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    FITGEN - AI Smart Fitness Companion: An Integrated Multi-Modal Approach to Personalized Health and Fitness Management
    (Institute of Electrical and Electronics Engineers Inc., 2025-12-09) Gunawardena S.N.A; Jayamali P.L.W; Methsandi K.A.N.; Gamage R.P.D.D; Wijendra, D; Krishara, J
    This research presents FITGEN, a comprehensive AI-powered fitness companion system that integrates four core modules: AI Gym Trainer with Gamification, Medical Guidance System, AI Nutritionist, and Social Bridge for inclusive fitness engagement. Unlike existing solutions that address singular aspects of fitness technology, FITGEN provides a holistic approach combining real-time pose detection, chronic disease management, personalized nutrition planning, and accessibility features for special abled youth. The system utilizes Flutter framework with Firebase backend, implementing Google ML Kit for pose estimation, TensorFlow models for nutrition recommendations, and ESP32-based IoT sensors for vital sign monitoring. Comprehensive evaluation demonstrates 93.5% pose detection accuracy, 96% nutrition recommendation accuracy, 73% user retention after 4 weeks, and significant improvements in accessibility compliance. The integrated approach addresses critical gaps in existing fitness technologies while maintaining high user engagement and safety standards for diverse user populations including those with chronic conditions and developmental disabilities.
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    WORDEX: Early Dyslexia Detection and Support
    (Institute of Electrical and Electronics Engineers Inc., 2025) Ganegoda, S.H; Dissanayake, O; Samarakoon, S; Jayawardana, N; Thelijjagoda, S; Gunathilake, P
    Dyslexia is a prevalent and complex learning disability that affects approximately 5% of primary school students worldwide. It often manifests as persistent difficulties in reading, writing, spelling, and overall academic performance, which can lead to long-term educational and psychological impacts if not addressed early. To facilitate the early identification and support of dyslexic learners aged 7 to 10, this paper introduces Wordex, an innovative and adaptive educational platform. Wordex is designed to screen for multiple dyslexia subtypes and provide targeted interventions through engaging, interactive, and personalized learning activities. The platform features an integrated machine learning-based screening system that analyzes user interactions and performance metrics to assess the risk of dyslexia. Upon identification, the platform delivers tailored remedial exercises that align with national school curricula, aiming to strengthen specific cognitive and linguistic skills. Wordex is developed using a modern technology stack including Spring Boot, Flutter, Python libraries, Firebase, and MongoDB, and incorporates capabilities such as image processing, supervised learning algorithms, real-time progress tracking, and cloud-based data management. A user-centered design approach and iterative testing cycles were employed to ensure the platform is accessible, intuitive, and pedagogically effective. Wordex contributes significantly to the field of educational technology by offering a scalable, research-informed intervention tool. Future enhancements include multilingual support, broader age group coverage, and integration with classroom learning environments.