Design and Analysis of Cost-Efficient Sensor Deployment for Tracking Small UAS with Agent-Based Modeling
Recently, commercial unmanned aerial systems (UAS) have gained popularity. However, these UAS are potential threats to people in terms of safety in public places, such as public parks or stadiums. To reduce such threats, we consider a design, modeling, and evaluation of a cost-efficient sensor syste...
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doaj-b3c436feaa5a475a97fd7135189f1a2a2020-11-24T22:50:02ZengMDPI AGSensors1424-82202016-04-0116457510.3390/s16040575s16040575Design and Analysis of Cost-Efficient Sensor Deployment for Tracking Small UAS with Agent-Based ModelingSangmi Shin0Seongha Park1Yongho Kim2Eric T. Matson3M2M Laboratory, Computer and Information Technology, Purdue University, West Lafayette, IN 47907, USAM2M Laboratory, Computer and Information Technology, Purdue University, West Lafayette, IN 47907, USAM2M Laboratory, Computer and Information Technology, Purdue University, West Lafayette, IN 47907, USAM2M Laboratory, Computer and Information Technology, Purdue University, West Lafayette, IN 47907, USARecently, commercial unmanned aerial systems (UAS) have gained popularity. However, these UAS are potential threats to people in terms of safety in public places, such as public parks or stadiums. To reduce such threats, we consider a design, modeling, and evaluation of a cost-efficient sensor system that detects and tracks small UAS. In this research, we focus on discovering the best sensor deployments by simulating different types and numbers of sensors in a designated area, which provide reasonable detection rates at low costs. Also, the system should cover the crowded areas more thoroughly than vacant areas to reduce direct threats to people underneath. This research study utilized the Agent-Based Modeling (ABM) technique to model a system consisting of independent and heterogeneous agents that interact with each other. Our previous work presented the ability to apply ABM to analyze the sensor configurations with two types of radars in terms of cost-efficiency. The results from the ABM simulation provide a list of candidate configurations and deployments that can be referred to for applications in the real world environment.http://www.mdpi.com/1424-8220/16/4/575sensor deploymentagent-based modelingUAS trackingdistributed sensor network |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sangmi Shin Seongha Park Yongho Kim Eric T. Matson |
spellingShingle |
Sangmi Shin Seongha Park Yongho Kim Eric T. Matson Design and Analysis of Cost-Efficient Sensor Deployment for Tracking Small UAS with Agent-Based Modeling Sensors sensor deployment agent-based modeling UAS tracking distributed sensor network |
author_facet |
Sangmi Shin Seongha Park Yongho Kim Eric T. Matson |
author_sort |
Sangmi Shin |
title |
Design and Analysis of Cost-Efficient Sensor Deployment for Tracking Small UAS with Agent-Based Modeling |
title_short |
Design and Analysis of Cost-Efficient Sensor Deployment for Tracking Small UAS with Agent-Based Modeling |
title_full |
Design and Analysis of Cost-Efficient Sensor Deployment for Tracking Small UAS with Agent-Based Modeling |
title_fullStr |
Design and Analysis of Cost-Efficient Sensor Deployment for Tracking Small UAS with Agent-Based Modeling |
title_full_unstemmed |
Design and Analysis of Cost-Efficient Sensor Deployment for Tracking Small UAS with Agent-Based Modeling |
title_sort |
design and analysis of cost-efficient sensor deployment for tracking small uas with agent-based modeling |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2016-04-01 |
description |
Recently, commercial unmanned aerial systems (UAS) have gained popularity. However, these UAS are potential threats to people in terms of safety in public places, such as public parks or stadiums. To reduce such threats, we consider a design, modeling, and evaluation of a cost-efficient sensor system that detects and tracks small UAS. In this research, we focus on discovering the best sensor deployments by simulating different types and numbers of sensors in a designated area, which provide reasonable detection rates at low costs. Also, the system should cover the crowded areas more thoroughly than vacant areas to reduce direct threats to people underneath. This research study utilized the Agent-Based Modeling (ABM) technique to model a system consisting of independent and heterogeneous agents that interact with each other. Our previous work presented the ability to apply ABM to analyze the sensor configurations with two types of radars in terms of cost-efficiency. The results from the ABM simulation provide a list of candidate configurations and deployments that can be referred to for applications in the real world environment. |
topic |
sensor deployment agent-based modeling UAS tracking distributed sensor network |
url |
http://www.mdpi.com/1424-8220/16/4/575 |
work_keys_str_mv |
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