TY - GEN
T1 - Low-Size and Cost Acoustic Buoy for Autonomous Vessel Detection
AU - Sedunov, Alexander
AU - Francis, Christopher
AU - Salloum, Hady
AU - Sutin, Alexander
AU - Sedunov, Nikolay
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Achieving maritime domain awareness through the deployment of many low-cost, low-power sensors to monitor large ocean areas has become an international trend [1], [2], an approach known as 'Ocean of Things' (OoT). The STAR Center at Stevens Institute of Technology is currently developing a sensor contained in a small, rapidly deployable 'smart' buoy for automated detection of vessels by their underwater acoustic signatures. Designed with commercial off-the-shelf (COTS) components and materials, multiple such buoys can work together to form a large, distributed sensor network, periodically communicating data to a command center for analysis. Marine-traffic monitoring is of particular interest in areas where small-boat traffic is a security concern, but many existing systems for detecting such vessels can be difficult to deploy. The buoy is based on in-house manufactured hydrophones. Processing is performed on an ARM Cortex-M7 microcontroller. Methods were developed based on numerous past data collections by the Stevens Institute of Technology.
AB - Achieving maritime domain awareness through the deployment of many low-cost, low-power sensors to monitor large ocean areas has become an international trend [1], [2], an approach known as 'Ocean of Things' (OoT). The STAR Center at Stevens Institute of Technology is currently developing a sensor contained in a small, rapidly deployable 'smart' buoy for automated detection of vessels by their underwater acoustic signatures. Designed with commercial off-the-shelf (COTS) components and materials, multiple such buoys can work together to form a large, distributed sensor network, periodically communicating data to a command center for analysis. Marine-traffic monitoring is of particular interest in areas where small-boat traffic is a security concern, but many existing systems for detecting such vessels can be difficult to deploy. The buoy is based on in-house manufactured hydrophones. Processing is performed on an ARM Cortex-M7 microcontroller. Methods were developed based on numerous past data collections by the Stevens Institute of Technology.
KW - acoustics
KW - buoy
KW - maritime surveillance
KW - remote sensing
KW - vessel tracking
UR - http://www.scopus.com/inward/record.url?scp=85148415354&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85148415354&partnerID=8YFLogxK
U2 - 10.1109/HST56032.2022.10025447
DO - 10.1109/HST56032.2022.10025447
M3 - Conference contribution
AN - SCOPUS:85148415354
T3 - 2022 IEEE International Symposium on Technologies for Homeland Security, HST 2022
BT - 2022 IEEE International Symposium on Technologies for Homeland Security, HST 2022
T2 - 2022 IEEE International Symposium on Technologies for Homeland Security, HST 2022
Y2 - 14 November 2022 through 15 November 2022
ER -