Maritime surveillance in the Intracoastal Waterway using networked underwater acoustic sensors integrated with a regional command center

Rice, Jeffrey S.; Wilson, Gary R.; Barlett, Marti; Smith, Justin O.; Chen, Teddy; Fletcher, C.L.; Creber, Bob; Rasheed, Zeeshan; Taylor, Geoff; Haering, Niels

doi:10.1109/wssc.2010.5730277

Cited by 10 publications

(4 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Notably, research studies demonstrate that divers, unmanned undersea vehicles, and drones can be detected with these systems [30,48]. Although the range varies depending on the technical specifications of the acoustic sensors, the area to be listened to, the location where it is deployed, and the characteristics of the region, it is stated that surface contact detection can be extended up to 600 m with acoustic sensors [48,49]. The SafeShore project relies primarily on data collected from coastal acoustic systems as its principal information source.…”

Section: Coastal Acoustic Systems Alternativementioning

confidence: 99%

Safety–Security Analysis of Maritime Surveillance Systems in Critical Marine Areas

Şengül,

Yılmaz,

Uğurlu

2023

Sustainability

View full text Add to dashboard Cite

In today’s world, wherein more than 80% of world trade is carried out by maritime routes, the safety and security of the seas where this trade takes place is of vast importance for nations and the international community. For this reason, ensuring the sustainable safety and security of the seas has become an integral part of the mission of all maritime-related entities. Using big data extracted from the seas and maritime activities into meaningful information with artificial intelligence applications and developing applications that can be used in maritime surveillance will be of great importance for augmenting maritime safety and security. In this article, data sources which can be used by a maritime surveillance system based on big data and artificial intelligence technologies and which can be established around sensitive sea areas and critical coastal facilities, are identified and a model proposal using this maritime big data is put forward.

show abstract

Section: Coastal Acoustic Systems Alternativementioning

confidence: 99%

Safety–Security Analysis of Maritime Surveillance Systems in Critical Marine Areas

Şengül,

Yılmaz,

Uğurlu

2023

Sustainability

View full text Add to dashboard Cite

show abstract

“…However, it is difficult for radar-based surveillance to detect nonmetallic objects or objects with low reflectivity in small fishing boats with six to eight passengers; furthermore, it is difficult to obtain information regarding the shape or size of the object [7]. Another method of maritime surveillance employs acoustic sensors, which can identify the location and type of an object by the object's sound characteristics [8,9]. However, acoustic sensors are vulnerable to interference from wind, waves, and other background noise, and their accuracy is low due to noise generated by the sensor itself.…”

Section: Introductionmentioning

confidence: 99%

MODAN: Multifocal Object Detection Associative Network for Maritime Horizon Surveillance

Yoon,

Jalal,

Cho

2023

JMSE

View full text Add to dashboard Cite

In maritime surveillance systems, object detection plays a crucial role in ensuring the security of nearby waters by tracking the movement of various objects, such as ships and aircrafts, that are found at sea, detecting illegal activities and preemptively countering or predicting potential risks. Using vision sensors such as cameras to monitor the sea can help to identify the shape, size, and color of objects, enabling the precise analysis of maritime situations. Additionally, vision sensors can monitor or track small ships that may escape radar detection. However, objects located at considerable distances from vision sensors have low resolution and are small in size, rendering their detection difficult. This paper proposes a multifocal object detection associative network (MODAN) to overcome these vulnerabilities and provide stable maritime surveillance. First, it searches for the horizon using color quantization based on K-means; then, it selects and partitions the region of interest (ROI) around the horizon using the ROI selector. The original image and ROI image, converted to high resolution through the Super-Resolution Convolutional Neural Network (SRCNN), are then passed to the near-field and far-field detectors, respectively, for object detection. The weighted box fusion removes duplicate detected objects and estimates the optimal object. The proposed network is more stable and efficient in detecting distant objects than existing single-object detection models. Through performance evaluations, the proposed network exhibited an average precision surpassing that of the existing single-object detection models by more than 7%, and the false detection rate was reduced by 59% compared to similar multifocal-based state-of-the-art detection methods.

show abstract

“…WSN has been applied in many applications [8], such as habitat monitoring [9], Point of Interest Building monitoring [10], pipeline monitoring [11], smart agriculture [12], and smart electrical grid [13]. Researchers, also, have extended the concept of land WSN into marine sensor network [14,15]. Because RF signals do not work under water, acoustic signals are used for communication.…”

Section: Introductionmentioning

confidence: 99%

Advanced Border Intrusion Detection and Surveillance Using Wireless Sensor Network Technology

Felemban¹

2013

IJCNS

View full text Add to dashboard Cite

Wireless Sensor Network (WSN) has been emerging in the last decade as a powerful tool for connecting physical and digital world. WSN has been used in many applications such habitat monitoring, building monitoring, smart grid and pipeline monitoring. In addition, few researchers have been experimenting with WSN in many mission-critical applications such as military applications. This paper surveys the literature for experimenting work done in border surveillance and intrusion detection using the technology of WSN. The potential benefits of using WSN in border surveillance are huge; however, up to our knowledge very few attempts of solving many critical issues about this application could be found in the literature.

show abstract

Maritime surveillance in the Intracoastal Waterway using networked underwater acoustic sensors integrated with a regional command center

Cited by 10 publications

References 3 publications

Safety–Security Analysis of Maritime Surveillance Systems in Critical Marine Areas

Safety–Security Analysis of Maritime Surveillance Systems in Critical Marine Areas

MODAN: Multifocal Object Detection Associative Network for Maritime Horizon Surveillance

Advanced Border Intrusion Detection and Surveillance Using Wireless Sensor Network Technology

Contact Info

Product

Resources

About