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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 91
PROCEEDINGS OF THE TWELFTH INTERNATIONAL CONFERENCE ON CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING COMPUTING
Edited by: B.H.V. Topping, L.F. Costa Neves and R.C. Barros
Paper 278

An Architecture for an Environmental Process Controller based on Geoprocessing

L.A.O.L. Roque

Instituto Federal Fluminense, Macaé, Rio de Janeiro, Brazil

Full Bibliographic Reference for this paper
L.A.O.L. Roque, "An Architecture for an Environmental Process Controller based on Geoprocessing", in B.H.V. Topping, L.F. Costa Neves, R.C. Barros, (Editors), "Proceedings of the Twelfth International Conference on Civil, Structural and Environmental Engineering Computing", Civil-Comp Press, Stirlingshire, UK, Paper 278, 2009. doi:10.4203/ccp.91.278
Keywords: object oriented model, database, environmental monitoring process control, mathematical models, statistical models, geoprocessing.

Summary
Human activity has changed natural resources in dramatic ways. In order to fight against this fierce degradation, there is a great need for geographic information systems oriented to environmental monitoring. Society must track the real situation of its natural environmental resources, and this can be accomplished by selecting the objects important to monitor, by measuring their characteristics or attributes and by analyzing all this data using mathematical models, statistics, simulation and other tools [2]. There are some standards, goals or desired situations for the behaviour of an environmental system and, against this standard, the data originating from real world must be compared. Data to be collected is of different kinds and geographically dispersed, acquired by sensors disposed on specific hardware, known as data acquisition systems. So, we present an object oriented model, based on geo-processed data, which could be thought as a framework for every kind of environment processes controlling information system. This model is internet oriented, in the sense that the data to be collected can be geographically distributed. After its capture the data is sent, via the internet, to specific data base management systems (DBMS) to be stored. This raw data can be disseminated also via the internet, to researchers or other interested people. Some analysis will be done with the spatial data stored in the DBMS, before their presentation to the users. If this data stays in non secure limits of concentration, due to various reasons, some processes will be trigged, in order to avoid environmental damages on air, soil or water.

In Deitel and Deitel [1], it is suggested that systems developed in Java present the most cost-usefulness relation in achieving the independence of operating systems. The design of the hardware required for a data acquisition system environment and a Java based prototype is underway, in order to test the proposed architecture in the analysis of water quality models for the basin of some Brazilian rivers, located north of Rio de Janeiro. These models specify the mathematical equations governing the transport of contaminants in the basin, and its numeric resolution, to accurately determine the temporal variation of pollutants concentration in any position of the monitored body of water. With this framework, models could also be developed for different kinds of ecosystems and archived in a specific database aiming at being reused later.

Noting the common requirements for systems for environmental monitoring, it is concluded that the use of the model presented in this paper may benefit research, avoiding the repetition of the development of programs that use the pattern here suggested, and provide for the creation of cooperative work. There are various examples of control systems for environmental monitoring of processes that can take advantage of an implementation of software based on the structure presented in this paper.

References
1
H.M. Deitel, P.J. Deitel, "How to Program Java", second edition, Bookman, Rio de Janeiro, Brazil, 2001.
2
E.D. Ongley, W.G. Booty, "Pollution Remediation Planning in Developing Countries: Conventional Modeling versus Knowledge-Based Prediction", In Proceedings of the African Water Resources Policy Conference, Nairobi, 1999.

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