A Framework for the Estimation and Validation of Energy Consumption in Wireless Sensor Networks

Karagiannis, A.; Vouyioukas, Demosthenes

doi:10.1155/2015/124987

Cited by 6 publications

(2 citation statements)

References 23 publications

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“…In BSNs, sensor energy is consumed by three main modules: the sensing module responsible for sensing physiological data, the microcontroller unit (MCU) in charge of performing of data processing such as data sampling and the radio communication module responsible of the wireless communication between the sensor and coordinator [7, 8, 63, 64]. Thus, the total energy consumed by a sensor is expressed as:

E_{normalt} = E_{sensing} + E_{MCU} + E_{radio}

where

E_{sensing} = V_{normals} I_{normals} t_{normals}

E_{MCU} = V_{MCU a} I_{MCU a} t_{MCU a} + V_{MCU i} I_{MCU i} t_{MCU i}

E_{radio} = V_{tx} I_{tx} N_{tx} t_{tx} + V_{rx} I_{rx} N_{rx} t_{rx} + V_{lx} I_{lx} t_{lx}

E_{normals}

is the energy consumed from sensing;

V_{normals}

and

I_{normals}

are the voltage and current energy consumed from sensing data during the time

t_{normals}

.…”

Section: Application To Bsns: Experiments and Resultsmentioning

confidence: 99%

“…In BSNs, sensor energy is consumed by three main modules: the sensing module responsible for sensing physiological data, the microcontroller unit (MCU) in charge of performing of data processing such as data sampling and the radio communication module responsible of the wireless communication between the sensor and coordinator [7,8,63,64]. Thus, the total energy consumed by a sensor is expressed as:…”

Section: Energy Modelmentioning

confidence: 99%

See 1 more Smart Citation

Toward fast and accurate emergency cases detection in BSNs

Boudargham

Sibai

Abdo

et al. 2020

IET wirel. sens. syst.

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In body sensor networks (BSNs), medical sensors capture physiological data from the human body and send them to the coordinator who act as a gateway to health care. The main aim of BSNs is to save peoples' lives. Therefore, fast and correct detection of emergencies while maintaining low-energy consumption of sensors is essential requirement of BSNs. In this study, the authors propose a new adaptive data sampling approach, where the sampling ratio is adapted based on the sensed data variation. The idea is to use the modified version of the cumulative sum (CUSUM) algorithm (modified CUSUM) that they previously proposed for wireless sensor networks to monitor the data variability, and adapt the sampling rate accordingly. Modified CUSUM is then applied to the adaptively sampled data to detect anomalies, and the correlation property between physiological parameters will be used to identify emergency cases from false alarms. Several experiments are performed and compared to evaluate the efficiency of their approach, and different parameters are considered.

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E_{normalt} = E_{sensing} + E_{MCU} + E_{radio}

where

E_{sensing} = V_{normals} I_{normals} t_{normals}

E_{MCU} = V_{MCU a} I_{MCU a} t_{MCU a} + V_{MCU i} I_{MCU i} t_{MCU i}

E_{radio} = V_{tx} I_{tx} N_{tx} t_{tx} + V_{rx} I_{rx} N_{rx} t_{rx} + V_{lx} I_{lx} t_{lx}

E_{normals}

is the energy consumed from sensing;

V_{normals}

and

I_{normals}

are the voltage and current energy consumed from sensing data during the time

t_{normals}

.…”

Section: Application To Bsns: Experiments and Resultsmentioning

confidence: 99%

“…In BSNs, sensor energy is consumed by three main modules: the sensing module responsible for sensing physiological data, the microcontroller unit (MCU) in charge of performing of data processing such as data sampling and the radio communication module responsible of the wireless communication between the sensor and coordinator [7,8,63,64]. Thus, the total energy consumed by a sensor is expressed as:…”

Section: Energy Modelmentioning

confidence: 99%