An Improved Detection Method of Human Target at Sea Based on Yolov3

Li, Dongjin; Liu, Yu; Wang, Jin; Zhang, Rufei; Jiang, Feng; Niu, Fu

doi:10.1109/iccece51280.2021.9342056

Cited by 8 publications

(2 citation statements)

References 5 publications

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“…Studies have successfully distinguished people on land from those swimming, using trained vision systems [ 40 ]. Typically, search and rescue (SAR) applications motivate research into detecting swimmers, such as autonomously locating lost people at great distances [ 33 ].…”

Section: Image Processing Techniques For Drowning Detectionmentioning

confidence: 99%

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: Image Processing 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

“…By leveraging the capabilities of the MPU6050 sensor and a wearable device, we will get into every detail about their components in the upcoming sections. We can develop innovative solutions to prevent drowning and keep people safe in and around water [30][31][32][33][34].…”

Section: Proposed Systemmentioning

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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Improved YOLOv7 Small Object Detection Algorithm for Seaside Aerial Images

Yu,

Jia

2024

Communications in Computer and Information Science

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An Improved Detection Method of Human Target at Sea Based on Yolov3

Cited by 8 publications

References 5 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

Improved YOLOv7 Small Object Detection Algorithm for Seaside Aerial Images

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