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Technical Documentation – Intelligent Restaurant Management System (SIMR)

Problem Description

In the HoReCa industry, processes related to order management, ingredients, staff, and customer interaction are still mostly done manually, leading to:

  • Delays in processing and delivering orders
  • Human errors in stock calculation and recipes
  • Lack of transparency in monitoring consumption and profitability
  • Additional costs due to food waste and chaotic supply management
  • Poor customer experience caused by long waiting times and lack of digitalization

These issues affect profitability, customer satisfaction, and overall service quality.


Proposed Solution

SIMR is a hybrid software-hardware platform that automates and optimizes restaurant workflows:

  • Fully digitalizes stock, order, and staff management
  • Uses IoT and sensors for real-time monitoring of storage conditions
  • Integrates AI for marketing recommendations and predictive analytics
  • Includes an automated drive-thru system with a client interface
  • Cloud-based communication and storage (Firebase) for scalability and real-time updates

Target Audience

  • Small and medium-sized restaurants needing fast, low-cost digitalization
  • Restaurant chains requiring centralized control across locations
  • Managers and chefs seeking to optimize costs and workflow
  • Customers wanting fast, digitalized ordering (table or drive-thru)

Market Analysis & Differentiators

Current solutions (Glovo, Tazz, Square POS) cover only limited aspects of restaurant operations. SIMR stands out through:

  • Fully automated ingredient and menu management
  • Hardware–software–integrated physical drive-thru
  • AI-based smart restocking predictions
  • Automatic supplier ordering based on stock
  • IoT for food safety (temperature, humidity, weight)

Detailed Functionalities

Admin App (MAUI – Windows & Android)

  • Ingredient management: add, edit, delete, track quantities and units

  • Critical stock alerts

  • Menu and recipe viewer: ingredient composition and required amounts

  • Statistics, visual reports, and AI analytics

    • Ingredient consumption forecasting
    • Product popularity analysis
    • Smart supply suggestions
    • Profitability per product
  • Employee management: roles, accounts, time tracking

  • AI-based restocking recommendations


Client App (Kotlin – Android)

  • Real-time menu synced with stock levels
  • Fast order placement with customization options
  • Table service or drive-thru choice
  • Real-time order status notifications
  • Customer loyalty system (cards, coupons, Happy Hour discounts)

IoT System – Monitoring & Automation

Arduino Nano ESP32

  • Pressure sensors → ingredient weight
  • DHT11 → temperature & humidity
  • Automatic fans triggered by critical conditions
  • Real-time Firebase communication

Arduino UNO + Raspberry Pi 5

  • Motion sensor → detect vehicles at drive-thru
  • LED traffic light at the drive-thru window
  • LED display with dynamic messages
  • Touchscreen interface for placing client orders

Security Implemented

  • Firebase Auth (email + password) with role management
  • Strict Firebase rules: read/write only on the owner’s UID
  • Input validation in all applications
  • Encrypted communication with Firebase

Technologies Used

Component Technology
Admin App .NET MAUI + CommunityToolkit.Mvvm
Client App Kotlin + Jetpack Compose
Backend Firebase Realtime Database + Firebase Auth
AI Gemini AI
Email SendGrid / Java Mail
Statistics Microcharts + LiveCharts
Sensors Arduino Nano ESP32 + DHT11 + pressure sensor + Peltier module + methane sensor
Drive-thru Arduino UNO + motion sensor + LED traffic light + LED Display + Raspberry Pi 5 + HDMI Display

Roadmap

  1. Phase 1: Market research
  2. Phase 2: Management app development
  3. Phase 3: Client app development
  4. Phase 4: Hardware system integration

Authors’ Opinion

We believe SIMR significantly contributes to efficient resource management in restaurants. By integrating modern technologies, it reduces food waste, enhances customer experience, and increases operational efficiency.


External Resources

  • Firebase SDK
  • Gemini AI SDK
  • SendGrid API
  • Java Mail
  • Arduino libraries (DHT11, Firebase ESP32)
  • MAUI CommunityToolkit

Annex 1 – Application Installation & User Guides


Annex 2 – System Architecture

System Architecture


Annex 3 – Physical Mockup Diagram

Mockup


Annex 4 – Firebase Realtime Database Security Rules

{
  "rules": {
    ".read": "auth != null",
    ".write": "auth != null",
    "kitchen": {
      "$ownerId": {
        ".read": "auth != null && (auth.uid === $ownerId || root.child('users').child(auth.uid).child('Owner').val() === $ownerId)",
        ".write": "auth != null && (auth.uid === $ownerId || root.child('users').child(auth.uid).child('Owner').val() === $ownerId)"
      }
    },
    "users": {
      "$userId": {
        ".read": "auth != null && (auth.uid === $userId || root.child('users').child(auth.uid).child('Owner').val() === root.child('users').child($userId).child('Owner').val() || (root.child('users').child(auth.uid).child('Type').val() === 'owner' && root.child('users').child($userId).child('Owner').val() === auth.uid))",
        ".write": "auth != null && (auth.uid === $userId || (root.child('users').child(auth.uid).child('Type').val() === 'owner' && root.child('users').child($userId).child('Owner').val() === auth.uid))"
      }
    }
  }
}

Annex 5 – Arduino Nano ESP32 Diagram

Arduino Nano ESP32


Annex 6 – Arduino UNO Diagram

Arduino UNO


Annex 7 – Raspberry Pi 5 Diagram

Raspberry Pi 5


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