Predict Restaurant Food Waste with Gemini AI and Google Sheets Reporting

Description

This automated n8n workflow performs daily forecasting of sales and raw material needs for a restaurant. By analyzing historical data and predicting future usage with AI, businesses can minimize food waste, optimize inventory, and improve operational efficiency. The forecast is stored in Google Sheets and sent via email for easy review by staff and management.

What is AI Forecast Generator?
The AI Forecast Generator is a machine learning component that analyzes historical sales data, weather patterns, and seasonal trends to predict future food demand and recommend optimal inventory levels to minimize waste.

Good to Know
AI forecasting accuracy improves over time with more historical data
Weather and seasonal factors significantly impact food demand predictions
Google Sheets access must be properly authorized to avoid data sync issues
Email notifications help ensure timely review of daily forecasts
The system works with two main data sources: historical food wastage data and predicted low-waste food requirements

How It Works
Daily Trigger - Initiates the workflow every day to perform food waste prediction
Fetch Historical Sales Data - Reads past food usage & sales data from Google Sheets to understand trends
Format Data for AI Forecasting - Cleans and organizes raw data into a structured format for AI processing
AI Forecast Generator - Uses Gemini AI to forecast food demand and recommend waste reduction strategies
Clean & Structure AI Output - Parses AI response into structured and actionable format for reporting
Log Forecast to Google Sheets - Stores AI-generated forecast back into Google Sheets for historical tracking
Create Email Summary - Creates a concise, human-friendly summary of the forecast findings
Send Email Forecast Report - Delivers the forecast report via email to decision makers and management

Data Sources
The workflow utilizes two Google Sheets:

Food Wastage Data Sheet - Contains historical data with columns:
Date (date)
Food Item (text)
Quantity Wasted (number)
Cost Impact (currency)
Category (text)
Reason for Waste (text)

Predicted Food Data Sheet - Contains AI predictions with columns:
Date (date)
Food Item (text)
Predicted Demand (number)
Recommended Order Quantity (number)
Waste Risk Level (text)
Optimization Notes (text)

How to Use
Import the workflow into n8n
Configure Google Sheets API access and authorize the application
Set up email credentials for forecast report delivery
Create the two required Google Sheets with the specified column structures
Configure the AI model credentials (Gemini API key)
Test with sample historical data to verify predictions and email delivery
Adjust forecasting parameters based on your restaurant's specific needs
Monitor and refine the system based on actual vs. predicted results

Requirements
Google Sheets API access
Email service credentials (Gmail, SMTP, etc.)
AI model API credentials (Gemini AI)
Historical food wastage data for initial training

Customizing This Workflow
Modify the AI Forecast Generator prompts to focus on specific food categories, seasonal adjustments, or local market conditions. Adjust the email summary format to match your restaurant's reporting preferences and add additional data sources like supplier information or menu planning data.