Abstract
Collision between ships and icebergs is a major problem in glacial area, where large to small icebergs becomes a threat to cargo ships, tankers, fishing ships etc. In this paper, we have devised a new approach for the detection of icebergs and movement of ships to predict their probability of collision. In this proposed work, an adaptive method is used to detect the presence of icebergs and the velocity of ships, followed by integrating the obtained data and applying the Bayesian algorithm we have successfully computed the collision probability. This work exhibits effective results against reduced visibility due to fog. Besides, we have acquired all the foreground authentic data from valid resources. So, the results will help in marking the safe and unsafe zones in the form of clusters by using DBSCAN algorithm.
Keywords
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Khan, A.A.: Why would sea-level rise for global warming and polar ice-melt, China University of Geosciences (Beijing and Peking University), Elsevier B.V. http://doi.org/10.1016/j.jsf.2018.01.008
Li, Y., Han, J., Yang. J.: Clustering moving objects, Department of Computer Science University of Illinois UrbanaChampaign. ACM (2004). 1-58113-888-1/04/0008
Wesche, C., Dierking, W.: From ice shelves to icebergs: classification of calving fronts, iceberg monitoring and drift simulation. In: 2014 IEEE Geoscience and Remote Sensing Symposium (2014). https://doi.org/10.1109/igarss.2014.6946410
Tiago, A.M., Silva, G.R.B.: Computer-based identification and tracking of Antarctic icebergs in SAR images, Department Street of Geography, Sheffield S10 2TN UK. Elsevier http://doi.org/10.1016/j.rse.2004.10.002
Phung, S.L., Bouzerdoum, A.: Matlab library for convolutional neural networks (2009)
Zhang, M.-L., Pena, J.M., Robles, V.: Feature selection for multi-label naive Bayes classification. Inf. Sci. 179(19), 3218–3229 (2009)
Soman, K.P., Diwakar, S., Ajay, V.: Insight into data mining. PHI Publication (2009)
http://www.ccg-gcc.gc.ca/Icebreaking/Ice-Navigation-Canadian-Waters/Navigation-in-ice-covered-waters
Mittal, M., Goyal, L.M., Hemanth, D.J., Sethi, J.K.: Clustering approaches for high-dimensional databases: a review. WIREs Data Min. Knowl. Discov. (2019). John Wiley & Sons. https://doi.org/10.1002/widm.1300
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Zishan Ali, S., Makhija, M., Choudhary, D., Singh, H. (2019). An Efficient and Adaptive Method for Collision Probability of Ships, Icebergs Using CNN and DBSCAN Clustering Algorithm. In: Somani, A., Ramakrishna, S., Chaudhary, A., Choudhary, C., Agarwal, B. (eds) Emerging Technologies in Computer Engineering: Microservices in Big Data Analytics. ICETCE 2019. Communications in Computer and Information Science, vol 985. Springer, Singapore. https://doi.org/10.1007/978-981-13-8300-7_3
Download citation
DOI: https://doi.org/10.1007/978-981-13-8300-7_3
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-8299-4
Online ISBN: 978-981-13-8300-7
eBook Packages: Computer ScienceComputer Science (R0)