Assessment of Radiation-Induced Soft Error on Unmanned Surface Vehicles

The presence of unmanned surface vehicles (USVs) is increasingly frequent in lakes and water reservoirs, performing tasks such as monitoring water quality or delivering goods across the water. However, the emergence of such autonomous vessels raises concerns in terms of safety for people sharing the...

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Vydané v:	IEEE transactions on nuclear science Ročník 71; číslo 8; s. 1589 - 1597
Hlavní autori:	Fleck, Marcos A., Pereira, Elisa G., Gava, Jonas F., Silva, Henrique B., Moraes, Fernando G., Calazans, Ney L.V., Meneguzzi, Felipe, Bastos, Rodrigo P., Reis, Ricardo A. L., Ost, Luciano, Garibotti, Rafael
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.08.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Institute of Electrical and Electronics Engineers
Predmet:	Algorithms Autonomous vehicles Engineering Sciences Feature extraction Floating bodies Inference algorithms Lakes Micro and nanotechnologies Microelectronics Neutron radiation Neutrons Object recognition object recognition algorithm Obstacle avoidance Radiation Radiation effects Reliability Safety Soft errors Strategy Surface vehicles uncrewed surface vessels unmanned surface vehicles (USVs) Unmanned vehicles Vessels Water monitoring Water quality YOLO Neutron radiation Uncrewed Surface Vessels Unmanned Surface Vehicles USVs USVs Object Recognition Algorithm
ISSN:	0018-9499, 1558-1578
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Abstract	The presence of unmanned surface vehicles (USVs) is increasingly frequent in lakes and water reservoirs, performing tasks such as monitoring water quality or delivering goods across the water. However, the emergence of such autonomous vessels raises concerns in terms of safety for people sharing the same environment and the risk of collisions with fixed structures and floating bodies, including other vessels. Therefore, the detection of obstacles and their reliable operation becomes primary in USVs. This work explores the effects caused by neutron radiation on an object detection algorithm tailored for USVs. Results report 77 silent data corruption (SDC)-induced failures, showing that radiation-induced soft errors contribute to missed and false detection of, respectively, existing and nonexistent objects. Furthermore, results suggest that object detection algorithms running with the multicore strategy (<inline-formula> <tex-math notation="LaTeX">\text {FIT}_{\text {SDC}} </tex-math></inline-formula> rate of 34.3 at sea level and 308.6 at Lake Titicaca) exhibit a 16.4% greater resilience to SDCs compared to the single-core strategy.
AbstractList	The presence of Unmanned Surface Vehicles (USVs) is increasingly frequent on lakes and water reservoirs, performing tasks such as monitoring water quality or delivering goods across the water. However, the emergence of such autonomous vessels raises concerns in terms of safety for people sharing the same environment and the risk of collisions with fixed structures and floating bodies, including other vessels. Therefore, the detection of obstacles and its reliable operation become primary in USVs. This work explores the effects caused by neutron radiation on an object detection algorithm tailored for USVs. Results report 77 silent data corruption (SDC)-induced failures, showing that radiation-induced soft errors contribute to missed and false detection of respectively existing and non-existent objects. Furthermore, results suggest that object detection algorithms running with the multi-core strategy ( FITSDC rate of 34.3 at sea level and 308.6 at Lake Titicaca) exhibit a 16.4% greater resilience to SDCs compared to the single-core strategy. The presence of unmanned surface vehicles (USVs) is increasingly frequent in lakes and water reservoirs, performing tasks such as monitoring water quality or delivering goods across the water. However, the emergence of such autonomous vessels raises concerns in terms of safety for people sharing the same environment and the risk of collisions with fixed structures and floating bodies, including other vessels. Therefore, the detection of obstacles and their reliable operation becomes primary in USVs. This work explores the effects caused by neutron radiation on an object detection algorithm tailored for USVs. Results report 77 silent data corruption (SDC)-induced failures, showing that radiation-induced soft errors contribute to missed and false detection of, respectively, existing and nonexistent objects. Furthermore, results suggest that object detection algorithms running with the multicore strategy ([Formula Omitted] rate of 34.3 at sea level and 308.6 at Lake Titicaca) exhibit a 16.4% greater resilience to SDCs compared to the single-core strategy. The presence of unmanned surface vehicles (USVs) is increasingly frequent in lakes and water reservoirs, performing tasks such as monitoring water quality or delivering goods across the water. However, the emergence of such autonomous vessels raises concerns in terms of safety for people sharing the same environment and the risk of collisions with fixed structures and floating bodies, including other vessels. Therefore, the detection of obstacles and their reliable operation becomes primary in USVs. This work explores the effects caused by neutron radiation on an object detection algorithm tailored for USVs. Results report 77 silent data corruption (SDC)-induced failures, showing that radiation-induced soft errors contribute to missed and false detection of, respectively, existing and nonexistent objects. Furthermore, results suggest that object detection algorithms running with the multicore strategy (<inline-formula> <tex-math notation="LaTeX">\text {FIT}_{\text {SDC}} </tex-math></inline-formula> rate of 34.3 at sea level and 308.6 at Lake Titicaca) exhibit a 16.4% greater resilience to SDCs compared to the single-core strategy.
Author	Fleck, Marcos A. Meneguzzi, Felipe Garibotti, Rafael Moraes, Fernando G. Reis, Ricardo A. L. Bastos, Rodrigo P. Calazans, Ney L.V. Silva, Henrique B. Ost, Luciano Pereira, Elisa G. Gava, Jonas F.
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Snippet	The presence of unmanned surface vehicles (USVs) is increasingly frequent in lakes and water reservoirs, performing tasks such as monitoring water quality or... The presence of Unmanned Surface Vehicles (USVs) is increasingly frequent on lakes and water reservoirs, performing tasks such as monitoring water quality or...
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SubjectTerms	Algorithms Autonomous vehicles Engineering Sciences Feature extraction Floating bodies Inference algorithms Lakes Micro and nanotechnologies Microelectronics Neutron radiation Neutrons Object recognition object recognition algorithm Obstacle avoidance Radiation Radiation effects Reliability Safety Soft errors Strategy Surface vehicles uncrewed surface vessels unmanned surface vehicles (USVs) Unmanned vehicles Vessels Water monitoring Water quality YOLO
Title	Assessment of Radiation-Induced Soft Error on Unmanned Surface Vehicles
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