WITHDRAWN: Design and development of IoT based health monitoring system for military applications

Anand, L. Vijay; Kotha, Murali Krishna; Kannan, Nimmati Satheesh; Kumar, Sunil; Meera, M.; Shawl, Rashed Qayoom; Ray, Abhra Pratip

doi:10.1016/j.matpr.2020.10.767

Cited by 9 publications

(3 citation statements)

References 4 publications

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“…Most of these devices are designed to convert AC power supply voltages to lower voltages for electronic circuits. The power supply can be divided into several blocks, each of which has a specific purpose [11]. In order for the tool to be used, it requires a power supply that provides power to the entire circuit.…”

Section: Power Supply Circuit Designmentioning

confidence: 99%

Design of room capacity measurement and body temperature detection based on atmega328 microcontroller

Azhari

Marbun

Karolina

et al. 2022

J. Phys.: Conf. Ser.

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The outbreak of Corona Virus Disease 2019 (Covid 19) cases that occurred from 2020 until now limits the current maximum allowed room capacity, which is only around 25% to 50% of the maximum room capacity. The purpose of this study is to design a device that can detect temperature and limit room capacity automatically as an effort to prevent the transmission of the covid 19 virus. In designing a room capacity measuring device and an atmega328 microcontroller-based body temperature detector with a viewer on an android smartphone. The ultrasonic sensor HC-SR04 is used to measure the capacity of the room to determine the number of people entering and leaving. Then this tool also uses the MLX90614 sensor to detect the body temperature of everyone who wants to enter with the temperature conditions below 38°C. When both sensors have worked according to their functions, the doorstop can be opened. The results of the data obtained on each sensor will be sent to the microcontroller as a control center on a system so that it can be displayed on the LCD and using an additional device, namely esp8266 as a wifi communication module. After testing it can be concluded that the tool works well. The comparison of the results of the MLX90614 sensor with a standard tool. The data obtained is quite accurate with maximum error only 2.2% with the comparison tool.

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Section: Power Supply Circuit Designmentioning

confidence: 99%

Design of room capacity measurement and body temperature detection based on atmega328 microcontroller

Azhari

Marbun

Karolina

et al. 2022

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

show abstract

“…Anand et al introduced a device that can be attached to soldiers' bodies to track their health and the current situation. The device uses IoT technology for data exchange between soldiers and control rooms [19]. Kadhim et al presented a monitoring system for IoT-based healthcare organizations.…”

Section: Related Workmentioning

confidence: 99%

Design and Evaluation of Large-Scale IoT-Enabled Healthcare Architecture

Said

Tolba

2021

Applied Sciences

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Employment of the Internet of Things (IoT) technology in the healthcare field can contribute to recruiting heterogeneous medical devices and creating smart cooperation between them. This cooperation leads to an increase in the efficiency of the entire medical system, thus accelerating the diagnosis and curing of patients, in general, and rescuing critical cases in particular. In this paper, a large-scale IoT-enabled healthcare architecture is proposed. To achieve a wide range of communication between healthcare devices, not only are Internet coverage tools utilized but also satellites and high-altitude platforms (HAPs). In addition, the clustering idea is applied in the proposed architecture to facilitate its management. Moreover, healthcare data are prioritized into several levels of importance. Finally, NS3 is used to measure the performance of the proposed IoT-enabled healthcare architecture. The performance metrics are delay, energy consumption, packet loss, coverage tool usage, throughput, percentage of served users, and percentage of each exchanged data type. The simulation results demonstrate that the proposed IoT-enabled healthcare architecture outperforms the traditional healthcare architecture.

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“…In information and communication technology, the Internet of things (IoT), as stateof-the-art technology for intelligent interconnectivity, has recently been presented to communicate at any time, from anywhere, and through any object. The IoT is extensively utilized in different fields, e.g., manufacturing [1], home [2], agriculture [3], healthcare [4], environment [5], military [6], retail [7], and sports [8]. It can be used in a great variety of applications for different purposes in mentioned fields, e.g., temperature control, appliance control, communication, quality control, threat analysis, situational awareness, risk assessment, patient care, fitness trackers, crop management, fire detection, species tracking, weather prediction, traffic flow, smart parking, theft protection, inventory control, and focused marketing.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Models for the Prediction of Energy Consumption Based on Cooling and Heating Loads in Internet-of-Things-Based Smart Buildings

et al. 2022

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In this article, the consumption of energy in Internet-of-things-based smart buildings is investigated. The main goal of this work is to predict cooling and heating loads as the parameters that impact the amount of energy consumption in smart buildings, some of which have the property of symmetry. For this purpose, it proposes novel machine learning models that were built by using the tri-layered neural network (TNN) and maximum relevance minimum redundancy (MRMR) algorithms. Each feature related to buildings was investigated in terms of skewness to determine whether their distributions are symmetric or asymmetric. The best features were determined as the essential parameters for energy consumption. The results of this study show that the properties of relative compactness and glazing area have the most impact on energy consumption in the buildings, while orientation and glazing area distribution are less correlated with the output variables. In addition, the best mean absolute error (MAE) was calculated as 0.28993 for heating load (kWh/m2) prediction and 0.53527 for cooling load (kWh/m2) prediction, respectively. The experimental results showed that our method outperformed the state-of-the-art methods on the same dataset.

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WITHDRAWN: Design and development of IoT based health monitoring system for military applications

Cited by 9 publications

References 4 publications

Design of room capacity measurement and body temperature detection based on atmega328 microcontroller

Design of room capacity measurement and body temperature detection based on atmega328 microcontroller

Design and Evaluation of Large-Scale IoT-Enabled Healthcare Architecture

Machine Learning Models for the Prediction of Energy Consumption Based on Cooling and Heating Loads in Internet-of-Things-Based Smart Buildings

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