travelerName,\n 'Train: ' + trainNo + ' ' + trainName,\n 'Station: ' + stationCode,\n 'Travel Date: ' + travelDate,\n 'Day of Week: ' + ['Sunday','Monday','Tuesday','Wednesday','Thursday','Friday','Saturday'][dayOfWeek],\n 'Departure Time: ' + departureTime,\n 'Class: ' + travelClass,\n 'Passengers: ' + passengers,\n 'Has e-Ticket: ' + (hasETicket ? 'Yes' : 'No'),\n '',\n 'PREDICTION RESULTS:',\n 'Crowd Score: ' + crowdScore + '/100',\n 'Alert Level: ' + alertLevel,\n 'Platform Wait: ' + platformWait + ' min',\n 'Ticket Counter Queue: ' + (hasETicket ? 'Skipped (e-ticket)' : ticketQueue + ' min'),\n 'Security Check: ' + (hasSecurityCheck ? securityTime + ' min' : 'Not required at this station'),\n 'Platform Walk: ' + platformWalk + ' min',\n 'Total Buffer Needed: ' + totalBuffer + ' minutes',\n 'Recommended Arrival: ' + optimalArrival + ' (arrive by this time)',\n '',\n 'Factors driving this prediction:',\n 'Day multiplier: ' + dayMultiplier + 'x (' + ['Sun','Mon','Tue','Wed','Thu','Fri','Sat'][dayOfWeek] + ')',\n 'Time of day: ' + timeMultiplier + 'x (departure at ' + departureTime + ')',\n 'Season: ' + seasonMultiplier + 'x (month ' + month + ')',\n 'Station size: ' + stationMult + 'x (' + stationCode + ')',\n 'Train type: ' + trainMultiplier + 'x (' + trainName + ')',\n 'Class: ' + classMultiplier + 'x (' + classCode + ')'\n].join('\\n');\n\nconst loggedAt = new Date().toISOString();\n\nreturn [{\n json: {\n travelerName, email, trainNo, trainName, stationCode,\n travelDate, departureTime, travelClass, classCode,\n hasETicket, passengers, dayOfWeek,\n crowdScore, alertLevel,\n platformWait, ticketQueue, securityTime,\n platformWalk, totalBuffer, optimalArrival,\n hasSecurityCheck,\n predictionContext,\n loggedAt\n }\n}];" }, "typeVersion": 2 }, { "id": "9d90dfa5-5125-4296-91c5-5ebec9534f39", "name": "3. HTTP \u2014 AI Write Advisory", "type": "n8n-nodes-base.httpRequest", "position": [ -448, 192 ], "parameters": { "url": "https://api.openai.com/v1/chat/completions", "method": "POST", "options": { "timeout": 30000, "response": { "response": { "responseFormat": "json" } } }, "jsonBody": "={\n \"model\": \"gpt-4o-mini\",\n \"temperature\": 0.5,\n \"max_tokens\": 800,\n \"messages\": [\n {\n \"role\": \"system\",\n \"content\": \"You are a helpful railway travel assistant for Indian train travelers. Write a friendly, practical travel advisory in simple English. Be specific, actionable, and conversational. Do not use markdown formatting \u2014 plain text paragraphs only.\"\n },\n {\n \"role\": \"user\",\n \"content\": {{ JSON.stringify(\n \"Write a short traveler advisory based on this queue prediction.\\n\\n\" + $json.predictionContext +\n \"\\n\\nInclude these points in your advisory (use plain text, no markdown, no bullets, no headers):\\n\" +\n \"1. One opening sentence mentioning their train and the crowd level prediction.\\n\" +\n \"2. A specific recommendation on what time to arrive and why.\\n\" +\n \"3. One practical tip for their class of travel (\" + $json.classCode + \") at \" + $json.stationCode + \" station to save time.\\n\" +\n \"4. One tip about the ticket counter situation based on whether they have an e-ticket or not.\\n\" +\n \"5. One general safety or comfort tip for travelling with \" + $json.passengers + \" passengers.\\n\" +\n \"Keep the entire advisory under 120 words. Be warm and helpful.\"\n ) }}\"\n }\n ]\n}", "sendBody": true, "sendHeaders": true, "specifyBody": "json", "authentication": "predefinedCredentialType", "headerParameters": { "parameters": [ { "name": "Content-Type", "value": "application/json" } ] }, "nodeCredentialType": "openAiApi" }, "typeVersion": 4.2 }, { "id": "c10c5399-6ff7-4deb-9141-7593eefacb2a", "name": "4. Code \u2014 Parse Advisory and Alert Colors", "type": "n8n-nodes-base.code", "position": [ -208, 192 ], "parameters": { "jsCode": "// Extract AI advisory text and merge with prediction data\nconst resp = $input.first().json;\nconst prediction = $('2. Code \u2014 Predict Queue Wait Times').first().json;\n\nconst advisory = resp?.choices?.[0]?.message?.content || 'Please arrive at least ' + prediction.totalBuffer + ' minutes before your train departure. Check the station board for your platform number.';\n\n// Alert level colors for email\nconst alertColor =\n prediction.alertLevel === 'RED' ? '#e74c3c' :\n prediction.alertLevel === 'ORANGE' ? '#e67e22' :\n prediction.alertLevel === 'YELLOW' ? '#f39c12' :\n '#27ae60';\n\nconst alertBg =\n prediction.alertLevel === 'RED' ? '#fdf0f0' :\n prediction.alertLevel === 'ORANGE' ? '#fdf5ec' :\n prediction.alertLevel === 'YELLOW' ? '#fefde7' :\n '#f0fdf4';\n\nconst alertText =\n prediction.alertLevel === 'RED' ? 'Very Crowded \u2014 Arrive 90+ minutes early' :\n prediction.alertLevel === 'ORANGE' ? 'Busy Station \u2014 Arrive 60-90 minutes early' :\n prediction.alertLevel === 'YELLOW' ? 'Moderate Crowd \u2014 Arrive 45-60 minutes early' :\n 'Light Crowd \u2014 Arrive 30 minutes early is sufficient';\n\nreturn [{\n json: {\n ...prediction,\n advisory: advisory.trim(),\n alertColor,\n alertBg,\n alertText\n }\n}];" }, "typeVersion": 2 }, { "id": "8185aa7b-1c5a-4e1c-9db0-4a0ee7bd73bc", "name": "5. Code \u2014 Build HTML Email", "type": "n8n-nodes-base.code", "position": [ 48, 192 ], "parameters": { "jsCode": "// Build the complete HTML email for the traveler\nconst d = $input.first().json;\n\nconst fmtMin = (m) => m === 0 ? 'Skipped' : m + ' min';\n\nconst htmlEmail =\n ''\n + ''\n\n + '
'\n + '

Railway Queue Predictor

'\n + '

' + d.travelerName + ' \u2014 Train ' + d.trainNo + ' ' + d.trainName + '

'\n + '
'\n\n + '
'\n + '
' + d.alertLevel + ' \u2014 ' + d.alertText + '
'\n + '
Crowd Score: ' + d.crowdScore + '/100
'\n + '
'\n\n + '
'\n + '' + d.travelDate + ''\n + '' + d.stationCode + ''\n + 'Departs ' + d.departureTime + ''\n + '' + d.classCode + ''\n + '' + d.passengers + ' passenger(s)'\n + '
'\n\n + '
'\n\n + '
'\n + '
Recommended Arrival Time
'\n + '
' + d.optimalArrival + '
'\n + '
Arrive by this time \u2014 total buffer needed: ' + d.totalBuffer + ' minutes
'\n + '
'\n\n + '

Queue Time Breakdown

'\n + ''\n + ''\n + ''\n + ''\n + ''\n + ''\n + ''\n + '
Queue TypePredicted WaitStatus
Platform Walk' + d.platformWalk + ' minAlways required
Security Check' + fmtMin(d.securityTime) + '' + (d.hasSecurityCheck ? 'Required at ' + d.stationCode : 'Not required') + '
Ticket Counter' + fmtMin(d.ticketQueue) + '' + (d.hasETicket ? 'E-ticket \u2014 skip queue' : 'Physical ticket needed') + '
Platform Wait' + d.platformWait + ' minFind seat, settle luggage
Total Buffer' + d.totalBuffer + ' min' + d.alertLevel + '
'\n\n + '
'\n + '

Travel Advisory

'\n + '

' + d.advisory + '

'\n + '
'\n\n + '
'\n + '

Quick Tips

'\n + '

- Keep your ticket and ID ready before entering the station

'\n + '

- Check the NTES app for real-time train location and platform number

'\n + '

- Platform number is usually announced 20-30 minutes before departure

'\n + (d.hasETicket ? '

- You have an e-ticket \u2014 go straight to your platform and skip the counter

' : '

- You need a physical ticket \u2014 reach early to avoid the counter queue

')\n + '
'\n\n + '
'\n\n + '
'\n + '

Railway Queue Predictor \u2014 n8n + ChatGPT AI

'\n + '

Prediction based on general patterns. Always allow extra time for unexpected delays.

'\n + '
'\n + '';\n\nreturn [{\n json: {\n ...d,\n htmlEmail,\n emailSubject: d.alertLevel + ' Queue Alert \u2014 Train ' + d.trainNo + ' | Arrive by ' + d.optimalArrival + ' | ' + d.stationCode\n }\n}];" }, "typeVersion": 2 }, { "id": "bc2d4ac8-8376-466d-b475-b174fad1e24d", "name": "6. Sheets \u2014 Log Prediction", "type": "n8n-nodes-base.googleSheets", "position": [ 288, 32 ], "parameters": { "columns": { "value": { "Date": "={{ $json.loggedAt.split('T')[0] }}", "Class": "={{ $json.classCode }}", "Station": "={{ $json.stationCode }}", "Passengers": "={{ $json.passengers }}", "Train Name": "={{ $json.trainName }}", "Alert Level": "={{ $json.alertLevel }}", "Crowd Score": "={{ $json.crowdScore }}", "Travel Date": "={{ $json.travelDate }}", "Has E-Ticket": "={{ $json.hasETicket ? 'Yes' : 'No' }}", "Train Number": "={{ $json.trainNo }}", "Advisory Sent": "Yes", "Departure Time": "={{ $json.departureTime }}", "Traveler Email": "={{ $json.email }}", "Optimal Arrival": "={{ $json.optimalArrival }}", "Ticket Queue (min)": "={{ $json.ticketQueue }}", "Total Buffer (min)": "={{ $json.totalBuffer }}", "Platform Wait (min)": "={{ $json.platformWait }}", "Security Time (min)": "={{ $json.securityTime }}" }, "schema": [ { "id": "Date", "type": "string", "display": true, "required": false, "displayName": "Date", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Train Number", "type": "string", "display": true, "required": false, "displayName": "Train Number", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Train Name", "type": "string", "display": true, "required": false, "displayName": "Train Name", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Station", "type": "string", "display": true, "required": false, "displayName": "Station", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Travel Date", "type": "string", "display": true, "required": false, "displayName": "Travel Date", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Departure Time", "type": "string", "display": true, "required": false, "displayName": "Departure Time", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Class", "type": "string", "display": true, "required": false, "displayName": "Class", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Passengers", "type": "string", "display": true, "required": false, "displayName": "Passengers", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Has E-Ticket", "type": "string", "display": true, "required": false, "displayName": "Has E-Ticket", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Crowd Score", "type": "string", "display": true, "required": false, "displayName": "Crowd Score", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Alert Level", "type": "string", "display": true, "required": false, "displayName": "Alert Level", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Platform Wait (min)", "type": "string", "display": true, "required": false, "displayName": "Platform Wait (min)", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Ticket Queue (min)", "type": "string", "display": true, "required": false, "displayName": "Ticket Queue (min)", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Security Time (min)", "type": "string", "display": true, "required": false, "displayName": "Security Time (min)", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Total Buffer (min)", "type": "string", "display": true, "required": false, "displayName": "Total Buffer (min)", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Optimal Arrival", "type": "string", "display": true, "required": false, "displayName": "Optimal Arrival", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Traveler Email", "type": "string", "display": true, "required": false, "displayName": "Traveler Email", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Advisory Sent", "type": "string", "display": true, "required": false, "displayName": "Advisory Sent", "defaultMatch": false, "canBeUsedToMatch": true } ], "mappingMode": "defineBelow", "matchingColumns": [], "attemptToConvertTypes": false, "convertFieldsToString": true }, "options": {}, "operation": "append", "sheetName": { "__rl": true, "mode": "name", "value": "Predictions" }, "documentId": { "__rl": true, "mode": "id", "value": "YOUR_QUEUE_LOG_SHEET_ID" } }, "typeVersion": 4.5 }, { "id": "5c57ee84-93ca-4eb1-81e8-bec30f82408d", "name": "7. Gmail \u2014 Send Queue Alert to Traveler", "type": "n8n-nodes-base.gmail", "position": [ 288, 224 ], "parameters": { "sendTo": "={{ $json.email }}", "message": "={{ $json.htmlEmail }}", "options": { "senderName": "Railway Queue Predictor" }, "subject": "={{ $json.emailSubject }}" }, "typeVersion": 2.1 } ], "active": false, "settings": { "binaryMode": "separate", "executionOrder": "v1" }, "versionId": "495ddbc1-3420-4ce4-972f-c4f44c63a72f", "nodeGroups": [], "connections": { "5. Code \u2014 Build HTML Email": { "main": [ [ { "node": "6. Sheets \u2014 Log Prediction", "type": "main", "index": 0 }, { "node": "7. Gmail \u2014 Send Queue Alert to Traveler", "type": "main", "index": 0 } ] ] }, "3. HTTP \u2014 AI Write Advisory": { "main": [ [ { "node": "4. Code \u2014 Parse Advisory and Alert Colors", "type": "main", "index": 0 } ] ] }, "1. Form \u2014 Traveler Train Details": { "main": [ [ { "node": "2. Code \u2014 Predict Queue Wait Times", "type": "main", "index": 0 } ] ] }, "2. Code \u2014 Predict Queue Wait Times": { "main": [ [ { "node": "3. HTTP \u2014 AI Write Advisory", "type": "main", "index": 0 } ] ] }, "4. Code \u2014 Parse Advisory and Alert Colors": { "main": [ [ { "node": "5. Code \u2014 Build HTML Email", "type": "main", "index": 0 } ] ] } } }