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Falls constitute a major health problem among the elderly. The economic significance of the treatment of falls is overwhelming and has led several governments to allocate a huge fraction of their budget to this cause. This project aims to reduce the risks of unattended falls by using readings from wearables to detect fall patterns. This project attempts to incorporate best practices in data ingress, data preprocessing, data privacy, data modelling and visualization to develop a user-friendly and cost-effective system to detect falls in smart homes

Jupyter Notebook 95.18% Java 3.95% Python 0.87%

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