An Early Drowning Detection System for Internet of Things (IoT) Applications

Ramdhan, Muhammad; Ali, Muhammad; N, Paulson Eberechukwu; G, Nurzal Effiyana; Ali, Samura; M.Y, Kamaludin

doi:10.12928/telkomnika.v16i4.9046

Cited by 13 publications

(5 citation statements)

References 11 publications

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“…Similar to prior two-module systems, a receiver alert is delivered if a heart pressure reading exceeds the threshold. Ramdhan et al [ 72 ] implemented pulse sensors in a three-module sensor-based system. The system is divided into a monitoring system, an access point, and a drowning detection module.…”

Section: Sensor-based Techniques For Drowning Detectionmentioning

confidence: 99%

“…Only those parameters that can operate as consistent, reliable parameters should be considered when deciding which to use for measurement. Based on these and other studies, the following variables were chosen: heart rate [ 63 , 71 , 72 ], blood oxygen saturation [ 64 , 76 ], depth of immersion [ 70 ], pattern of movement [ 73 ], and body temperature [ 77 , 78 ]. All the mentioned factors are reliable, with values that may vary from person to person but stay within a stable range.…”

Section: Sensor-based Techniques For Drowning Detectionmentioning

confidence: 99%

See 1 more Smart Citation

Enhancing Water Safety: Exploring Recent Technological Approaches for Drowning Detection

Jalalifar,

Belford,

Erfani

et al. 2024

Sensors

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Drowning poses a significant threat, resulting in unexpected injuries and fatalities. To promote water sports activities, it is crucial to develop surveillance systems that enhance safety around pools and waterways. This paper presents an overview of recent advancements in drowning detection, with a specific focus on image processing and sensor-based methods. Furthermore, the potential of artificial intelligence (AI), machine learning algorithms (MLAs), and robotics technology in this field is explored. The review examines the technological challenges, benefits, and drawbacks associated with these approaches. The findings reveal that image processing and sensor-based technologies are the most effective approaches for drowning detection systems. However, the image-processing approach requires substantial resources and sophisticated MLAs, making it costly and complex to implement. Conversely, sensor-based approaches offer practical, cost-effective, and widely applicable solutions for drowning detection. These approaches involve data transmission from the swimmer’s condition to the processing unit through sensing technology, utilising both wired and wireless communication channels. This paper explores the recent developments in drowning detection systems while considering costs, complexity, and practicality in selecting and implementing such systems. The assessment of various technological approaches contributes to ongoing efforts aimed at improving water safety and reducing the risks associated with drowning incidents.

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Section: Sensor-based Techniques For Drowning Detectionmentioning

confidence: 99%

Section: Sensor-based Techniques For Drowning Detectionmentioning

confidence: 99%

Enhancing Water Safety: Exploring Recent Technological Approaches for Drowning Detection

Jalalifar,

Belford,

Erfani

et al. 2024

Sensors

View full text Add to dashboard Cite

show abstract

“…However, the system did not consider the complexities of in this case, the alarm could trigger too late, and the swimmer may not be able to be rescued in time; or it could trigger too early and create a false alarm [21]. To address this issue, the system must be further developed to better understand the nuanced scenarios of a near-drowning experience [22][23][24]. This may require the implementation of sensors that can judge the swimmer's movements and breathing patterns, as well as improved algorithms that are able to accurately assess the swimmer's well-being.…”

Section: Drowning Detection Using Multisensorsmentioning

confidence: 99%

A Low-Cost Approach for Drowning Detection and Alertness

Ibrahim,

Ali,

Ahmed

et al. 2024

Egyptian Journal of Artificial Intelligence

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In this paper, a unique approach has been developed to detect drowning by using a chest area belt equipped with a pressure sensor to monitor the breathing rate of the person wearing the belt. Additionally, MPU6050 module has been used to measure the cumulative displacement to track the swimmer's movement. These sensors have been integrated with a Remotexy application and a GSM module to create an SMS message that alerts lifeguards when someone is in danger of drowning. The chest area belt is equipped with carbon resistors that are sensitive to pressure changes, allowing us to monitor the breathing rate of the person wearing the belt. By monitoring the breathing rate, we can detect when a swimmer is in distress and alert lifeguards to the potential drowning. To track the swimmer's movement, an MPU6050 has been used, which is a motion sensor that measures the cumulative displacement of the person wearing the belt. This data is then integrated with a Remotexy application and a GSM module to create an SMS message that is sent to lifeguards when someone is in danger of drowning.

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“…Similarly, to the previous two-module designs, if a heart rate reading above the threshold values is recorded, an alert is sent to the receiver. A three-module system to detect drowning is presented by Ramdhan et al [18]. The system is split into monitoring, access point, and drowning detection segments.…”

Section: Related Workmentioning

confidence: 99%

A Smart Multi-Sensor Device to Detect Distress in Swimmers

Jalalifar

Kashizadeh

Mahmood

et al. 2022

Sensors

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Drowning is considered amongst the top 10 causes of unintentional death, according to the World Health Organization (WHO). Therefore, anti-drowning systems that can save lives by preventing and detecting drowning are much needed. This paper proposes a robust and waterproof sensor-based device to detect distress in swimmers at varying depths and different types of water environments. The proposed device comprises four main components, including heart rate, blood oxygen level, movement, and depth sensors. Although these sensors were designed to work together to boost the system’s capability as an anti-drowning device, each could operate independently. The sensors were able to determine the heart rate to an accuracy of 1 beat per minute (BPM), 1% SpO2, the acceleration with adjustable sensitivities of ±2 g, ±4 g, ±8 g, and ±16 g, and the depth up to 12.8 m. The data obtained from the sensors were sent to a microcontroller that compared the input data to adjustable threshold values to detect dangerous situations. Being in hazardous situations for more than a specific time activated the alarming system. Based on the comparison made in the program and measuring the time of submersion, a message indicating drowning or safe was sent to a lifeguard to continuously monitor the swimmer’ condition via Wi-Fi to an IP address reachable by a mobile phone or laptop. It is also possible to continuously monitor the sensor outputs on the device’s display or the connected mobile phone or laptop. The threshold values could be adjusted based on biometric parameters such as swimming conditions (swimming pool, beach, depth, etc.) and swimmers health and conditions. The functionality of the proposed device was thoroughly tested over a wide range of parameters and under different conditions, both in air and underwater. It was demonstrated that the device could detect a range of potentially hazardous aquatic situations. This work will pave the way for developing an effective drowning sensing system that could save tens of thousands of lives across the globe every year.

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An Early Drowning Detection System for Internet of Things (IoT) Applications

Cited by 13 publications

References 11 publications

Enhancing Water Safety: Exploring Recent Technological Approaches for Drowning Detection

Enhancing Water Safety: Exploring Recent Technological Approaches for Drowning Detection

A Low-Cost Approach for Drowning Detection and Alertness

A Smart Multi-Sensor Device to Detect Distress in Swimmers

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