3 resultados para web based training

em CUNY Academic Works


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Smart water metering technologies for residential buildings offer, in principle, great opportunities for sustainable urban water management. However, much of this potential is as yet unrealized. Despite that several ICT solutions have already been deployed aiming at optimum operations on the water utilities side (e.g. real time control for water networks, dynamic pump scheduling etc.), little work has been done to date on the consumer side. This paper presents a web-based platform targeting primarily the household end user. The platform enables consumers to monitor, on a real-time basis, the water demand of their household, providing feedback not only on the total water consumption and relevant costs but also on the efficiency (or otherwise) of specific indoor and outdoor uses. Targeting the reduction of consumption, the provided feedback is combined with notifications about possible leakages\bursts, and customised suggestions to improve the efficiency of existing household uses. It also enables various comparisons, with past consumption or even with that of similar households, aiming to motivate further the householder to become an active player in the water efficiency challenge. The issue of enhancing the platform’s functionality with energy timeseries is also discussed in view of recent advances in smart metering and the concept of “smart cities”. The paper presents a prototype of this web-based application and critically discusses first testing results and insights. It also presents the way in which the platform communicates with central databases, at the water utility level. It is suggested that such developments are closing the gap between technology availability and usefulness to end users and could help both the uptake of smart metering and awareness raising leading, potentially, to significant reductions of urban water consumption. The work has received funding from the European Union FP7 Programme through the iWIDGET Project, under grant agreement no318272.

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The objective of this study is to develop a Pollution Early Warning System (PEWS) for efficient management of water quality in oyster harvesting areas. To that end, this paper presents a web-enabled, user-friendly PEWS for managing water quality in oyster harvesting areas along Louisiana Gulf Coast, USA. The PEWS consists of (1) an Integrated Space-Ground Sensing System (ISGSS) gathering data for environmental factors influencing water quality, (2) an Artificial Neural Network (ANN) model for predicting the level of fecal coliform bacteria, and (3) a web-enabled, user-friendly Geographic Information System (GIS) platform for issuing water pollution advisories and managing oyster harvesting waters. The ISGSS (data acquisition system) collects near real-time environmental data from various sources, including NASA MODIS Terra and Aqua satellites and in-situ sensing stations managed by the USGS and the NOAA. The ANN model is developed using the ANN program in MATLAB Toolbox. The ANN model involves a total of 6 independent environmental variables, including rainfall, tide, wind, salinity, temperature, and weather type along with 8 different combinations of the independent variables. The ANN model is constructed and tested using environmental and bacteriological data collected monthly from 2001 – 2011 by Louisiana Molluscan Shellfish Program at seven oyster harvesting areas in Louisiana Coast, USA. The ANN model is capable of explaining about 76% of variation in fecal coliform levels for model training data and 44% for independent data. The web-based GIS platform is developed using ArcView GIS and ArcIMS. The web-based GIS system can be employed for mapping fecal coliform levels, predicted by the ANN model, and potential risks of norovirus outbreaks in oyster harvesting waters. The PEWS is able to inform decision-makers of potential risks of fecal pollution and virus outbreak on a daily basis, greatly reducing the risk of contaminated oysters to human health.

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Serious games are a category of games which are designed for a specific purpose other than for pure entertainment. It is not a new concept but serious games using real data, coupled with real time modelling and combining model results with social and economic factors opens up a new paradigm for active stakeholder participation. DHI and UNEP-DHI Centre initiated a project called Aqua Republica where a virtual world is developed which allows participants to develop a river basin and visualise the consequences of their decisions. The aim of this project is to raise awareness of the interconnectivity of water and educate on integrated water resources management. Aqua Republica combines a game layer with a water allocation model, MIKE BASIN, to create an interactive, realistic virtual environment where players play the role of a catchment manager of an undeveloped river catchment. Their main objective is to develop the river catchment to be as prosperous as it can be. To achieve that, they will need to generate a good economy in the catchment to provide the funds needed for development, have a steady food supply for their population and enough energy and water for the catchment. Through these actions by the player, a meaningful play is established to engage players and to educate them about the complex relationships between developmental actions in a river basin and the natural environment as well as their consequences. The game layer also consists of a reward system to encourage learning. People can play and replay the game, get rewarded from performing the right principles and penalised from failures in the game. This abstract will explain the concept of the game and how it has been used in a stakeholder participation environment.