Monitoring water quality through a telematic sensor network and a fuzzy expert system

Abstract

In this paper we present an expert system that monitors seawater quality and pollution in northern Greece through a sensor network called Andromeda. The expert system monitors sensor data collected by local monitoring stations and reasons about the current level of water suitability for various aquatic uses, such as swimming and piscicultures. The aim of the expert system is to help the authorities in the decision-making process in the battle against pollution of the aquatic environment, which is vital for public health and the economy of northern Greece. The expert system determines, using fuzzy logic, when certain environmental parameters exceed certain pollution limits, which are specified either by the authorities or by environmental scientists, and flags up appropriate alerts.

An empirical study on sea water quality prediction

“…In the future, we plan to integrate the water quality prediction algorithms we presented in this paper within the intelligent alerting system of Hatzikos et al (2007), so that the alerting system will be able to issue early warnings based on predicted hydrological parameters values.…”

“…Furthermore, the central station hosts an intelligent alerting system (Hatzikos et al, 2007) that monitors sensor data and reasons about the current level of water suitability for various aquatic uses, such as swimming and piscicultures. The aim of this intelligent alerting system is to help the authorities in the "decision-making" process in the battle against the pollution of the aquatic environment, which is very vital for the public health and the economy of Northern Greece.…”

Applying adaptive prediction to sea-water quality measurements

“…Furthermore, we plan to integrate the water quality prediction algorithms we presented in this paper within the fuzzy intelligent alerting system of Hatzikos et al (2007), so that the alerting system will be able to issue early warnings based on predicted hydrological parameters values. To this end, we have to extend our least square algorithms using fuzzy regression techniques (Hong & Hwang, 2004;Wang, Zhang, & Mei, 2007).…”

“…Furthermore, the central station hosts an intelligent alerting system (Hatzikos, Bassiliades, Asmanis, & Vlahavas, 2007) that monitors sensor data and reasons about the current level of water suitability for various aquatic uses, such as swimming and piscicultures. The aim of this intelligent alerting system is to help the authorities in the ''decision-making" process in the battle against the pollution of the aquatic environment, which is very vital for the public health and the economy of Northern Greece.…”

Data Fusion and Type-2 Fuzzy Inference in Contextual Data Stream Monitoring

“…In monitoring activities, FL could be proved a useful technique for delivering high quality systems [14], [15], [16]. The proposed FL systems handle the uncertainty related to the distribution of sensors reports and help in the decision making, i.e., simple alerts or more complex reasoning tasks.…”