A review of signal processing algorithms employing Wi-Fi signals for positioning and recognition of human activities is presented. The principles of how channel state information (CSI) is used and how the Wi-Fi sensing systems operate are reviewed. It provides a brief introduction to the algorithms that perform signal processing, feature extraction and recognitions, including location, activity recognition, physiological signal detection and personal identification. Challenges and future trends of Wi-Fi sensing are also discussed in the end.
Currently, Infrastructure as a Service(IaaS) and Platform as a Service(PaaS) platforms play a role as a cloud operating system(COS).They are separated from each other in resource management, which may cause inconsistent resource status and result in the decrease of performance. Moreover, heterogeneous resources are not managed well in existing cloud computing platforms. Referring to the theory of operating system, we propose a unified architecture model of cloud operating system, which has six layers corresponding to the layered architecture of legacy operating system. Based on this architecture, a new cloud operating system called Hua-Cloud Computing System(HCOS) is realized. In HCOS, the hybrid resources are managed in a unified way. This method improves the unified scheduling capability of heterogeneous resources and eliminates the problem of resource status inconsistency. The main characteristics of HCOS are introduced and two typical applications are illustrated in this paper.