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Design and Analysis of Cost-Efficient Sensor Deployment for Tracking Small UAS with Agent-Based Modeling.

Sangmi Shin¹, Seongha Park², Yongho Kim³

¹M2M Laboratory, Computer and Information Technology, Purdue University, West Lafayette, IN 47907, USA. shin180@purdue.edu.

Sensors (Basel, Switzerland)

|April 26, 2016

Summary

This study developed a cost-efficient sensor system to detect and track small unmanned aerial systems (UAS) in public spaces. Agent-Based Modeling simulations optimized sensor deployment for enhanced safety in crowded areas.

Keywords:

UAS tracking agent-based modeling distributed sensor network sensor deployment

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Area of Science:

Engineering
Computer Science
Security Studies

Background:

Commercial unmanned aerial systems (UAS) are increasingly prevalent, posing safety risks in public venues like parks and stadiums.
Effective detection and tracking of small UAS are crucial for mitigating public safety threats.
Existing sensor systems may not be cost-efficient or optimally deployed for varied public area densities.

Purpose of the Study:

To design, model, and evaluate a cost-efficient sensor system for detecting and tracking small UAS.
To identify optimal sensor configurations and deployments that balance detection rates and cost.
To prioritize sensor coverage in crowded public areas for enhanced safety.

Main Methods:

Utilized Agent-Based Modeling (ABM) to simulate a system of interacting agents representing sensors and UAS.
Simulated various sensor types and quantities within a designated area to assess performance.
Evaluated cost-efficiency and detection capabilities of different sensor deployment strategies.

Main Results:

Identified optimal sensor configurations and deployment strategies for effective small UAS detection.
Demonstrated the ability of ABM to analyze sensor systems for cost-efficiency and coverage.
Generated a list of candidate sensor configurations and deployments for real-world application.

Conclusions:

The developed sensor system and deployment strategies offer a cost-efficient solution for mitigating UAS threats in public spaces.
Agent-Based Modeling is a viable technique for optimizing sensor network design in complex environments.
The findings provide practical guidance for implementing effective UAS detection and tracking systems in real-world scenarios.