  Falls represent one of the most detrimental occurrences for the elderly.
Given the continually increasing ageing demographic, there is a pressing demand
for advancing fall detection systems. The swift progress in sensor networks and
the Internet of Things (IoT) has made human-computer interaction through sensor
fusion an acknowledged and potent approach for tackling the issue of fall
detection. Even IoT-enabled systems can deliver economical health monitoring
solutions tailored to pregnant women within their daily environments. Recent
research indicates that these remote health monitoring setups have the
potential to enhance the well-being of both the mother and the infant
throughout the pregnancy and postpartum phases. One more emerging advancement
is the integration of 'panic buttons,' which are gaining popularity due to the
escalating emphasis on safety. These buttons instantly transmit the user's
real-time location to pre-designated emergency contacts when activated. Our
solution focuses on the above three challenges we see every day. Fall detection
for the elderly helps the elderly in case they fall and have nobody around for
help. Sleep pattern sensing is helpful for pregnant women based on the SPO2
sensors integrated within our device. It is also bundled with heart rate
monitoring. Our third solution focuses on a panic situation; upon pressing the
determined buttons, a panic alert would be sent to the emergency contacts
listed. The device also comes with a mobile app developed using Flutter that
takes care of all the heavy processing rather than the device itself.
