MtDetector
Chun-Xun Lin, Tsung‐Wei Huang, Guannan Guo, Martin D. F. Wong · 2018
In this paper, we present MtDetector, a high performance marine traffic detector that can predict the destination and the arrival time of travelling vessels. MtDetector accepts streaming data reported by the moving vessels and generates continuous predictions of the arrival port and arrival time for those vessels. To predict the destination for a ship, MtDetector builds a neural network for every port and infers the arrival port for vessels based on their departure port. For the arrival time prediction, we derive informative features from training data and apply Deep Neural Network (DNN) to estimate the traveling time. MtDetector is built on top of DtCraft [1,2], a high-performance distributed execution engine for stream programming. By utilizing the task-based parallelism in DtCraft, MtDetector can process multiple predictions concurrently to achieve high throughput and low latency.