Falls represent a major public health risk worldwide for the elderly people. A fall not assisted in time can cause functional impairment in an elderly and a significant decrease in his mobility, independence, and life quality. In this sense, we propose IoTE-Fall system, an intelligent system for detecting falls of elderly people in indoor environments that takes advantages of the Internet of Thing and the ensemble machine learning algorithm. IoTE-Fall system employs a 3D-axis accelerometer embedded into a 6LowPAN wearable device capable of capturing in real time the data of the movements of elderly volunteers. To provide high efficiency in fall detection, in this paper, four machine learning algorithms (classifiers): decision trees, ensemble, logistic regression, and Deepnets are evaluated in terms of AUC ROC, training time and testing time. The acceleration readings are processed and analyzed at the edge of the network using an ensemble-based predictor model that is identified as the most suitable predictor for fall detection. The experiment results from collection data, interoperability services, data processing, data analysis, alert emergency service, and cloud services show that our system achieves accuracy, precision, sensitivity, and specificity above 94%.

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This paper describes the pathway towards the realisation of a 5G Facility that will allow the validation of the major 5G Key Performance Indicators (KPIs). It reflects the approach that the 5GENESIS consortium will adopt in this direction. More precisely, it describes the key design principles of such Facility as well as the targeted use cases for the KPIs validation. The adopted approach for the Facility realisation includes the design of a common implementation blueprint that will be instantiated in five Platforms distributed across Europe. To maximise the diversity and the efficiency of the Facility, complementary performance objectives have been selected for the Platforms, while specific characteristics from different vertical industries have been allocated to each of them.

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