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Development of a Daily Step Monitoring Mobile Application for Promoting improved Wellness
K. Revanth 1, M. Sri Sai 2, K. Pramod 3, Mrs. P. Venkata Pratima 4
1,2,3 UG Scholars, 4Assistant Professor
1,2,3,4 Department of Artificial Intelligence & Data Science,
1,2,3,4 Guru Nanak Institutions Technical Campus, Hyderabad, Telangana, India
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Abstract - In this paper, we propose a real-time mobile application designed for daily step monitoring and personalized wellness tracking, aimed at combating sedentary lifestyles and their associated health risks such as obesity, diabetes, and cardiovascular diseases. Unlike traditional fitness tracking systems that rely on external devices, our solution utilizes Android’s built-in sensors—specifically the accelerometer and step counter—to perform accurate step detection in a cost-effective and accessible manner. The application architecture integrates cloud-based storage through ThingSpeak, enabling secure and scalable data retention for long-term activity tracking and trend analysis.
To enhance user engagement and promote sustained physical activity, the system incorporates artificial intelligence (AI) techniques to deliver personalized fitness insights, detect irregular step patterns, and provide goal-based motivational feedback. Users can set custom fitness goals, monitor progress through interactive data visualizations, and receive AI- powered recommendations tailored to their movement behavior. By combining real-time sensor data, cloud computing, and intelligent analytics within a unified framework, this application serves as a holistic and adaptive wellness companion, contributing to preventive healthcare and promoting a data-driven approach to personal fitness management. [2][3]
Key Words: Step Tracking, Mobile Health (mHealth), Android Sensors, AI Analytics, Cloud Storage, ThingSpeak, Fitness Monitoring, Wellness Application, Human Activity Recognition.
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