Abstract
In a context of e-government, there are usually regulatory compliance requirements that support systems must monitor, control and enforce. These requirements may come from environmental laws and regulations that aim to protect the natural environment and mitigate the effects of pollution on human health and ecosystems. Monitoring compliance with these requirements involves processing a large volume of data from different sources, which is a major challenge. This volume is also increased with data coming from autonomous sensors (e.g. reporting carbon emission in protected areas) and from citizens providing information (e.g. illegal dumping) in a voluntary way. Complex Event Processing (CEP) technologies allow processing large amount of event data and detecting patterns from them. However, they do not provide native support for the geographic dimension of events which is essential for monitoring requirements which apply to specific geographic areas. This paper proposes a geospatial extension for CEP that allows monitoring environmental requirements considering the geographic location of the processed data. We extend an existing platform-independent, model-driven approach for CEP adding the geographic location to events and specifying patterns using geographic operators. The use and technical feasibility of the proposal is shown through the development of a case study and the implementation of a prototype.
Highlights
A good management of natural resources and the environment requires the establishment of legal frameworks through laws and regulations
This section describes the main activities involved in regulatory compliance management and specific issues concerning the compliance with environmental regulations
In this paper we present how to perform the Complex Event Processing (CEP)-based monitoring and enforcement of environmental laws following a model-driven approach
Summary
A good management of natural resources and the environment requires the establishment of legal frameworks through laws and regulations. Those laws are continuously evolving in a complex way. Complex Event Processing (CEP) technologies allow processing, analyzing and correlating large amounts of heterogeneous data from many sources. This data comes in the form of events for detecting, in real time, relevant and critical situations [2].
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