Fruit Quality Detection using Thermometer

https://doi.org/10.55529/jipirs.25.20.27

Authors

  • Madhupriya Sagar Kamuni Students, Department of Information Technology, Shree Siddheswar Womem’s College of Engineering, Solapur (MS), India
  • Tulsi Pandit Devasani Students, Department of Information Technology, Shree Siddheswar Womem’s College of Engineering, Solapur (MS), India
  • Lavanya Ramesh Nalla Students, Department of Information Technology, Shree Siddheswar Womem’s College of Engineering, Solapur (MS), India
  • Dr Kazi Kutubuddin Sayyad Liyakat Associate Professor, Department of AI and DS, Shree Siddheswar Womem’s College of Engineering, Solapur (MS), India

Keywords:

Fruit quality Detection, Real Time Performance, Digital Thermometer.

Abstract

Fruit is incredibly crucial to our daily lives. Globalization is causing a daily decline in food quality. The fruit is given various additives or preservatives to make it look appealing or fresh. The majority of fruit is now preserved using chemicals, which contaminates the fruit. The consumer wants healthy fruit as a result of the diseases caused by this contamination. For a healthy lifestyle, many prefer organic fruit. We therefore require such a technology that aids in determining the fruit's quality in order to avoid the issues related to the fruit without human interpretation. Such a tool is necessary in order to inform us about organic fruit. Consequently, to satisfy this customer demand we created a tool that determines whether fruit is of good or poor quality. The usage of several sensors in the fruit sector is illustrated in this paper. Fruit condition can be determined with the aid of sensors like the resistance temperature detector sensor and thermocouple. Effectively present in homes and small-scale fruit industries, this system.

Published

2022-09-06

How to Cite

Madhupriya Sagar Kamuni, Tulsi Pandit Devasani, Lavanya Ramesh Nalla, & Dr Kazi Kutubuddin Sayyad Liyakat. (2022). Fruit Quality Detection using Thermometer. Journal of Image Processing and Intelligent Remote Sensing, 2(05), 20–27. https://doi.org/10.55529/jipirs.25.20.27

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