Georgi Nikolov

Air quality monitoring in urban environments

Air pollution is both an environmental and a social problem, as it leads to a multitude of adverse effects on human health, ecosystems and the climate. Air pollution is one of the largest environmental health risks in Europe today. Quality of the air in city and urban areas is the most important factor that directly influences the incidence of diseases and decreases the quality of life. Taking appropriate decisions in a timely period depends on the measurement and analysis of the parameters of the air, which creates the need for the development of real time air quality monitoring. The use of multi-parameter air quality monitoring systems makes it possible to do a detailed level analysis of major pollutants and their sources. These monitoring systems are important components in many smart city projects for monitoring air quality and for controlling the main pollutant concentrations in urban areas. In this paper we present an approach for cost-effective measurement of relevant environmental parameters, based on a scalable sensor array with integrated amperometric and infrared gas sensors. The device has been tested in the city and the measurement was compared with the output data of the local environmental control authority stations. The preliminary results show that this approach can be used as an economical alternative to the professional grade systems.

Extraction of solar cell parameters using source measure unit

This paper presents a methodology for parameters extraction of photovoltaic cell based on real measurement. The modeling of equivalent schemes of solar cells is of great importance in order to be included in electric circuits for wireless sensor networks power supply. The parameters extraction of these devices is still a very difficult task, which requires experimental data, computing and modeling. In recent years different analytic, iterative, and evolutionary computational methods have been suggested in various references to extract the parameters of solar cell and modules. This paper presents an innovative approach to estimate model parameters by completely extracting them from real measured data.

Virtual system for analysis of treated water

One of our most vital resources nowadays is fresh water. Water quality refers to the condition of the water, including chemical, biological and physical characteristics with respect to its suitability for a particular purpose. The main purpose of this publication is to set up a virtual system for water analysis in order to measure particular parameters of the water before and after physicochemical treatment. The water is treated with clinoptilolite, which has recently been used for water filtration. It is suitable especially for water treatment due to its ion exchange, absorption properties and high porosity. The main geochemical and technological concerns are how the chemical behavior of natural clinoptilolite affects the quality of different types of water.

Environmental noise monitoring and mapping

Decline of environmental noise and subsequent pollution are one of the most important purposes for citizens, scientists and public representatives nowadays. Many European legislative initiatives and studies deal with environmental noise monitoring. The enabling factor for this ongoing development is the availability of low-cost and low-power devices for sensing, computing and communication. Systems for monitoring and depicting noise maps in real-time are an engineering and economic challenge that has already been addressed in several studies. The aim of this paper is to study and demonstrate scalable architecture of noise measuring devices with real-time functionality, which allows for straightforward expansions with additional sensors, and energy harvesting features. This work describes the design and rapid prototyping of a wireless sensor node to monitor environmental noise based on a Raspberry Pi 3 and cost-effective electronic components. Raspberry Pi architecture allows for acoustic level acquisition to be carried out simultaneously with computation of environmental noise levels. The noise maps presented here are produced by pilot installation of three sensor nodes. The evaluation of nodes functionality through long-term measurement shows that the proposed approach provides a good foundation for noise monitoring and mapping.

Cross-platform sensor networks

The development of wireless sensor networks offers new challenges for engineers and scientists from different technological areas. The involving of various hardware and software platforms in the implementation and design of sensor node increases the capabilities of sensor networks. Also, cloud services provide effective network management and access to stored data, detected and measured by sensors in the sensor network. This paper presents an approach for developing heterogeneous sensor networks and connecting it with cloud services.

Performance evaluation of low-cost particulate matter sensors

Increased particulate matter (PM) concentration in big cities and agglomerations is one of the main risk factors for the health of the residents. Conventional systems for PM monitoring have significant limitations, especially with respect to the costs for installation and maintenance. The number of these monitor stations is limited but PM concentration changes fast, non-linearly, within wide limits and depends on various factors. The large gradients in air quality, especially in urban areas, are a significant challenge for conventional measurement technologies. In recent years there has been a rapid development of compact, mobile low-cost measurement systems with better spatial coverage than that of traditional air quality systems. The present work is dedicated to the performance evaluation of commercial, off-the-shelf PM sensors. The main error sources in these sensors and the possibilities for their reduction are discussed.

System for multi-frequency capacitance-voltage characterization

Capacitance measurement at different DC voltage levels, different signal amplitudes and different frequencies, finds extensive application to qualify semiconductor and multiple-layered structures. Generally, the cost of such type instrumentation is in range of several thousand dollars and they are not very popular in the market. In present paper an approach of combining conventional measuring instruments and high-level programming environment is suggested in order to achieve system with complete functionalities for capacitance measurements.

Environmental noise logging and calculating

Noise pollution in urban environments is a common problem that affects peoples health and quality of life. It is therefore one of the main issues addressed in many studies of environmental noise level assessment. The equivalent sound pressure level (LAeq) is one of the most widely used indicators for evaluating environmental noise from roads, railways, and industry. According to the European framework of noise management, the day-evening-night noise indicator Lden is calculated on the basis of the LAeq measurements. Several studies show that the use of only one parameter for noise levels assessments is a simplification and it is necessary to take into account the noise frequency characteristics. So the use of parameters, which can estimate subjective peoples feelings, are required. In this paper, we analyze the suitability of using the psychoacoustic metrics given by Zwickers/ISO532 model, in addition to LAeq. The calculation of the parameters of this model for annoyance assessment requires considerable signal processing features which wireless sensor nodes do not have. Therefore, we propose a two-stage approach. At the first stage a conventional noise measurement is performed. The noise data is logged and the equivalent noise LAeq over defined time T (LAeq, T) is computed and forwarded to a database. At the second stage, using the logged data, basic psychoacoustic parameters are computed in a LabVIEW environment. Finally, sensor node prototypes and preliminary test results are presented.

LabVIEW based ECG signal acquisition and analysis

This paper presents a LabVIEW based system of acquisition, processing and analysis of ECG (electrocardiogram) signals. Biomedical signal acquisition has made great advances in recent years due to the introduction of modern hardware and software technologies. Computer based signal processing systems are becoming an efficient approach for acquisition and analyzing of such signals. In our implementation an AD8232 integrated signal conditioning front end of Analog Devices is used for measurement and preprocessing of the ECG signals. Battery powered data acquisition system, which avoids 50Hz noise and allows for safety measurement without additional isolation is employed. LabVIEW Biomedical Toolkit time-domain analysis is applied to study heart rate variability together with additional parameters.

Virtual colorimeter for water analysis

The water quality analysis is important for human health and environmental protection. There are many physical and chemical methods for such analysis, with different accuracies, complexity and time consumption. In the presented paper, a colorimetric method, based on virtual instrumentation is suggested and considered in details. At the end of the paper, the concentration of free chlorine in water is determined for example.