Water quality inversion model based on multi-spectral remote sensing from unmanned aerial vehicle (UAV) DOI

Shengwei Huang,

Mengya Zhao,

Sitian Jin

et al.

Published: May 24, 2024

Language: Английский

Enhancing water security through automation: case studies and technical advancements in water quality management DOI

Inam Ul Haq,

Akib Mohi Ud Din Khanday, Hilal Ahmad Shah

et al.

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 337 - 362

Published: Jan. 1, 2025

Language: Английский

Citations

0
Developing a real-time water quality simulation toolbox using machine learning and application programming interface DOI

Gi-Hun Bang,

Na-Hyeon Gwon,

Min‐Jeong Cho

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 377, P. 124719 - 124719

Published: Feb. 28, 2025

Language: Английский

Citations

0
Enhancing Desalination Systems with IoT, Solar Energy, and Advanced Sensor Technologies DOI Creative Commons

Geethu James,

K. Saravana Kumar,

D. Sudharsan

et al.

E3S Web of Conferences, Journal Year: 2025, Volume and Issue: 619, P. 02009 - 02009

Published: Jan. 1, 2025

Desalination management, the process of turning saltwater into potable water, has long been under pressure from rising water demands and environmental degradation, necessitating innovative solutions. We can streamline a number procedures that used to be labour-intensive resource-intensive. Improving administration treatment is one such thing. This study proposes smart environment regulate facilities offers workable model for system. The suggested method collects data analyses it find best way desalinate water. Incorporating enabling technologies like cloud portal, network communication, internet things, solar-powered sensors an old purification system what desalination framework all about seawater. To ensure systems run smoothly efficiently, makes use cutting- edge technology. Utilizing solar energy, dual membrane employs time-honoured techniques purify saltwater, creating irrigation-ready was cost- effective, producing 0.51 m 3 / l freshwater salt concentration 12 g/ with energy usage 9.12 KWh/m.

Language: Английский

Citations

0
Lake Environmental Data Harvester (LED) for Alpine Lake Monitoring with Autonomous Surface Vehicles (ASVs) DOI Creative Commons
Angelo Odetti, Gabriele Bruzzone, R. Ferretti

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(11), P. 1998 - 1998

Published: June 1, 2024

This article introduces the Lake Environmental Data Harvester (LED) System, a robotic platform designed for development of an innovative solution monitoring remote alpine lakes. LED is intended as first step in creating portable tools that are lightweight, cost-effective, and highly reliable water bodies. The system based on Shallow-Water Autonomous Multipurpose Platform (SWAMP), groundbreaking Surface Vehicle (ASV) originally wetlands. objective to achieve comprehensive lakes by outfitting SWAMP with suite sensors, integrating IoT infrastructure, adhering FAIR principles structured data management. SWAMP’s modular design open architecture facilitate easy integration payloads, while its compact size construction reduced weight ensure portability. Equipped four azimuth thrusters flexible hull structure, offers high degree maneuverability position-keeping ability precise surveys shallow waters typical In this project, was equipped including single-beam dual-frequency echosounder, water-quality winch sensor deployment, AirQino, low-cost air quality analysis system, along RTK-GNSS (Global Navigation Satellite System) receiver positioning. Utilizing commercial off-the-shelf (COTS) components, Data-Acquisition System forms basis Internet Things (IoT) enabling acquisition, storage, long-range communication. data-centric ensures acquired variables from both sensors managed according principles.

Language: Английский

Citations

1
Challenges and Opportunities for Water Quality Monitoring and Management in India DOI

Mridu Kulwant,

Akhilesh Kumar Yadav

Water science and technology library, Journal Year: 2024, Volume and Issue: unknown, P. 121 - 137

Published: Jan. 1, 2024

Language: Английский

Citations

1
Integrating sensor data and machine learning to advance the science and management of river carbon emissions DOI Creative Commons
Lee E. Brown, Taylor Maavara, Jiangwei Zhang

et al.

Critical Reviews in Environmental Science and Technology, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 24

Published: Nov. 24, 2024

Language: Английский

Citations

1
Smart Water Management and Resource Conservation DOI
Rajeev Kumar, Arti Saxena

Advances in electronic government, digital divide, and regional development book series, Journal Year: 2024, Volume and Issue: unknown, P. 235 - 262

Published: Nov. 15, 2024

Water is essential to every living being. management and resource conservation very important provide safe clean water all. Resources of have been polluted contaminated due increasing population urbanization. Irrigation hydropower reservoir are other sources responsible for stress on earth. The main aim smart cities urban development everyone at low cost in sustainable ways. Thus, it necessary conserve resources manage the smartly. Use non-conventional irrigation, aquaculture aquifer recharge one solutions decrease use fresh these purposes. Machine learning solution managing conserving resources. Various machine models applied prediction tasks. However, deep categorization regression task. chapter objective cities.

Language: Английский

Citations

1
Integrating sensor data and machine learning to advance the science and management of river carbon emissions DOI Creative Commons
Lee E. Brown

Authorea (Authorea), Journal Year: 2024, Volume and Issue: unknown

Published: April 16, 2024

Greenhouse gas (GHG) emission estimates originating from river networks remain highly uncertain in many parts of the world, leading to gaps global inventories and preventing effective management.In-situ sensor technology advances, coupled with mobile sensors on robotic sensor-deployment platforms, will allow more data acquisition monitor carbon cycle processes influencing CO 2 CH 4 emissions; however, if countries are respond effectively climate change threats, must be installed strategically ensure that they can used directly evaluate a range management responses across networks.We how analytical advances integrated into adaptable catchment human modifications.The most promising analytics provide processing, modelling, visualising approaches for high-resolution system Posted 16 Apr 2024 | CC-BY 4.0 https://doi.org/10.22541/essoar.171322696.69831029/v1| This is preprint has not been peer-reviewed.Data may preliminary.are assessed, illustrating multi-sensor machine learning solutions improve both proactive (e.g.forecasting) reactive strategies better manage emissions.

Language: Английский

Citations

0
Electrochemical activity of self-supporting nitrogen-doped graphene for the degradation and in-situ determination of methylene blue DOI

Jinzhe Bao,

Hongji Li, Xiaoyan Wang

et al.

Process Safety and Environmental Protection, Journal Year: 2024, Volume and Issue: 189, P. 920 - 929

Published: July 4, 2024

Language: Английский

Citations

0
Water quality inversion model based on multi-spectral remote sensing from unmanned aerial vehicle (UAV) DOI

Shengwei Huang,

Mengya Zhao,

Sitian Jin

et al.

Published: May 24, 2024

Language: Английский

Citations

0