Digital Twin Sluice Management System
Plough the waves Team
Background & SignificanceAlgorithms

Backbone Feature
In recent years, the occurrence of water traffic accidents is common, including the collision of twoReduce
Regression Prediction Network
Extraction Network
ships, capsizing and other phenomena, the main reasons are insufficient surface supervision, large
FillPredictive Feature
ship flow, improper operation of the driver, and the water is not calm so that the ship deviates
Hourglass-104
OffsetSize
Map
Key Point Thermodynamic
Original ShipDLA-34
from the course etc. To improve the safety of water navigation and facilitate ship management, we
Input Ship Image
Map Prediction
Prediction
128 X 128
Prediction
Image
ResDeconv-50
512 X 512established the digital twin sluice management system according to the real-time scenario to1920 X 1080
Centermonitor the running state of the water surface in real-time, to decrease the occurrence of water 1. Ship Tracking Algorithm: This does the real-time
point
traffic accidents, which has great significance for the future water surface management.
acquisition of ship ID and its location. It can detect
Deterthe size and speed of ships based on changes in Heat map Mination
the position and size of detection boxes inFill128
x128
different frames. Each ship detected will be placed
Digital twin sluice management system uses algorithms such as ship tracking, ship license
in the database for detecting the number of ships.
recognition and ship classification to build twin sluice gates in UC-win/Road software and importrich ship models to twinned ship operating status in real scenarios, and monitor the operating 2. Ship Plate Recognition Algorithm: This includes a multilingual
status, performance and operating parameters through a large visual screen. At the same time, inrecognition model and supports complex ship nameplateorder to ensure safety, ship will display warning information on large screen to remind the driver.
recognition. Also Supports dynamic and static identification.

System Architecture & Algorithm

Ship Classification
Algorithm

Real Sluice Gate Scene

Algorithm Development

Archive Database

Vessel TrafficStatistics

Yaw Warning

Ship License CategoryInformation

OverspeedWarning

Visualize the web screen

We use different types of algorithms to get different types of boat information The paddleOCRalgorithm identifies the boat number for license information. The EfficientNet algorithm to classify
ships category. The yolov5 algorithm to track the boat position. The results of each algorithm are
saved into the MySQL database. The UC-win/Road is connected with the database through
ODBC+ADO. In order to access all the algorithm results, at first user needs to enter the valid
username and password of the database and run the desired scenario. Then the user can see theship information displayed on the large screen, including the boat's license plate, the class of theboat and the time the boat passed the gate. When the speed of the ship is detected, the console
will sound an alarm to remind the driver to slow down.

CONVSlice

CONV

Input An Image

Decoder

LSTM

LSTM

LSTM

LSTM

LSTM

LSTM

LSTM

LSTM

LSTM

Output TheContents Of
Words In TheImage“Forum8-2398”

Convolutiona
l Module

3. Ship Classification Algorithm: Thisalgorithm network has the dual
advantages of network size andAttention
recognition accuracy and can complete Moduleclassification tasks in almost real-time.

Global Feature
Extraction
Key FeatureExtraction
Key Feature
Extraction
Key Feature
Extraction

Angel Navigation

Fully Connected Layer

Ship Plate Recognition
Algorithm

Feature extraction
process

Encoder
LSTM

Feature Fusion

Current Time

Ship Tracking Algorithms

Information
Bulletins

Classificati
on Results