Identification Of Artificially Ripened Fruits Using Smart Phones

Also Available Domains Raspberry pi|Embedded with Matlab

Project Code :TEMBMA41

Abstract

Health is one the most vital aspects that is of greater concern to most of the human beings at present days. To keep people healthier they intake a lot of fruits which contains more amount of nutrition and helps them to remain fit. Health benefits are provided with the intake of fruits and people who regularly intake fruits are expected to have minimized risk of chronic diseases. The Nutrients provided by the fruits are vital for proper maintenance of the body. But those fruits nowadays are ripened through some artificial means like usage of chemicals like calcium carbide as ripening agent which might even cause cancer. Important news that flashes during the mango seasons in television is that the fruit markets contain an artificially ripened fruit which is extremely hazardous to health. Artificial ripening of mangoes using calcium carbide was the important fact that was being displayed in the news. Despite repeated warnings, raids and seizures, chemically ripened fruits are flooding the market. According to health officials, the consumption of mangoes ripened using calcium carbide leads to various harmful effects like vomiting, diarrhoea, ulcers of throat and abdomen, general weakness, and sometimes damage of eye permanently and breathing shortness. To avoid such ill effects the consumers have to be careful in buying the mangoes, find out the artificially ripened mangoes. Finding out the artificially ripened fruits is difficult with human eye observation. To aid the detection we have developed a device which uses image processing to find the artificially ripened mangoes. The proposed device gets an input image of mango under test and compares the features (histogram values) with a naturally ripened one and detects fruits which are ripened artificially. This method makes usage of the Smartphone which runs android application that is installed in it and the image processing is executed to detect the artificially ripened fruits. The proposed system has an efficiency of 91% in the identification of the fruits ripened artificially.

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

Block Diagram

calcium carbide , artificially ripened mangoes , smart phone

Specifications

Hardware Requirements:

  • Raspberry pi
  • Camera
  • LCD
  • Bluetooth

 

 

Software Requirements:

  • Python  IDE

Learning Outcomes

  • Raspberry pi pin diagram and architecture
  • How to install python IDE  software
  • Setting up and installation procedure for raspberry pi
  • Introduction to python IDE
  • Basic coding in python IDE
  • Working of LCD
  • Interface LCD with raspberry pi?
  • Working of Bluetooth
  • Interface Bluetooth with raspberry pi?
  • Working of power supply
  • About Project Development Life Cycle:
    • Planning and Requirement Gathering( software’s, 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.
  • Project development Skills
    • Problem analyzing skills
    • Problem solving skills
    • Creativity and imaginary skills
    • Programming skills
    • Deployment
    • Testing skills
    • Debugging skills
    • Project presentation skills
    • Thesis writing skills

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