Potentiometric E-Tongue System for Geosmin/Isoborneol Presence Monitoring in Drinkable Water

A potentiometric E-tongue system based on low-selective polymeric membrane and chalcogenide-glass electrodes is employed to monitor the taste-and-odor-causing pollutants, geosmin (GE) and 2-methyl-isoborneol (MIB), in drinkable water. The developed approach may permit a low-cost monitoring of these compounds in concentrations near the odor threshold concentrations (OTCs) of 20 ng/L. The experiments demonstrate the success of the E-tongue in combination with partial least squares (PLS) regression technique for the GE/MIB concentration prediction, showing also the possibility to discriminate tap water samples containing these compounds at two concentration levels: the same OTC order from 20 to 100 ng/L and at higher concentrations from 0.25 to 10 mg/L by means of PLS-discriminant analysis (DA) method. Based on the results, developed multisensory system can be considered a promising easy-to-handle tool for express evaluation of GE/MIB species and to provide a timely detection of alarm situations in case of extreme pollution before the drinkable water is delivered to end users.

Multisensory System for Monitoring and Control of Artificial Plant Growing Environment

The paper represents a small controller with wireless connection, which measures air temperature, air humidity and soil humidity. As an output action it can switch on and off an irrigation pump. Monitoring is realized over Wi-Fi connection to a gateway and cloud service. The service allows database storage and graph representation of the input values via desktop or mobile device browser. Sensors choice is also explained in details with advantages and disadvantages of the possible solutions. Developed device allows fine tuning, according to the target plants, can be duplicated many times in the range of the hothouse. It is one of the cheapest solutions which provides very stable work as a result of the specific implementation.

RANCANG BANGUN SISTEM PENDETEKSI KEBAKARAN DINI BERBASIS LOGIKA FUZZY MENGGUNAKAN MULTISENSOR

At Indonesia, cases of residential house fires are still rampant. This resulted in considerable losses for the population of Indonesia. If there is no prevention or countermeasure, it is possible that the danger of a house fires will continue. Therefore, this system exists to create a condition where the system is able to detect the potential that will bring a fire hazard. In this system using a method that is the application of a multisensory system in detecting the presence of fire, smoke and temperature in the room. The sensors used include KY-026 fire sensor, MQ-9 smoke sensor and DS18B20 temperature sensor. Then the system also implements an intelligent system that is fuzzy logic to process sensor reading data. The three sensor inputs will be processed through the fuzzification stage, rule evaluation and the deffuzification. The output of this system is in the form of firm values, namely the values 1 to 5 from the results of the multisensory defuzzification in each module. So the error of the defuzzification average is 0.99% after being compared with the MATLAB output. This system is expected to be able to provide early warning of the threat of fire, reduce the risk of casualties, and be able to be implemented to a wider scale or scope.

Multisensory System Used for the Analysis of the Water in the Lower Area of River Danube

The present paper describes the development of a multisensory system for the analysis of the natural water in the Danube, water collected in the neighboring area of Galati City. The multisensory system consists of a sensor array made up of six screen-printed sensors based on electroactive compounds (Cobalt phthalocyanine, Meldola’s Blue, Prussian Blue) and nanomaterials (Multi-Walled Carbon Nanotubes, Multi-Walled Graphene, Gold Nanoparticles). The measurements with the sensors array were performed by using cyclic voltammetry. The cyclic voltammograms recorded in the Danube natural water show redox processes related to the electrochemical activity of the compounds in the water samples or of the electro-active compounds in the sensors detector element. These processes are strongly influenced by the composition and physico-chemical properties of the water samples, such as the ionic strength or the pH. The multivariate data analysis was performed by using the principal component analysis (PCA) and the discriminant factor analysis (DFA), the water samples being discriminated according to the collection point. In order to confirm the observed classes, the partial least squares discriminant analysis (PLS-DA) method was used. The classification of the samples according to the collection point could be made accurately and with very few errors. The correlations established between the voltammetric data and the results of the physico-chemical analyses by using the PLS1 method were very good, the correlation coefficients exceeding 0.9. Moreover, the predictive capacity of the multisensory system is very good, the differences between the measured and the predicted values being less than 3%. The multisensory system based on voltammetric sensors and on multivariate data analysis methods is a viable and useful tool for natural water analysis.