scholarly journals KnoWare: A System for Citizen-based Environmental Monitoring

10.28945/3500 ◽  
2016 ◽  
Vol 19 ◽  
pp. 125-139 ◽  
Author(s):  
Jeremy J Storer ◽  
Joseph T. Chao ◽  
Andrew T Torelli ◽  
Alexis D Ostrowski
Keyword(s):  
Water Quality ◽  
Environmental Monitoring ◽  
Real Time ◽  
Citizen Science ◽  
Mobile Device ◽  
Scientific Data ◽  
Reliable Data ◽  
User Engagement ◽  
Timely Feedback ◽  
Quality Measurements

Non-expert scientists are frequently involved in research requiring data acquisition over large geographic areas. Despite mutual benefits for such “citizen science”, barriers also exist, including 1) difficulty maintaining user engagement with timely feedback, and 2) the challenge of providing non-experts with the means to generate reliable data. We have developed a system that addresses these barriers. Our technologies, KnoWare and InSpector, allow users to: collect reliable scientific measurements, map geo-tagged data, and intuitively visualize the results in real-time. KnoWare comprises a web portal and an iOS app with two core functions. First, users can generate scientific ‘queries’ that entail a call for information posed to a crowd with customized options for participant responses and viewing data. Second, users can respond to queries with their GPS-enabled mobile device, which results in their geo- and time-stamped responses populating a web-accessible map in real time. KnoWare can also interface with additional applications to diversify the types of data that can be reported. We demonstrate this capability with a second iOS app called InSpector that performs quantitative water quality measurements. When used in combina-tion, these technologies create a workflow to facilitate the collection, sharing and interpretation of scientific data by non-expert scientists.

scholarly journals KnoWare: A System for Citizen-based Environmental Monitoring

10.28945/3510 ◽  
2016 ◽  
Author(s):  
Jeremy J Storer ◽  
Joseph T. Chao ◽  
Andrew T Torelli ◽  
Alexis D Ostrowski
Keyword(s):  
Water Quality ◽  
Environmental Monitoring ◽  
Real Time ◽  
Citizen Science ◽  
Mobile Device ◽  
Scientific Data ◽  
Reliable Data ◽  
User Engagement ◽  
Timely Feedback ◽  
Quality Measurements

Non-expert scientists are frequently involved in research requiring data acquisition over large geographic areas. Despite mutual benefits for such “citizen science”, barriers also exist, including 1) difficulty maintaining user engagement with timely feedback, and 2) the challenge of providing non-experts with the means to generate reliable data. We have developed a system that addresses these barriers. Our technologies, KnoWare and InSpector, allow users to: collect reliable scientific measurements, map geo-tagged data, and intuitively visualize the results in real-time. KnoWare comprises a web portal and an iOS app with two core functions. First, users can generate scientific ‘queries’ that entail a call for information posed to a crowd with customized options for participant responses and viewing data. Second, users can respond to queries with their GPS-enabled mobile device, which results in their geo- and time-stamped responses populating a web-accessible map in real time. KnoWare can also interface with additional applications to diversify the types of data that can be reported. We demonstrate this capability with a second iOS app called InSpector that performs quantitative water quality measurements. When used in combina-tion, these technologies create a workflow to facilitate the collection, sharing and interpretation of scientific data by non-expert scientists.

scholarly journals Citizen Scientists Contribute to Real-Time Monitoring of Lake Water Quality Using 3D Printed Mini Secchi Disks

2021 ◽  
Vol 3 ◽  
Author(s):  
Grinson George ◽  
Nandini N. Menon ◽  
Anas Abdulaziz ◽  
Robert J. W. Brewin ◽  
P. Pranav ◽  
...  
Keyword(s):  
Water Quality ◽  
Real Time ◽  
Citizen Science ◽  
Economic Benefits ◽  
Scientific Data ◽  
Series Data ◽  
Estuarine System ◽  
Water Colour

Citizen science aims to mobilise the general public, motivated by curiosity, to collect scientific data and contribute to the advancement of scientific knowledge. In this article, we describe a citizen science network that has been developed to assess the water quality in a 100 km long tropical lake-estuarine system (Vembanad Lake), which directly or indirectly influences the livelihood of around 1.6 million people. Deterioration of water quality in the lake has resulted in frequent outbreaks of water-associated diseases, leading to morbidity and occasionally, to mortality. Water colour and clarity are easily measurable and can be used to study water quality. Continuous observations on relevant spatial and temporal scales can be used to generate maps of water colour and clarity for identifying areas that are turbid or eutrophic. A network of citizen scientists was established with the support of students from 16 colleges affiliated with three universities of Kerala (India) and research institutions, and stakeholders such as houseboat owners, non-government organisations (NGOs), regular commuters, inland fishermen, and others residing in the vicinity of Vembanad Lake and keen to contribute. Mini Secchi disks, with Forel-Ule colour scale stickers, were used to measure the colour and clarity of the water. A mobile application, named “TurbAqua,” was developed for easy transmission of data in near-real time. In-situ data from scientists were used to check the quality of a subset of the citizen observations. We highlight the major economic benefits from the citizen network, with stakeholders voluntarily monitoring water quality in the lake at low cost, and the increased potential for sustainable monitoring in the long term. The data can be used to validate satellite products of water quality and can provide scientific information on natural or anthropogenic events impacting the lake. Citizens provided with scientific tools can make their own judgement on the quality of water that they use, helping toward Sustainable Development Goal 6 of clean water. The study highlights potential for world-wide application of similar citizen-science initiatives, using simple tools for generating long-term time series data sets, which may also help monitor climate change.

scholarly journals CWDAT—An Open-Source Tool for the Visualization and Analysis of Community-Generated Water Quality Data

2021 ◽  
Vol 10 (4) ◽  
pp. 207
Author(s):  
Annie Gray ◽  
Colin Robertson ◽  
Rob Feick
Keyword(s):  
Water Quality ◽  
Data Quality ◽  
Capacity Building ◽  
Open Source ◽  
Citizen Science ◽  
Water Resource ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
User Engagement ◽  
Community Based

Citizen science initiatives span a wide range of topics, designs, and research needs. Despite this heterogeneity, there are several common barriers to the uptake and sustainability of citizen science projects and the information they generate. One key barrier often cited in the citizen science literature is data quality. Open-source tools for the analysis, visualization, and reporting of citizen science data hold promise for addressing the challenge of data quality, while providing other benefits such as technical capacity-building, increased user engagement, and reinforcing data sovereignty. We developed an operational citizen science tool called the Community Water Data Analysis Tool (CWDAT)—a R/Shiny-based web application designed for community-based water quality monitoring. Surveys and facilitated user-engagement were conducted among stakeholders during the development of CWDAT. Targeted recruitment was used to gather feedback on the initial CWDAT prototype’s interface, features, and potential to support capacity building in the context of community-based water quality monitoring. Fourteen of thirty-two invited individuals (response rate 44%) contributed feedback via a survey or through facilitated interaction with CWDAT, with eight individuals interacting directly with CWDAT. Overall, CWDAT was received favourably. Participants requested updates and modifications such as water quality thresholds and indices that reflected well-known barriers to citizen science initiatives related to data quality assurance and the generation of actionable information. Our findings support calls to engage end-users directly in citizen science tool design and highlight how design can contribute to users’ understanding of data quality. Enhanced citizen participation in water resource stewardship facilitated by tools such as CWDAT may provide greater community engagement and acceptance of water resource management and policy-making.

scholarly journals GEOSPATIAL BASED CITIZEN CENTRIC WATER QUALITY MEASUREMENT SOLUTION

2018 ◽  
Vol XLII-5 ◽  
pp. 75-78
Author(s):  
K. Oberoi ◽  
S. Purohit ◽  
P. A. Verma ◽  
A. Deshmukh ◽  
S. Saran ◽  
...  
Keyword(s):  
Water Quality ◽  
Information And Communication Technologies ◽  
Citizen Science ◽  
Web Application ◽  
National Level ◽  
Quality Measurement ◽  
Water Quality Monitoring ◽  
Scientific Data ◽  
Mobile App ◽  
Time Data

<p><strong>Abstract.</strong> Citizen science has emerged as a game changer in various scientific endeavors, wherein scientific data for understanding the phenomenon could be collected by volunteers/non-specialist in a quick possible time. Citizens nowadays play an important role by functioning as “sensors” helping government/institutions by collecting and analyzing data. The advancements and convergence of technologies (Information and communication technologies (ICT)), especially the Internet and mobile technology has further assisted in such efforts. Moreover, the location sensors (GPS) and camera on board the mobile devices enables citizens to collect geotagged data. The classic example is the OpenStreetMap project where volunteers contribute towards the mapping of the planet. This paper highlights the geospatial solution based on citizen science to collect geotagged data about the water quality (turbidity). This solution is developed using open source tools and consists of an Android based mobile app and web based dashboard on the server side for real time data visualization and analysis. The web application is designed and developed using PHP, JavaScript, HTML &amp; CSS and allows user to view the interpolated geotagged data about water quality over various background maps like OSM, Bhuvan etc. PostgreSQL/PostGIS are used as the backend geospatial data server for storing the geotagged dataset. Such solution will be very useful for water quality monitoring as part of national level project like Clean Ganga Mission using the citizen centric approach.</p>

A Robotic Vehicle for Aquatic Environmental Monitoring

2015 ◽  
Author(s):  
Jeffrey Laut ◽  
Ben High ◽  
Oded Nov ◽  
Maurizio Porfiri
Keyword(s):  
Water Quality ◽  
Data Collection ◽  
Environmental Monitoring ◽  
Citizen Science ◽  
Local Community ◽  
Rapid Assessment ◽  
Quality Data ◽  
Water Quality Data ◽  
Web Based ◽  
Robotic Vehicle

Environmental monitoring is critical for assessing and protecting our natural resources. Robotics can greatly benefit this field be enabling rapid assessment of large areas with minimal human supervision. Here, we describe an aquatic mobile robot for data collection in a polluted waterway. The robot is part of an environmental monitoring project known as “Brooklyn Atlantis,” and collects water quality data and images within the Gowanus Canal in Brooklyn, NY. Water quality is analyzed offline, while images are classified using citizen science through a web-based interface. To provide an added degree of interactivity to the participants of the project, an automated pan-tilt camera rig is developed, capable of providing 360° panorama photos that can be manipulated by a user. Beyond data collection, the robot serves as a useful tool for outreach and directly engaging the local community in science-based activities.

Sky Segmentation for Enhanced Depth Reconstruction and Bokeh Rendering with Efficient Architectures

2020 ◽  
Vol 2020 (14) ◽  
pp. 378-1-378-7
Author(s):  
Tyler Nuanes ◽  
Matt Elsey ◽  
Radek Grzeszczuk ◽  
John Paul Shen
Keyword(s):  
Real Time ◽  
Mobile Device ◽  
Computational Cost ◽  
False Positives ◽  
Compact Model ◽  
High Quality ◽  
False Negatives ◽  
Trade Off ◽  
Depth Reconstruction ◽  
Binary Classifiers

We present a high-quality sky segmentation model for depth refinement and investigate residual architecture performance to inform optimally shrinking the network. We describe a model that runs in near real-time on mobile device, present a new, highquality dataset, and detail a unique weighing to trade off false positives and false negatives in binary classifiers. We show how the optimizations improve bokeh rendering by correcting stereo depth misprediction in sky regions. We detail techniques used to preserve edges, reject false positives, and ensure generalization to the diversity of sky scenes. Finally, we present a compact model and compare performance of four popular residual architectures (ShuffleNet, MobileNetV2, Resnet-101, and Resnet-34-like) at constant computational cost.

A Real-Time Mathematical Model for Three-Dimensional Tidal Flow and Water Quality

1991 ◽  
Vol 24 (6) ◽  
pp. 171-177 ◽  
Author(s):  
Zeng Fantang ◽  
Xu Zhencheng ◽  
Chen Xiancheng
Keyword(s):  
Mathematical Model ◽  
Water Quality ◽  
Real Time ◽  
Control Volume ◽  
Tidal Flow ◽  
Three Dimensional ◽  
River Estuary ◽  
Pearl River Estuary ◽  
Practical Application ◽  
The Pearl River

A real-time mathematical model for three-dimensional tidal flow and water quality is presented in this paper. A control-volume-based difference method and a “power interpolation distribution” advocated by Patankar (1984) have been employed, and a concept of “separating the top-layer water” has been developed to solve the movable boundary problem. The model is unconditionally stable and convergent. Practical application of the model is illustrated by an example for the Pearl River Estuary.

First flush effects in an urban catchment area in Aalborg

1998 ◽  
Vol 37 (1) ◽  
pp. 251-257 ◽  
Author(s):  
Torben Larsen ◽  
Kirsten Broch ◽  
Margit Riis Andersen
Keyword(s):  
Water Quality ◽  
Catchment Area ◽  
Quality Parameters ◽  
Average Concentration ◽  
First Flush ◽  
Storm Events ◽  
Urban Catchment ◽  
Discharge Measurements ◽  
Quality Measurements

The paper describes the results of measurements from a 2 year period on a 95 hectare urban catchment in Aalborg, Denmark. The results of the rain/discharge measurements include 160 storm events corresponding to an accumulated rain depth of totally 753 mm. The water quality measurements include 15 events with time series of concentration of SS, COD, BOD, total nitrogen and total phosphorus. The quality parameters showed significant first flush effects. The paper discusses whether either the event average concentration or the accumulated event mass is the most appropriate way to characterize the quality of the outflow.

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