Reducing the energy consumption to the minimum
is a crucial design requirement for all body area sensor networks.
Sensors deployed on the human body, especially at the limbs often
move along different positions. Usually, the transmit power is set
to a sufficiently high value to achieve reliable transmission for the
constellation with highest attenuation. For periodic movements,
data transmission can be carried out at the position of the lowest
path loss between the sender and the receiver, provided this
position can be reliably identified. We propose a novel framework
that predicts this position using acceleration data and the received
signal strength. By learning a correlation between these signals,
accurate predictions can be performed and up to
24
:
7%
of
the power spent by a Bluetooth Low Energy module for the
transmission of a packet can be saved while still achieving the
same packet error rate as with sending using the higher transmit
power.
«
Reducing the energy consumption to the minimum
is a crucial design requirement for all body area sensor networks.
Sensors deployed on the human body, especially at the limbs often
move along different positions. Usually, the transmit power is set
to a sufficiently high value to achieve reliable transmission for the
constellation with highest attenuation. For periodic movements,
data transmission can be carried out at the position of the lowest
path loss between the sender...
»