Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Amina El Attaoui"'
Publikováno v:
Journal of Ambient Intelligence and Humanized Computing. 12:8777-8792
Blood pressure issues are related to many illnesses threatening human health and require continuous control and monitoring. Health telemonitoring is an innovative solution allowing wellbeing and increasing autonomy of patients. Moreover, machine lear
Autor:
Achraf Benba, Abdennaser Bourouhou, Salma Largo, Soufiane Kaissari, Abdelilah Jilbab, Amina El Attaoui
Publikováno v:
IET Wireless Sensor Systems. 10:320-332
Health telemonitoring systems are constrained by the computational and data transmission load resulting from the large volumes of various measured signals, e.g. in the fall detection application. Nevertheless, the trend of movement and the implementa
Publikováno v:
Wireless Personal Communications. 111:1955-1976
The technological progress of wireless communication, embedded systems and health offers innovative alternatives to medical care, in particular, telemonitoring and telediagnosis. ECG signal monitoring is a vital indicator in the control of heart dise
Publikováno v:
2020 International Conference on Electrical and Information Technologies (ICEIT).
The technological progress of wireless communication, embedded systems and health equipment offers innovative alternatives to medical care, in particular, the telemonitoring of vital signs such as the ECG signal for heart disease control. In this pap
Publikováno v:
2020 International Conference on Electrical and Information Technologies (ICEIT).
This work describes an implementation of a Wireless Sensor Network-based system for real-time remote monitoring of photovoltaic (PV) panel. This proposed system consists on three parts: (a) sensor node, which contains five sensors, namely: ambient te
Autor:
Achraf Benba, Abdelilah Jilbab, Amina El Attaoui, Abdennaser Bourouhou, Abdellah Kaissari, Soufiane Kaissari
Publikováno v:
International Journal on Engineering Applications (IREA). 9:162
Plant diseases are a major threat to food security. Thus, the identification of these diseases is crucial to alleviate the problem. Deep learning combined with image processing has proven to be efficient in order to identify such diseases accurately,