Bayesian Smart Gateway and Information driven Based Communication for Noisy IOT Scenario

Computer Engineering

Assessment in Internet of Things has recently received much attention due to its large application in the areas of object classification, target tracking and medical diagnosis etc. Machine-to-Machine communication plays a significant role in supporting Internet of Thing . This system is concerned about multiuser detection for large M2M supported by Low-Activity Code Division Multiple Access. One major challenge is the huge amount of data generated by the sensing devices, which make the control of sending useless data. To face this challenge, we present a Bayesian Inference Approach , which allows avoiding the transmission of high spatio -temporal correlated data. BIA is based on a hierarchical architecture with simple nodes, smart gateways and data centers. Belief Propagation algorithm has been chosen for performing an estimate inference on our model in order to restore the missing sensing data. BIA is evaluated based on the data collected from real sensors and according to different outlines.

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