  Worldwide 2019 million people have been infected and 4.5 million have lost
their lives in the ongoing Covid-19 pandemic. Until vaccines became widely
available, precautions and safety measures like wearing masks, physical
distancing, avoiding face touching were some of the primary means to curb the
spread of virus. Face touching is a compulsive human begavior that can not be
prevented without making a continuous consious effort, even then it is
inevitable. To address this problem, we have designed a smartwatch-based
solution, CovidAlert, that leverages Random Forest algorithm trained on
accelerometer and gyroscope data from the smartwatch to detects hand transition
to face and sends a quick haptic alert to the users. CovidALert is highly
energy efficient as it employs STA/LTA algorithm as a gatekeeper to curtail the
usage of Random Forest model on the watch when user is inactive. The overall
accuracy of our system is 88.4% with low false negatives and false positives.
We also demonstrated the system viability by implementing it on a commercial
Fossil Gen 5 smartwatch.
