Paper Info
Title
Cost-Constrained Drone Presence Detection Through Smart Sound Processing
Abstract
Sometimes, drones lead to problems of invasion of privacy or access to restricted areas. Because of that, it is important to develop a system capable of detecting the presence of these vehicles in real time in environments where they could be used for malicious purposes. However, the computational cost associated to that system must be limited if it has to work in an autonomous way. In this manuscript an algorithm based on Smart Sound Processing techniques has been developed. Feature extraction, cost constrained feature selection and detection processes, typically implemented in pattern recognition systems, are applied. Results show that it is possible to detect the presence of drones with low cost feature subsets, where MFCCs and pitch are the most relevant ones.
Year
DOI
Venue
2019
10.5220/0007556007660772
ICPRAM: PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION APPLICATIONS AND METHODS
Keywords
Field
DocType
Drone Detection, Smart Sound Processing, Feature Extraction, Feature Selection, Evolutionary Computation, Cost Constraints
Computer vision,Computer science,Artificial intelligence,Drone,Audio signal processing,Machine learning
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
Joaquín García-Gómez100.34
Marta Bautista-Durán200.34
Roberto Gil-Pita37917.06
inma mohinoherranz492.71
Miguel Aguilar-Ortega500.34
César Clares-Crespo600.34