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Modeling and Optimization for Irriga...

Winkler, Daniel A.

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Modeling and Optimization for Irrigation Control Using Wireless Sensor Networks.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Modeling and Optimization for Irrigation Control Using Wireless Sensor Networks./
Author:	Winkler, Daniel A.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	229 p.
Notes:	Source: Dissertations Abstracts International, Volume: 81-04, Section: B.
Contained By:	Dissertations Abstracts International81-04B.
Subject:	Computer science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13884589
ISBN:	9781085772181

Modeling and Optimization for Irrigation Control Using Wireless Sensor Networks.
Winkler, Daniel A.

Modeling and Optimization for Irrigation Control Using Wireless Sensor Networks. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 229 p.

Source: Dissertations Abstracts International, Volume: 81-04, Section: B.

Thesis (Ph.D.)--University of California, Merced, 2019.

This item must not be sold to any third party vendors.

Lawns, also known as turf, cover an estimated 128,000 square kilometers in North America, consuming an estimated 7 billion gallons of freshwater each day. Despite recent developments in irrigation control and sprinkler technology, state-of-the-art irrigation systems are unable to consider localized water requirements across the irrigation system and deliver localized control, preventing efficient irrigation. Inspired by preliminary results in simulation, we introduce a distributed irrigation controller, allowing us to sense moisture data across the space, actuate each sprinkler independently, and perform computation in a distributed way. To efficiently schedule irrigation for these distributed devices, we introduce modeling techniques allowing us to predict future water movement through the space caused by runoff, leaching, and weather effects that will affect the moisture in the system. These models are then used as constraints in optimization to choose schedules for the distributed valves that minimize system water consumption while maintaining optimal plant health. Finally, we show through extensive deployment side by side with state-of-the-art control strategies that our proposed systems are capable of providing significant water savings while simultaneously providing a higher quality of service to the turf compared to the baselines. Furthermore, we find that through clever system design we can achieve a perpetual system lifetime and virtually eliminate manual system configuration requirements, allowing us to bridge the technology gap to the end user to vastly improve system adoptability. In this way, we demonstrate the feasibility of wireless sensor use in turf irrigation systems.

ISBN: 9781085772181Subjects--Topical Terms:

523869
Computer science.
Subjects--Index Terms:

Lawns

Modeling and Optimization for Irrigation Control Using Wireless Sensor Networks.
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245 1 0 $a Modeling and Optimization for Irrigation Control Using Wireless Sensor Networks.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2019
300 $a 229 p.
500 $a Source: Dissertations Abstracts International, Volume: 81-04, Section: B.
500 $a Advisor: Cerpa, Alberto E.
502 $a Thesis (Ph.D.)--University of California, Merced, 2019.
506 $a This item must not be sold to any third party vendors.
520 $a Lawns, also known as turf, cover an estimated 128,000 square kilometers in North America, consuming an estimated 7 billion gallons of freshwater each day. Despite recent developments in irrigation control and sprinkler technology, state-of-the-art irrigation systems are unable to consider localized water requirements across the irrigation system and deliver localized control, preventing efficient irrigation. Inspired by preliminary results in simulation, we introduce a distributed irrigation controller, allowing us to sense moisture data across the space, actuate each sprinkler independently, and perform computation in a distributed way. To efficiently schedule irrigation for these distributed devices, we introduce modeling techniques allowing us to predict future water movement through the space caused by runoff, leaching, and weather effects that will affect the moisture in the system. These models are then used as constraints in optimization to choose schedules for the distributed valves that minimize system water consumption while maintaining optimal plant health. Finally, we show through extensive deployment side by side with state-of-the-art control strategies that our proposed systems are capable of providing significant water savings while simultaneously providing a higher quality of service to the turf compared to the baselines. Furthermore, we find that through clever system design we can achieve a perpetual system lifetime and virtually eliminate manual system configuration requirements, allowing us to bridge the technology gap to the end user to vastly improve system adoptability. In this way, we demonstrate the feasibility of wireless sensor use in turf irrigation systems.
590 $a School code: 1660.
650 4 $a Computer science. $3 523869
650 4 $a Water resources management. $3 794747
653 $a Lawns
653 $a Irrigation control
653 $a Wireless sensors
653 $a Turf irrigation systems
690 $a 0984
690 $a 0595
710 2 $a University of California, Merced. $b Electrical Engineering and Computer Science. $3 2095014
773 0 $t Dissertations Abstracts International $g 81-04B.
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791 $a Ph.D.
792 $a 2019
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13884589