Edge AI-Powered Food Calorie Estimation for Real-Time Dietary Assessment on Raspberry Pi

Project Code :TEMBMA3785

Objective

The objective is to develop an edge AI system on Raspberry Pi that estimates food calories in real time, enabling effective diet tracking and healthier lifestyle management.

Abstract

This work presents an Edge AI-powered food calorie estimation system for real-time dietary assessment using Raspberry Pi. The system employs a USB web camera integrated with a YOLO-based deep learning model to identify food items, while a load cell connected to Arduino measures the weight of the food. By combining food recognition and weight measurement, the system estimates calorie content and nutritional values accurately. The Raspberry Pi performs on-device inference, enabling offline operation without depending on cloud services. A buzzer provides alerts when calorie intake surpasses predefined thresholds, thereby supporting personalized health monitoring. Designed to be cost-effective, portable, and intelligent, this system is highly beneficial for health-conscious individuals, dieticians, and clinical nutrition management by providing real-time food analysis and dietary guidance at the edge.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

Hardware components:

  • Raspberry pi
  • Arduino UNO
  • Load Cell
  • Buzzer
  • LCD

Software requirements:

  • Raspbian OS
  • Python IDLE
  • Embedded C
  • Arduino IDE

Learning Outcomes

  • Raspberry pi pin diagram and architecture
  • How to install Raspberrypi / setup software
  • Setting up and installation procedure for Raspberrypi
  • Introduction to Raspberrypi environment / development setup
  • Basic programming in Raspberrypi (Python)
  • Basics of Embedded programming using Raspberrypi
  • Basics of IoT platforms
  • Working of power supply
  • About Project Development Life Cycle:
    • Planning and Requirement Gathering (software, tools, hardware components, etc.)
    • Schematic preparation
    • Code development and debugging
    • Hardware development and debugging
    • Development of the project and output testing
  • Practical exposure to:
    • Hardware and software tools
    • Solution providing for real-time problems
    • Working with team/individual
    • Work on creative ideas
  • Skills developed:
    • Project development skills
    • Problem analyzing skills
    • Problem solving skills
    • Creativity and imaginative skills
    • Programming skills
    • Deployment
    • Testing skills
    • Debugging skills
    • Project presentation skills
    • Thesis writing skills


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