An IoT Based e-Health Platform Using Raspberry Pi

Khoumeri, El-Hadi; Cheggou, Rabea; Ferhah, Kamila

doi:10.1007/978-3-030-39445-5_20

Cited by 3 publications

(1 citation statement)

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“…In parallel, there has also been a large uptake by the scientific and engineering communities who have capitalised on the relative affordability of the Raspberry Pi devices, as well as their small size, low‐power consumption and flexibility to create innovative products. These devices have been incorporated into instruments for a diverse range of applications such as medical and e‐health (Khoumeri et al., 2020), security and surveillance monitoring (Sajjad et al., 2019) and robotics (Bindu et al., 2019). Agricultural, forest and ecological scientists have also been active in this emerging field and at the forefront of developing new measurement and monitoring technologies.…”

Section: Introductionmentioning

confidence: 99%

A Raspberry Pi‐based camera system and image processing procedure for low cost and long‐term monitoring of forest canopy dynamics

2021

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Section: Introductionmentioning

confidence: 99%

A Raspberry Pi‐based camera system and image processing procedure for low cost and long‐term monitoring of forest canopy dynamics

2021

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People Counter with Area Occupancy Control for Covid-19

Fraoucene

Khoumeri

Hamouda

et al. 2020

Artificial Intelligence and Renewables Towards an Energy Transition

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Governments have imposed social distancing regulations to counter the coronavirus pandemic. An automated occupancy control system to provide a more cost-effective and efficient way to abide with these safety regulations. With the generalization of the use of digital images, the analysis of movement in video sequences has proved to be an essential tool for various applications such as video surveillance, robotics etc. The advance in video processing algorithms and the fast computational capability, give a possibility to use a video tracking and counting people in real time. Estimating the number of people in real time is useful information for several applications such as security and health management. With the COVID-19 pandemic, the counting of people present in a region of interest is important to control the area occupancy in order to minimize human virus transmission. In this paper we present a finished solution for counting people present in the same area. The system is based on Raspberry Pi and a common camera. The method called BLOB (Binary Large Object) analysis is used. The performance of the system, achieving an average count rate between 95% and 98%.

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Convergence Catalysts: Exploring the Fusion of Embedded Systems, IoT, and Artificial Intelligence

Rosca

2024

Springer Tracts in Nature-Inspired Computing

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An IoT Based e-Health Platform Using Raspberry Pi

Cited by 3 publications

References 1 publication

A Raspberry Pi‐based camera system and image processing procedure for low cost and long‐term monitoring of forest canopy dynamics

A Raspberry Pi‐based camera system and image processing procedure for low cost and long‐term monitoring of forest canopy dynamics

People Counter with Area Occupancy Control for Covid-19

Convergence Catalysts: Exploring the Fusion of Embedded Systems, IoT, and Artificial Intelligence

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