Ai fitness coach Strava data analysis and personalized training insights
Detailed Title "Triathlon Coach AI Workflow: Strava Data Analysis and Personalized Training Insights using n8n" --- Description This n8n workflow enables you to build an AI-driven virtual triathlon coach that seamlessly integrates with Strava to analyze activity data and provide athletes with actionable training insights. The workflow processes data from activities like swimming, cycling, and running, delivers personalized feedback, and sends motivational and performance improvement advice via email or WhatsApp. --- Workflow Details Trigger: Strava Activity Updates Node: Strava Trigger Purpose: Captures updates from Strava whenever an activity is recorded or modified. The data includes metrics like distance, pace, elevation, heart rate, and more. Integration: Uses Strava API for real-time synchronization. Step 1: Data Preprocessing Node: Code Purpose: Combines and flattens the raw Strava activity data into a structured format for easier processing in subsequent nodes. Logic: A recursive function flattens JSON input to create a clean and readable structure. Step 2: AI Analysis with Google Gemini Node: Google Gemini Chat Model Purpose: Leverages Google Gemini's advanced language model to analyze the activity data. Functionality: Identifies key performance metrics. Provides feedback and insights specific to the type of activity (e.g., running, swimming, or cycling). Offers tailored recommendations and motivational advice. Step 3: Generate Structured Output Node: Structure Output Purpose: Processes the AI-generated response to create a structured format, such as headings, paragraphs, and bullet lists. Output: Formats the response for clear communication. Step 4: Convert to HTML Node: Convert to HTML Purpose: Converts the structured output into an HTML format suitable for email or other presentation methods. Output: Ensures the response is visually appealing and easy to understand. Step 5: Send Email with Training Insights Node: Send Email Purpose: Sends a detailed email to the athlete with performance insights, training recommendations, and motivational messages. Integration: Utilizes Gmail or SMTP for secure and efficient email delivery. Optional Step: WhatsApp Notifications Node: WhatsApp Business Cloud Purpose: Sends a summary of the activity analysis and key recommendations via WhatsApp for instant access. Integration: Connects to WhatsApp Business Cloud for automated messaging. --- Additional Notes Customization: You can modify the AI prompt to adapt the recommendations to the athlete's specific goals or fitness levels. The workflow is flexible and can accommodate additional nodes for more advanced analysis or output formats. Scalability: Ideal for individual athletes or coaches managing multiple athletes. Can be expanded to include additional metrics or insights based on user preferences. Performance Metrics Handled: Swimming: SWOLF, stroke count, pace. Cycling: Cadence, power zones, elevation. Running: Pacing, stride length, heart rate zones. --- Implementation Steps Set Up Strava API Key: Log in to Strava Developers to generate your API key. Integrate the API key into the Strava Trigger node. Configure Google Gemini Integration: Use your Google Gemini (PaLM) API credentials in the Google Gemini Chat Model node. Customize Email and WhatsApp Messaging: Update the Send Email and WhatsApp Business Cloud nodes with the recipient’s details. Automate Execution: Deploy the workflow and use n8n's scheduling features or cron jobs for periodic execution. --- GET n8n Now N8N COURSE n8n Book Developer Notes Author: Amjid Ali improvements. Resources: See in Action: Syncbricks Youtube PayPal: Support the Developer Courses : SyncBricks LMS By using this workflow, triathletes and coaches can elevate training to the next level with AI-powered insights and actionable recommendations.
By Amjid AliConvert meeting recordings to notes & action items with AssemblyAI, GPT-4 & Sheets
This workflow automates the process of turning meeting recordings into structured notes and actionable tasks using AssemblyAI and Google Sheets. It is ideal for teams who want to save time on manual note-taking and ensure that action items from meetings are never missed. What it does Receives a meeting recording (audio file) via webhook Transcribes the audio using AssemblyAI Uses AI to generate structured meeting notes and extract action items (tasks) Logs meeting details and action items to a Google Sheet for easy tracking Use cases Automatically document meetings and share notes with your team Track action items and responsibilities from every meeting Centralize meeting outcomes and tasks in Google Sheets --- Quick Setup AssemblyAI API Key: Sign up at AssemblyAI and get your API key. Google Sheets Credentials: Set up a Google Service Account and share your target Google Sheet with the service account email. OpenAI API Key (optional, if using OpenAI for notes extraction): Get your API key from OpenAI. Configure the following essential nodes: Recording Ready Webhook: Set the webhook URL in your meeting platform to trigger the workflow when a recording is ready. Workflow Configuration: Enter your AssemblyAI API key, default due date, and admin email. AssemblyAI Transcription: Add your AssemblyAI API key in the credentials. Generate Meeting Notes & Extract Action Items: Add your OpenAI API key if required. Log Meeting to Sheets: Enter your Google Sheets document ID and sheet name. --- How to Use AssemblyAI in this Workflow The workflow sends the meeting audio file to AssemblyAI via the AssemblyAI Transcription node. AssemblyAI processes the audio and returns a full transcript. The transcript is then used by AI nodes to generate meeting notes and extract action items. --- Requirements AssemblyAI API key Google Service Account credentials (Optional) OpenAI API key for advanced note and action item extraction --- Start the workflow by sending a meeting recording to the webhook URL. The rest is fully automated!
By Țugui Dragoș