CVJan 20, 2025

FruitPAL: An IoT-Enabled Framework for Automatic Monitoring of Fruit Consumption in Smart Healthcare

arXiv:2502.01643v1h-index: 52
Originality Synthesis-oriented
AI Analysis

This addresses health monitoring and dietary awareness for individuals, especially those with allergies, but is incremental as it builds on existing object detection models and IoT frameworks.

The study tackled the problem of monitoring fruit consumption for health and allergy management by developing two IoT devices, FruitPAL and FruitPAL 2.0, which use YOLOv8 and YOLOv5 models to detect fruit types with improved accuracy and provide real-time notifications or nutritional estimates.

Fruits are rich sources of essential vitamins and nutrients that are vital for human health. This study introduces two fully automated devices, FruitPAL and its updated version, FruitPAL 2.0, which aim to promote safe fruit consumption while reducing health risks. Both devices leverage a high-quality dataset of fifteen fruit types and use advanced models- YOLOv8 and YOLOv5 V6.0- to enhance detection accuracy. The original FruitPAL device can identify various fruit types and notify caregivers if an allergic reaction is detected, thanks to YOLOv8's improved accuracy and rapid response time. Notifications are transmitted via the cloud to mobile devices, ensuring real-time updates and immediate accessibility. FruitPAL 2.0 builds upon this by not only detecting fruit but also estimating its nutritional value, thereby encouraging healthy consumption. Trained on the YOLOv5 V6.0 model, FruitPAL 2.0 analyzes fruit intake to provide users with valuable dietary insights. This study aims to promote fruit consumption by helping individuals make informed choices, balancing health benefits with allergy awareness. By alerting users to potential allergens while encouraging the consumption of nutrient-rich fruits, these devices support both health maintenance and dietary awareness.

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