This invention relates to the field of
data processing technology and discloses a
big data analysis
system based on the usage habits of power
bank users. It includes a cloud-based
big data analysis platform, a cabinet control node, and a power
bank communication module. The cloud-based
big data analysis platform extracts historical rental characteristics to construct a data increment prediction model, generates predicted data volume labels, and sends them to the cabinet control node. The cabinet control node calculates the available channel evaluation index based on the total predicted data volume and issues power
attenuation factor and extended contention window commands when the volume is below a preset congestion threshold. The power
bank communication module reduces the
gain of the RF front-end
amplifier according to the commands and resets the upper limit of the random backoff counter in the
carrier sense multiple access (CMI) collision avoidance mechanism to
complete data upload. This solution reduces the probability of co-channel interference and the number of data retransmissions, shortens the
channel occupancy time, and avoids
communication link disconnection due to channel congestion.