TY - GEN
T1 - Real-Time Train Speed Prediction using Ip-Camera Based on Time Difference
AU - Pramunanto, Eko
AU - Yuniarno, Eko Mulyanto
AU - Putrawardana, Arifandi
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/11/17
Y1 - 2020/11/17
N2 - In 2014, PT. KAI has added Remote locomotive speed detection which is useful for increasing travel safety. The indicator will turn red if the speed of the monitored train exceeds the predetermined speed. This monitoring can only focus on overspeed only, while it needs to be given specifically at places such as train intersections, and stops. In This, a security system will be made for Monitoring Train Speed at certain points, such as train gates, intersections, and stations. In this case, the Real-Time Train Speed Prediction using IP-Camera is an effective and affordable solution to be applied. This system uses IP-camera to capture the input image and an SBC to process the image to produce the output direction and speed data. The Camera is used to detect the train, then the speed is calculated based on the different frames in the image input.
AB - In 2014, PT. KAI has added Remote locomotive speed detection which is useful for increasing travel safety. The indicator will turn red if the speed of the monitored train exceeds the predetermined speed. This monitoring can only focus on overspeed only, while it needs to be given specifically at places such as train intersections, and stops. In This, a security system will be made for Monitoring Train Speed at certain points, such as train gates, intersections, and stations. In this case, the Real-Time Train Speed Prediction using IP-Camera is an effective and affordable solution to be applied. This system uses IP-camera to capture the input image and an SBC to process the image to produce the output direction and speed data. The Camera is used to detect the train, then the speed is calculated based on the different frames in the image input.
KW - Computer Vision
KW - OpenCV
KW - Speed Detection
UR - http://www.scopus.com/inward/record.url?scp=85099643028&partnerID=8YFLogxK
U2 - 10.1109/CENIM51130.2020.9298004
DO - 10.1109/CENIM51130.2020.9298004
M3 - Conference contribution
AN - SCOPUS:85099643028
T3 - CENIM 2020 - Proceeding: International Conference on Computer Engineering, Network, and Intelligent Multimedia 2020
SP - 445
EP - 450
BT - CENIM 2020 - Proceeding
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2020
Y2 - 17 November 2020 through 18 November 2020
ER -