Nowadays, the increasing number of patients accompanied with the emergence of new symptoms and diseases makes heath monitoring and assessment a complicated task for medical staff and hospitals. Indeed, the processing of big and heterogeneous data collected by biomedical sensors along with the need of patients’ classification and disease diagnosis become major challenges for several health-based sensing applications. Thus, the combination between remote sensing devices and the big data technologies have been proven as an efficient and low cost solution for healthcare applications. In this paper, we propose a robust big data analytics platform for real time patient monitoring and decision making to help both hospital and medical staff. The proposed platform relies on big data technologies and data analysis techniques and consists of four layers: real time patient monitoring, real time decision and data storage, patient classification and disease diagnosis, and data retrieval and visualization. To evaluate the performance of our platform, we implemented our platform based on the Hadoop ecosystem and we applied the proposed algorithms over real health data. The obtained results show the effectiveness of our platform in terms of efficiently performing patient classification and disease diagnosis in healthcare applications.

A low-profile single-polarized folded Fresnel zone plate (FZP) lens antenna is presented for 5G millimeter-wave point-to-point communications in V-band. This antenna has two benefits: 1) the compactness of folded reflector structures made of a trans-reflector and a twist-reflector, and 2) the simplicity of FZP lenses. The idea of the folded structure is to triple the electrical path compared to nonfolded configurations. The combination of all these benefits leads to a very low-profile, high-directive, broadband, and low-cost antenna, as confirmed by measurements. A measured peak gain of 32.7 dBi is obtained at 60 GHz, with almost flat gain curve from 57 to 64 GHz, with a half-power beamwidth of 3°, compliant with ETSI V-band class 2 standard.