Devising Mobile Sensing and Actuation Infrastructure with Drones

Vast applications and services have been enabled as the number of mobile or sensing devices with communication capabilities has grown. However, managing the devices, integrating networks or combining services across different networks has become a new problem since each network is not directly conne...

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Main Authors: Mungyu Bae, Seungho Yoo, Jongtack Jung, Seongjoon Park, Kangho Kim, Joon Yeop Lee Kim, Hwangnam Kim
Format: Article
Language:English
Published: MDPI AG 2018-02-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/18/2/624
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author Mungyu Bae
Seungho Yoo
Jongtack Jung
Seongjoon Park
Kangho Kim
Joon Yeop Lee Kim
Hwangnam Kim
author_facet Mungyu Bae
Seungho Yoo
Jongtack Jung
Seongjoon Park
Kangho Kim
Joon Yeop Lee Kim
Hwangnam Kim
author_sort Mungyu Bae
collection DOAJ
description Vast applications and services have been enabled as the number of mobile or sensing devices with communication capabilities has grown. However, managing the devices, integrating networks or combining services across different networks has become a new problem since each network is not directly connected via back-end core networks or servers. The issue is and has been discussed especially in wireless sensor and actuator networks (WSAN). In such systems, sensors and actuators are tightly coupled, so when an independent WSAN needs to collaborate with other networks, it is difficult to adequately combine them into an integrated infrastructure. In this paper, we propose drone-as-a-gateway (DaaG), which uses drones as mobile gateways to interconnect isolated networks or combine independent services. Our system contains features that focus on the service being provided in the order of importance, different from an adaptive simple mobile sink system or delay-tolerant system. Our simulation results have shown that the proposed system is able to activate actuators in the order of importance of the service, which uses separate sensors’ data, and it consumes almost the same time in comparison with other path-planning algorithms. Moreover, we have implemented DaaG and presented results in a field test to show that it can enable large-scale on-demand deployment of sensing and actuation infrastructure or the Internet of Things (IoT).
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spelling doaj.art-c559dc168b2b42d7a22d3abf4f8f90cf2022-12-22T01:58:25ZengMDPI AGSensors1424-82202018-02-0118262410.3390/s18020624s18020624Devising Mobile Sensing and Actuation Infrastructure with DronesMungyu Bae0Seungho Yoo1Jongtack Jung2Seongjoon Park3Kangho Kim4Joon Yeop Lee Kim5Hwangnam Kim6School of Electrical Engineering, Korea University, Seoul 02841, KoreaSchool of Electrical Engineering, Korea University, Seoul 02841, KoreaSchool of Electrical Engineering, Korea University, Seoul 02841, KoreaSchool of Electrical Engineering, Korea University, Seoul 02841, KoreaSchool of Electrical Engineering, Korea University, Seoul 02841, KoreaSchool of Electrical Engineering, Korea University, Seoul 02841, KoreaSchool of Electrical Engineering, Korea University, Seoul 02841, KoreaVast applications and services have been enabled as the number of mobile or sensing devices with communication capabilities has grown. However, managing the devices, integrating networks or combining services across different networks has become a new problem since each network is not directly connected via back-end core networks or servers. The issue is and has been discussed especially in wireless sensor and actuator networks (WSAN). In such systems, sensors and actuators are tightly coupled, so when an independent WSAN needs to collaborate with other networks, it is difficult to adequately combine them into an integrated infrastructure. In this paper, we propose drone-as-a-gateway (DaaG), which uses drones as mobile gateways to interconnect isolated networks or combine independent services. Our system contains features that focus on the service being provided in the order of importance, different from an adaptive simple mobile sink system or delay-tolerant system. Our simulation results have shown that the proposed system is able to activate actuators in the order of importance of the service, which uses separate sensors’ data, and it consumes almost the same time in comparison with other path-planning algorithms. Moreover, we have implemented DaaG and presented results in a field test to show that it can enable large-scale on-demand deployment of sensing and actuation infrastructure or the Internet of Things (IoT).http://www.mdpi.com/1424-8220/18/2/624wireless sensor and actuator networksdrone networkconnectivityarchitectures and applications for the Internet of Thingsopportunistic and delay-tolerant networks
spellingShingle Mungyu Bae
Seungho Yoo
Jongtack Jung
Seongjoon Park
Kangho Kim
Joon Yeop Lee Kim
Hwangnam Kim
Devising Mobile Sensing and Actuation Infrastructure with Drones
Sensors
wireless sensor and actuator networks
drone network
connectivity
architectures and applications for the Internet of Things
opportunistic and delay-tolerant networks
title Devising Mobile Sensing and Actuation Infrastructure with Drones
title_full Devising Mobile Sensing and Actuation Infrastructure with Drones
title_fullStr Devising Mobile Sensing and Actuation Infrastructure with Drones
title_full_unstemmed Devising Mobile Sensing and Actuation Infrastructure with Drones
title_short Devising Mobile Sensing and Actuation Infrastructure with Drones
title_sort devising mobile sensing and actuation infrastructure with drones
topic wireless sensor and actuator networks
drone network
connectivity
architectures and applications for the Internet of Things
opportunistic and delay-tolerant networks
url http://www.mdpi.com/1424-8220/18/2/624
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