Semantic IoT: intelligent water management for efficient urban outdoor water conservation

Myers, Trina, Mohring, Karl, and Andersen, Trevor (2017) Semantic IoT: intelligent water management for efficient urban outdoor water conservation. In: Lecture Notes in Computer Science (10675), pp. 304-317. From: 7th Joint International Semantic Technology Conference JIST 2017, 10-12 November 2017, Gold Coast, QLD, Australia.

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Abstract

Water depletion is critical in the dry tropics due to drought, increased development and demographic or economic shifts. Although educational initiatives have improved urban indoor water-use, excessive outdoor wastage still occurs because in most urban areas residential users only have a biannual reading of quantity available to make informed or educated decisions on necessary or unnecessary consumption. For example, the average consumer will water lawns during a designated non-restricted time. The amount of water they use is determined arbitrarily (i.e., either by sight or by blocks of time). In many cases, water is wasted due to over saturation, automated sprinklers that cannot sense precipitation, poor placement of sprinkler direction, etc. Outdoor water use efficiency could be maximized if water flow was shut off when an area of lawn has had sufficient water based on a more intelligent monitoring system. This paper describes the development of an intelligent water management and information system that integrates real-time sensed data (soil moisture, etc) and Web-available information to make dynamic decisions on water release for lawns and fruit trees. The initial pilot-prototype combines Semantic Technologies with Internet of Things to decrease urban outdoor water-use and educate residents on best water usage strategies.

Item ID: 51581
Item Type: Conference Item (Research - E1)
ISBN: 978-3-319-70682-5
ISSN: 0302-9743
Keywords: semantic technologies, Internet of Things, water conservation
Additional Information:

JIST 2017 forms part of the Lecture Notes in Computer Science book series (LNCS, volume 10675).

Date Deposited: 26 Nov 2017 23:18
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080105 Expert Systems @ 100%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970108 Expanding Knowledge in the Information and Computing Sciences @ 100%
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