As the emerging development of IoT circumstance, on-line detections or observations of a system states become easier by facilitating its corresponding multi-sensory responses, and thus the description of a system behavior becomes clearer. Abundant on-line multi-channel information from the embedded sensors would be advantageous to the understanding of the system. Though having the information, it is still uneasy to thoroughly assess the integrity behavior of the system without a eligible system identification method. In the study, through a recurrent function approximation by an integrated multiregression of support vector regression (SVR), the identification has been developed and represented as a family of characteristic functions. With the set of characteristic functions, a design of IoT based live interaction of adaptive control or human-machine system could hereafter followed up. The study constructed primarily the SVR based framework of the recurrent multisensor system identification. There are two major contributions of the study: First, an IoT aspect for the discovery of the multiple regression extended from an underlying SVR, second, a technical overcoming in the realization of the recurrent framework of SVR.