Semantic IoT: Intelligent Water Management for Efficient Urban Outdoor Water Conservation

Myers, Trina; Mohring, Karl; Andersen, Trevor

doi:10.1007/978-3-319-70682-5_21

Cited by 12 publications

(6 citation statements)

References 13 publications

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“…The platform layer consists of mainly databases, data, and data preprocessing modules [20]. This layer accumulates and processes the data streams acquired from the low-level layer.…”

Section: Related Workmentioning

confidence: 99%

Interoperability Structure of Smart Water Conservancy Based on Internet of Things

Wang,

2024

International Journal of Distributed Sensor Networks

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Massive smart water conservancy object (WCO) need to be connected for real-time monitoring and control, which produces massive data. Unfortunately, heterogeneous data structures and semantics lead to low interoperability between WCO and management systems. To address this challenge, we propose a novel interoperability structure for a smart water conservancy system based on the Internet of Things (IoT), and the key design includes a smart WCO terminal, interoperability network, special interoperability protocol, WCO information model, and cloud platform. Universal terminal and network are the base of interoperability hardware, and special interoperability protocol and information model for interconnection of WCO are designed for smart water conservancy management system. WCO can be connected to a water conservancy Big Data processing cloud platform for interoperability applications. The application results demonstrate that our proposed WCO’s interoperability structure has obvious advantages than the general IoT at WCO interoperability. The interoperability protocol is reliable, the information model can ease interoperability and security, and the semantic dictionary is very rich and covers all semantic services of WCO.

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“…The platform layer consists of mainly databases, data, and data preprocessing modules [20]. This layer accumulates and processes the data streams acquired from the low-level layer.…”

Section: Related Workmentioning

confidence: 99%

Interoperability Structure of Smart Water Conservancy Based on Internet of Things

Wang,

2024

International Journal of Distributed Sensor Networks

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“…However, the investment in commercial sensors was very high. Myers et al [27] designed an intelligent water management and information system the integrates real-time sensed data (soil moisture, etc.) and Webavailable information to make dynamic decisions on water release for lawn and fruit trees.…”

Section: Related Workmentioning

confidence: 99%

Design and Calibration of Moisture Sensor Based on Electromagnetic Field Measurement for Irrigation Monitoring

et al. 2021

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Soil moisture control is crucial to assess irrigation efficiency in green areas and agriculture. In this paper, we propose the design and calibration of a sensor based on inductive coils and electromagnetic fields. The proposed prototypes should meet a series of requirements such as low power consumption, low relative error, and a high voltage difference between the minimum and maximum moisture. We tested different prototypes based on two copper coils divided into two different sets (P1–P15 and NP1–NP4). The prototypes have different characteristics: variations in the number and distribution of spires, existence or absence of casing, and copper wires with a diameter of 0.4 or 0.6 mm. In the first set of experiments carried out in commercial soil, the results showed that the best prototypes were P5, P8, and P9. These prototypes were used in different types of soils, and P8 was selected for the subsequent tests. We carried the second set of experiments using soil from an agricultural field. Based on the data gathered, mathematical models for the calibration of prototypes were obtained and verified. In some cases, two equations were used for different moisture intervals in a single prototype. According to the verification results, NP2 is the best prototype for monitoring the moisture in agricultural lands. It presented a difference in induced voltage of 1.8 V, at 500 kHz, between wet and dry soil with a maximum voltage of 5.12 V. The verification of the calibration determined that the calibration using two mathematical models offers better results, with an average absolute error of 2.1% of moisture.

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“…The work done by Joseph et al [11] focuses on IoT devices that assist in controlling and planning the utilization of the water. The work carried out by Myers et al [12] presents the improvement of intelligent water management and information technique to build active decision while releasing the water for the fruit trees and grasses. This study demonstrates the SWAMP-project using IoT based water conservation method for the correctness irrigation into the agriculture by Kamienski et al [13].…”

Section: Review Of Literaturementioning

confidence: 99%

Modeling of Smart Water Control Mechanism using IoT

Akanksha*

2019

IJITEE

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Abstract: The unexpected water demand has become a serious concern in the last few years. The increasing demand for water supply has posed a significant challenge for many countries around the world. Various factors, such as population growth, urbanization, and climate changes, have further exhausted water resources. Therefore, water conservation and natural resource management have become crucial factors for human survival. The proposed study presents the modeling of smart water control system based on IoT technology. The implementation of the proposed water control model is carried out using an analytical approach with cost-effective, functional modules using sensors and wireless communication system. The proposed smart water control mechanism is mainly designed for water distribution and monitoring application.

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Semantic IoT: Intelligent Water Management for Efficient Urban Outdoor Water Conservation

Cited by 12 publications

References 13 publications

Interoperability Structure of Smart Water Conservancy Based on Internet of Things

Interoperability Structure of Smart Water Conservancy Based on Internet of Things

Design and Calibration of Moisture Sensor Based on Electromagnetic Field Measurement for Irrigation Monitoring

Modeling of Smart Water Control Mechanism using IoT

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