International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 04 | April 2025
p-ISSN: 2395-0072
www.irjet.net
IOT -BASED SYSTEM FOR MILK QUALITY ASSESSMENT, ADULTERATION DETECTION, AND GRADING Swastik Vaidya1, Prof. Prachi A Deshpande2 1M. E Student, Department of Electronics and Telecommunications Engineering, Savitribai Phule Pune University,
Pune-411005
2Professor, Department of Electronics and Telecommunications, DPCOE College of Engineering Pune, Pune-411005
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Abstract - This project aims to develop a comprehensive
and innovative smart system for milk quality analysis and grading, leveraging the capabilities of an ESP32 microcontroller and a suite of specialized sensors. By integrating pH, turbidity, spectral, TDS, temperature, and gas sensors, the system will meticulously measure key parameters that are critical indicators of milk quality and integrity.
This Milk, a vital dietary staple, is often subject to adulteration and quality degradation, posing significant health risks and economic losses. To address these concerns, this project aims to develop an innovative IoTpowered device capable of accurately assessing milk quality through a comprehensive analysis of its properties. By leveraging a suite of advanced sensors, including pH, turbidity, spectral, TDS, temperature, and gas sensors, the device can measure critical parameters that indicate adulteration, spoilage, and origin. The collected data is seamlessly integrated with a 16x2 LCD display and the Blynk IoT platform, enabling real-time monitoring, analysis, and remote access. Through rigorous sensor calibration and advanced data processing algorithms, the device can accurately identify adulterated milk, determine its origin (cow or buffalo), and assign a quality grade based on its freshness and overall composition. This innovative solution has the potential to significantly enhance food safety, improve dairy industry transparency, and empower consumers to make informed choices about the milk they consume.
The collected sensor data will be intelligently processed and analyzed, enabling the system to: • Accurately assess milk quality: By comparing the measured parameters against established quality standards, the system will reliably determine the overall quality of the milk sample. • Detect adulteration: Through careful analysis of the spectral and gas sensor data, the system will be able to identify potential adulterants, such as water, urea, or detergent, ensuring the purity of the milk. • Discriminate between milk sources: By leveraging the unique spectral signatures of cow and buffalo milk, the system will be able to distinguish between these two primary sources, providing valuable information for consumers and producers.
Specifically, the device will measure the following parameters: • pH: Indicates acidity or alkalinity, which can be affected by adulteration or spoilage. Adulterated milk may have a lower or higher pH than pure milk, depending on the adulterant used.
• Grade milk based on quality and freshness: By combining the assessment of multiple parameters, the system will assign a precise grade to the milk, reflecting its quality and level of freshness.
• Turbidity: Measures the cloudiness of milk, which can be increased by the addition of water or other substances. Adulterated milk often has a higher turbidity than pure milk.
The collected data will be seamlessly displayed on a 16x2 LCD for local monitoring and transmitted to the Blynk IoT platform, facilitating remote access, analysis, and decisionmaking. By empowering users with real-time insights into milk quality, this system will play a pivotal role in safeguarding public health and promoting fair and transparent dairy practices.
1.1 Sub Heading 1 • Enhanced Food Safety: Protects consumers from consuming adulterated or low-quality milk.
Key Words: Milk Quality Analysis , Milk Adulteration Detection , IoT-Based Milk Monitoring , Sensor Fusion for Milk Grading , ESP32-Based Milk Quality System
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• Improved Dairy Industry Transparency: Ensures fair practices and quality control.
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