Development of a Low-Power Smart Water Meter for Discharges in Indus Basin Irrigation Networks

Ahmad, Zahoor; Asad, Ehsan U.; Muhammad, Abubakr; Ahmad, Waqas; Anwar, Arif A.

doi:10.1007/978-3-642-41054-3_1

Cited by 20 publications

(22 citation statements)

References 9 publications

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“…In our field work, we used Ultra-Sonic range sensors [15]. These sensors were deployed (usually at bridges) at different lengths along the downstream channel.…”

Section: Methodsmentioning

confidence: 99%

“…In this paper, we present our complete system identification procedure, from experimental design to model validation, and we hope that our findings will help in building accurate models for controlled irrigation canals in Pakistan. The work reported in this paper runs in parallel to the efforts at CYPHYNETS Lab in Lahore University of Management Sciences, to build a scalable hydrometry infrastructure for the Indus basin canal network [9], [15], [16]. In particular, the data recordings have been obtained using smart sensors developed by the authors' group.…”

Section: Introductionmentioning

confidence: 99%

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System identification of Khaira distributory

Aleem

Khalid

Zaheer

et al. 2013

Inmic

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Water has become a scarce resource for agro-based economy of Pakistan. In this work, we derive channel models for regulation in irrigation canals using system identification techniques. System identification models are computationally inexpensive and accurate for simulating water profiles. We take inspiration from recent developments in control of large-scale irrigation networks and perform experimental identification of distributory irrigation channels in Pakistan. The channel models are estimated and validated on operational data from Khaira Distributory off BRB Link Canal, Lahore. Our results show that system identification techniques capture the efficacy of canal models appropriately and will play a vital role in building accurate models for controlled irrigation canals in Pakistan 1 .

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“…In our field work, we used Ultra-Sonic range sensors [15]. These sensors were deployed (usually at bridges) at different lengths along the downstream channel.…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

System identification of Khaira distributory

Aleem

Khalid

Zaheer

et al. 2013

Inmic

Self Cite

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“…Individuals or objects are created from the hierarchy of the class and contextual semantic information will be based on the data generated from wireless sensor network proposed in WaterGird [1]. Low power WSN for calculating the flow of water discharge in canal and watercourse is developed [21]. A. Ontological conceptualization of Disaster Management, Rehabilitation, and other Supporting authorities.…”

Section: Figure 2: a Sub Set Of The Ontology Is Show For Representationmentioning

confidence: 99%

WaterOnto: Ontology of Context-Aware Grid-Based Riverine Water Management System

Mughal

Shaikh

2017

SJCMS

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The management of riverine water always remains a big challenge, because the volatility of water flow creates hurdles to determine the exact time and quantity of water flowing in rivers and available for daily use. The volatile water caused by various water sources and irregular flow pattern generates different kinds of challenges for management. Distribution of flow of water in irrigation network affects the relevant community in either way. In the monsoon seasons, river belt community high risk of flood, while far living community suffering drought. Contemplating this situation, we have developed an ontology for context-aware information representation of riverine water management system abetting the visualization and proactive planning for the complex real-time situation. The purpose of this WaterOnto is to improve river water management and enable for efficient use of this precious natural resource. This would also be helpful to save the extra water being discharged in sea & non-irrigational areas, and magnitude and location of water leakage. We conceptualized stakeholder and relevant entities. We developed a taxonomy of irrigation system concepts in machine process able structure. Being woven these hierarchies together we developed a detailed conceptualization of river flow that helps us to manage the flow of water and enable to extract danger situation.

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“…The framework has one or more Arduino, Arduino shields to connect the water level detector (sensor), USB power plug (optional), solar panel, a chargeable battery, server computer, MicroSD card for storing data, socket for Xbee modules, breadboard with wires and LED for signal testing [18], siren, data and graph screen display, strong pillar to hold (solar panel, Arduino and other small components of wireless sensors network), box to keep and protect Arduino for security purpose [19]. The solar panel in this proposed framework is among the most important parts.…”

Section: A Overviewmentioning

confidence: 99%

Flood sensing framework by Arduino and Wireless Sensor Network in Rural-Rwanda

Vunabandi

Matsunaga

Markon

et al. 2015

2015 IEEE/ACIS 16th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distribu

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Our society is increasingly reliant on embedded systems for many critical day-to-day activities. Nowadays, Wireless Sensor Networks (WSN) are widely used almost everywhere, including both residential areas, and undeveloped areas near the river. Therefore, embedded systems can reduce risks due to an increase of climate change in Rwanda with potentially devastating impacts of floods on local communities and their properties. Advances in embedded system, particularly in WSN, offer us critical opportunities to develop complex real-time early warning and monitoring systems. The WSN technology has been applied in monitoring natural disasters for the last couple of decades. This paper further proposes an innovative and inexpensive framework designed to provide early warning for natural disaster via a siren. It works by continuously recording and transmitting sensor data to the main server. The server processes the data and then provides the warning, so that vulnerable residents can be notified before the floods come around their houses, especially in high risk zones. The major components of our framework include Arduino, solar panel, flood detector (sensor) with other wireless sensor components, a chargeable battery, Xbee and access point.

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Development of a Low-Power Smart Water Meter for Discharges in Indus Basin Irrigation Networks

Cited by 20 publications

References 9 publications

System identification of Khaira distributory

System identification of Khaira distributory

WaterOnto: Ontology of Context-Aware Grid-Based Riverine Water Management System

Flood sensing framework by Arduino and Wireless Sensor Network in Rural-Rwanda

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