• ENVIRONMENTAL AIR QUALITY MONITORING SYSTEM AS A SUPPORT FOR PRECISION AGRICULTURE

    Science. Business. Society., Vol. 4 (2019), Issue 2, pg(s) 41-43

    In order to make better decisions in the precision agriculture the measurement of air pollution parameters such as PM10, NOx, SO2, CO, O3 and agriculture parameters such as air temperature, humidity, soil moisture and leaf wetness are of crucial importance. Making analysis using different AI technics based on these parameters can bring better yield and quality in the food production process. In this paper, we present our approach in building an environmental air quality monitoring system as a support for precision agriculture by using Arduino [5] open-source electronics platform.

  • MODELLING THE RELATIONSHIP BETWEEN SATURATED OXYGEN AND DISTOMS‘ ABUNDANCE USING WEIGTHED PATTERN TREES WITH ALGEBRAIC OPERATORS

    Mathematical Modeling, Vol. 2 (2018), Issue 4, pg(s) 170-172

    Machine learning has been used in many disciplines to reveal important patterns in data. One of the research disciplines that benefits from using these methods is eco-informatics. This branch of applied computer science to solve environmental problems uses computer algorithms to discover the impact of the environmental stress factors on the organisms’ abundance. Decision tree type of machine learning methods are particularly interesting for the computer scientists as well as ecologists, because they provide very easy interpretable structure without any practical knowledge in mathematics or the inner working of the algorithm. These methods do not rely only on classical sets, but many of them are using fuzzy set theory to overcome some problems like overfitting, robustness to data change and improved prediction accuracy. In this direction, this paper aims to discover the influence of one particular environmental stress factor (Saturated Oxygen) on real measured data containing information about the diatoms’ abundance in Lake Prespa, Macedonia, using weighted pattern tree (WPT) algorithm. WPT is a decision tree method variant that combines fuzzy set theory concepts, like similarity metrics, fuzzy membership functions and aggregation operators, to achieve better prediction accuracy, improve interpretability and increase the resistance to overfitting compared to the classical decision trees. In this study, we use Algebraic operators for aggregation. One WPT model is presented in this paper to relate the saturated oxygen parameter with the diatoms’ abundance and reveal which diatoms can be used to indicate certain water quality class (WQC). The obtained results are verified with the existing knowledge found in literature.

  • MATHEMATICAL MODELLING OF TECHNOLOGICAL PROCESSES AND SYSTEMS

    INFLUENCE OF RANDOM NUMBER GENERATORS IN AIR POLLUTION MODEL SAMPLING

    Mathematical Modeling, Vol. 2 (2018), Issue 1, pg(s) 17-20

    The research covers the usage of the random numbers in Monte Carlo simulations for air pollution models. Two new random number generators are developed; their strengths are compared with the existing random number generators. The results in this paper showed that the two newly developed random number generators achieved better results on a basis of failed test, however it extended the time for generating random numbers. In future we plan to use the newly developed random generators for filling the missing values in the measurements.

  • TRANSPORT. SAFETY AND ECOLOGY. LOGISTICS AND MANAGEMENT

    ANALYZING THE LEVEL OF HIGH TROPOSPHERC OZONE DURING THE SUMMER 2014 and 2015 IN SKOPJE, R.MACEDONIA

    Trans Motauto World, Vol. 2 (2017), Issue 1, pg(s) 30-32

    Ozone is health-hazardous air pollutant and his level in the living environment is very important to be tracked and understand. This specific gas in nowadays occurs as byproduct of certain human activities, especially with car pollution and naturally due to increased temperature. Therefore, it is important to understand the relationship between this variable. The focus of this paper is to model this relationship, with data collected for period of 3 months in 2014 and 2015(summer period). According to the models obtained with machine learning methods, high level concentrations of ozone was found if temperature of the air is higher than 30.15oC and concentrations of NO2 are lower than 16.93 mg/m3(in 2013). Encourage by this model, in this paper we go further and extend our research to include more data (from 2014 and 2015) and different methods to find other influencing factors that contributes to high concentration of ozone.

  • SOCIETY

    NOISE POLLUTION MODELLING AND VISUALISATION – THE CASE STUDY FOR THE CITY OF SKOPJE

    Science. Business. Society., Vol. 1 (2016), Issue 2, pg(s) 48-50

    Noise pollution modelling can be used to provide information about growing noise pollution from the urban traffic. Various methods have been developed that aim at minimizing the noise pollution and improving the environment. Geographic Information System (GIS) can be adapted to gather, analyse and present noise information. The results in this paper demonstrated that most of regions surrounding the main streets are suffering from the noise pollution. As a main contribution of this paper, the first this-kind of study for the city of Skopje, practicing GIS capabilities for presenting noise information, we have produced a general picture of the traffic-induced noise pollution on annual level. The assessment showed that the used method in visualization can provide reliable information about noise pollution in any city or urban region. In this paper, we were focused, as a case study, for the city of Skopje.