Development Of Coordinates Based Cnnshortestpath Algorithm For The Prediction Of The Uav Travel Path Based On The Drone Node Dataset – An Alpha Defensive Path Prediction

Authors

  • Dr. Moiz Abdul Hussain, Tejal Kharche

DOI:

https://doi.org/10.47750/pnr.2023.14.03.184

Abstract

Today is the era of ultra-age technology and practices for the betterment of the society. Drone is the Unmanned Aerial Vehicle (UAV), which needs a path planning to reach up to the target. There are two basic modes for use of drone in case of military/surveillance: first is attack mode and defensive mode. Hence, this paper focuses on defensive mode as a scope of the proposed study. This paper provides significance of drone surveillance, a new artificial intelligence strategy to develop a predictive model based on the path planning. Further, based on the drone dataset, the UAV travel graph can be predicted and tested with a recursive machine learning algorithm. This strategy can be clubbed as an image path using deep learning algorithm also but to ensure the graph-based training and testing, the proposed research will use CNN algorithm for comparative analysis of simulated path’s plan coordinates. This further can be developed as a human-machine interface module.

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Published

— Updated on 2023-02-01

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Articles

How to Cite

Development Of Coordinates Based Cnnshortestpath Algorithm For The Prediction Of The Uav Travel Path Based On The Drone Node Dataset – An Alpha Defensive Path Prediction. (2023). Journal of Pharmaceutical Negative Results, 1383-1387. https://doi.org/10.47750/pnr.2023.14.03.184