Fall Detection using CNN architecture #tinyml #cainvas #FallDetection

Did you know that falls are the leading cause of injury-related hospitalizations among older adults? In fact, according to the Centers for Disease Control and Prevention (CDC), one in four older adults falls each year, resulting in over 3 million emergency department visits and 800,000 hospitalizations annually in the United States alone.

cAInvas is built on no-code, low-code and full-code principles for AI applications and models derived from all popular platform like TensorFlow, keras, PyTorch and others.

cAInvas is bolstered by native integration of deepC inference framework and a compiler designed for embedded devices. It comes with python and c++ notebooks to develop end-to-end application with autoML and ensemble of ML models.

Best of all, it is free for all students, researchers and hobbyists to spread fast adoption of ML models for tiny devices. Reach out for more information:
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