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

Abdulrahman Alkinani, Alakananda Mitra, Saraju P. Mohanty, Elias Kougianos

TL;DR

FruitPAL introduces two IoT-enabled CPS devices for smart healthcare: FruitPAL for real-time allergen detection and caregiver alerts, and FruitPAL 2.0 for detection of 15 fruit types with nutritional estimation. The approach relies on YOLO-based object detectors (YOLOv8 for FruitPAL and YOLOv5 V6.0 for FruitPAL 2.0) trained on the Allergic-fruit dataset to provide instant allergen warnings and daily nutrient feedback via GSM notifications. A detailed CPS architecture with End/Cloud/Edge layers, on-device inference, and cloud-based messaging underpins real-time operation and scalability, supported by extensive dataset annotation and augmentation. The work demonstrates practical viability for safe and healthful fruit consumption in smart healthcare settings and outlines future directions including face recognition and multi-user health record integration.

Abstract

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.

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

TL;DR

FruitPAL introduces two IoT-enabled CPS devices for smart healthcare: FruitPAL for real-time allergen detection and caregiver alerts, and FruitPAL 2.0 for detection of 15 fruit types with nutritional estimation. The approach relies on YOLO-based object detectors (YOLOv8 for FruitPAL and YOLOv5 V6.0 for FruitPAL 2.0) trained on the Allergic-fruit dataset to provide instant allergen warnings and daily nutrient feedback via GSM notifications. A detailed CPS architecture with End/Cloud/Edge layers, on-device inference, and cloud-based messaging underpins real-time operation and scalability, supported by extensive dataset annotation and augmentation. The work demonstrates practical viability for safe and healthful fruit consumption in smart healthcare settings and outlines future directions including face recognition and multi-user health record integration.

Abstract

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.

Paper Structure

This paper contains 27 sections, 26 figures, 7 tables, 1 algorithm.

Figures (26)

  • Figure 1: The vitamins FruitPAL 2.0 promotes
  • Figure 2: Preventable Disease by Eating Fruit.
  • Figure 3: FruitPAL Method
  • Figure 4: Three Different Computing Platforms Visible in FruitPAL's Architecture: End Platform, Cloud Platform, and Edge Platform
  • Figure 5: End Platform in FruitPAL
  • ...and 21 more figures