FruitPAL: An IoT-Enabled Framework for Automatic Monitoring of Fruit Consumption in Smart Healthcare
Abdulrahman Alkinani, Alakananda Mitra, Saraju P. Mohanty and, Elias Kougianos

TL;DR
This paper presents FruitPAL devices that utilize IoT and advanced AI models to automatically detect fruits, assess nutritional value, and alert users about allergies, promoting safe and healthy fruit consumption in smart healthcare.
Contribution
Introduction of two automated IoT devices, FruitPAL and FruitPAL 2.0, using YOLO models for fruit detection, allergy alerts, and nutritional analysis to enhance dietary health monitoring.
Findings
FruitPAL accurately detects multiple fruit types and alerts for allergies.
FruitPAL 2.0 estimates nutritional value to promote healthy eating.
Real-time notifications improve dietary awareness and safety.
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…
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Taxonomy
TopicsIoT and Edge/Fog Computing
MethodsYou Only Look Once
