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SafeBite Fruit Scanner : A New Era in Fruit Quality and Safety Analysis

  • Unique Paper ID: 164239
  • Volume: 10
  • Issue: 12
  • PageNo: 1206-1214
  • Abstract:
  • In the pursuit of healthier eating habits, the quality and safety of fruits play a critical role in consumer choices. This research introduces FruitSense, a state-of-the-art system designed to assess various aspects of fruit quality through advanced image analysis and machine learning algorithms. The system is equipped with capabilities to evaluate fruit freshness, calculate calorie content, determine ripeness, and detect pesticide residues. By employing leading libraries such as Numpy, Matplotlib, Pandas, PyTorch, TensorFlow, and Keras, the system efficiently processes visual data from fruit images. Additionally, the Roboflow API is integrated to enhance data handling and model performance. The results demonstrate the model's ability to deliver precise assessments, empowering consumers to make informed decisions regarding fruit selection. By addressing these critical factors, FruitSense contributes to the broader goal of ensuring safe and healthy fruit consumption for all. This innovative solution paves the way for future advancements in fruit quality and safety assessment.
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  • ISSN: 2349-6002
  • Volume: 10
  • Issue: 12
  • PageNo: 1206-1214

SafeBite Fruit Scanner : A New Era in Fruit Quality and Safety Analysis

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