Power Of Gas Research Articles

Application of gene expression programing in predicting the concentration of PM2.5 and PM10 in Xi’an, China: a preliminary study

Introduction: Traditional statistical methods cannot find quantitative relationship from environmental data.Methods: We selected gene expression programming (GEP) to study the relationship between pollutant gas and PM2.5 (PM10). They were used to construct the relationship between pollutant gas and PM2.5 (PM10) with environmental monitoring data of Xi’an, China. GEP could construct a formula to express the relationship between pollutant gas and PM2.5 (PM10), which is more explainable. Back Propagation neural networks (BPNN) was used as the baseline method. Relevant data from January 1st 2021 to April 26th 2021 were used to train and validate the performance of the models from GEP and BPNN.Results: After the models of GEP and BPNN constructed, coefficient of determination and RMSE (Root Mean Squared Error) are used to evaluate the fitting degree and measure the effect power of pollutant gas on PM2.5 (PM10). GEP achieved RMSE of [8.7365–14.6438] for PM2.5; RMSE of [13.2739–45.8769] for PM10, and BP neural networks achieved average RMSE of [13.8741–34.7682] for PM2.5; RMSE of [29.7327–52.8653] for PM10. Additionally, experimental results show that the influence power of pollutant gas on PM2.5 (PM10) situates between −0.0704 and 0.6359 (between −0.3231 and 0.2242), and the formulas are obtained with GEP so that further analysis become possible. Then linear regression was employed to study which pollutant gas is more relevant to PM2.5 (PM10), the result demonstrates CO (SO2, NO2) are more related to PM2.5 (PM10).Discussion: The formulas produced by GEP can also provide a direct relationship between pollutant gas and PM2.5 (PM10). Besides, GEP could model the trend of PM2.5 and PM10 (increase and decrease). All results show that GEP can be applied smoothly in environmental modelling.

SITUATION IN THE RUSSIAN GAS INDUSTRY IN 2022–2023

The article examines the state of the Russian gas industry in the period from the beginning of sanctions (2022) to the end of 2023. The author assesses the period of adaptation to the new market conditions. It is the author’s opinion that the risks in the gas sector last year turned out to be more extensive than in the oil sector. The reduction in gas production is primarily due to the reduction in natural gas purchases by European consumers. Exports to non-CIS countries have decreased over the past two years. Over the past two years, there has been a decline in gas production levels, with the most noticeable drawdowns being seen at Gazprom. This is not only due to the decrease in exports, but also due to the increase in production by other companies (NOVATEK and Rosneft).Russia currently supplies gas via pipelines to Europe, Turkey and the People’s Republic of China. In the European direction, supplies are made through the Ukrainian GTS and the Turkish Stream pipeline. Gas supplies to China have the greatest potential; during the period under review, they increased one and a half times. There is a planned increase in supplies through the Power of Siberia gas pipeline.The author also describes the complicated dynamics in the domestic gas market. The program of social gasification, which continues to develop, is mentioned separately.According to the author, the government will have to develop measures to support the industry in order to fulfill its social obligations and develop new projects that will ensure diversification of sales markets and substitution of partners from unfriendly jurisdictions in the coming years.

Effect of Many-Particle Interactions on the Transport Properties of Low-Energy Ions in Carbon Nanotubes

Using the method of molecular dynamics, the significance of many-particle interactions in the dynamics of low-energy ions in carbon nanotubes is studied, and the necessity of taking into account such interactions in the corresponding molecular dynamics calculations is shown. The effect of elastic perturbations of the carbon nanotube wall on the motion of ions inside the nanotube channel has been studied. It was found that the ion energy losses decrease by a factor of 1.5–3 when the influence of the perturbation of the carbon nanotube wall on the motion of ions is taken into account when the ion velocity approaches the perturbation propagation velocity. It has also been shown that the effect of the interaction between moving ions and perturbations of the carbon nanotube wall becomes more monotonic with a decrease in the magnitude of thermal fluctuations of the nanotube wall, in terms of energy losses by ions. Within the framework of the model under consideration, the stopping power of the electron gas bound to the atoms that form the walls of a carbon nanotube is small compared to the energy losses of ions due to elastic collisions with nanotube atoms.

Controlling Silicon Etching Parameters in RF CHF3 Plasma by Optical Emission Spectroscopy

The processes of plasma-chemical and reactive-ion etching of silicon in trifluoromethane (CHF3) are studied using optical emission spectroscopy. The dependences of the radiation intensities of atoms and mol-ecules on the etching time, input power, and pressure of the plasma-forming gas are obtained and analyzed.

Performance analysis of a bio-diesel fired engine bottoming with micro-ORC

The purpose of this work is to investigate the performance in terms of electric power and electric efficiency of a 11kW bio-diesel internal combustion engine (ICE) coupled with a micro Organic Rankine Cycle (ORC) both in design and off-design conditions. A zero dimensional (0D) thermodynamical engine model has been developed to predict the electric and thermal power with 100% biodiesel fuel (B100). B100 has been selected for the performance analysis of the integrated system due its lower environmental impact. For the ORC system, a subcritical thermodynamic model has been used with various working fluid (R245fa, R1233zd(E), R134a, R1234ze(E) and R1234ze(Z)). A plate heat exchanger (PHEX) has been adopted as evaporator of the organic cycle to directly recover the thermal power of the exhaust gas. Both models have been validated using experimental data from literature. Two different expander configurations, dynamic and volumetric, has been investigated. Model validations show good agreement with the experimental and literature data, respectively. Moreover, the results highlight that the micro-ORC could achieve a maximum electric efficiency of about 7% at full load with R1234ze(Z). Although at part load the dynamic expander show better performance, the volumetric expander has been selected for the system analysis due to its real suitability for small and micro scale ORC. Combined system results show a maximum enhancement of engine efficiency of about 5%, and better results, in terms of good compromise between electric efficiency and operating range width, has been shown for R1233zd(E). Furthermore, the direct coupling of the PHEX with the exhaust gases allows to have heat exchange evaporator areas below 2 m2 for all analysed fluids.

Flame acceleration process of premixed hydrogen in confined space with different obstacle shapes

Obstacles can greatly stimulate the detonation power of gas, and have great research value in industrial safety and energy utilization. Thus, in this work, the combustion characteristics of hydrogen under different shape obstacles are investigated. The important parameters for the evaluation of the gas combustion characteristics are analyzed, including the flame structure, flame propagation velocity and explosion overpressure. The results show that it is difficult for the flame front to recover to the regular front after passing through grid-type obstacles with many voids. To further understand the influence of the obstacle shape on the flame structure evolution, the change in the flow field before and after the flame approaches the obstacle is analyzed. The results show that the flow field formed by the combustion products can be seriously unstable after the flame front passes through grid-type obstacles, resulting in a severe distortion of the flame front. Moreover, the influence of the obstacle shape on the flame propagation velocity under different blockage ratios is compared. The results show that the single-type obstacle has a better effect on the acceleration of the flame, and it is more sensitive to the increase in the blockage ratio. The grid-type obstacle can improve the sensitivity to the blocking rate by reducing the void area. Furthermore, by analyzing the pressure growth rate, it is found that the influence of the obstacle shape on the explosion overpressure under different blockage ratios is the same as that of the flame propagation velocity. This work can provide some guidance for industrial explosion prevention and control and energy power system design.

A novel process of cyclic adsorption and plasma-desorption for ppm-level CO removal from H2-rich stream

A cyclic adsorption and plasma-desorption (CAPD) process is applied to remove ppm-level carbon monoxide (CO) from the H2-rich stream for the first time. In the CAPD process, CO is first selectively adsorbed on CuCl/γ-Al2O3 till adsorption saturation; Then, the adsorbed CO is in-situ desorbed by plasma generated in dielectric barrier discharge (DBD) and the adsorbent is regenerated simultaneously. The effects of discharge power (Pdis) and flow rate of discharge gas (FD) on performances of plasma-desorption are investigated. The time to reach desorption of 50% (t50) and 90% (t90) significantly decreases with Pdis but is weakly correlated to the FD. At the investigated conditions, t50 and t90 are lower than 2.6 min and 4.5 min, respectively, which indicates that plasma-desorption features high desorption rate. In addition, desorption efficiency of plasma-desorption is higher than 98%. Moreover, CAPD process stability is preliminarily confirmed by six consecutive adsorption-desorption cycles.

Optimization and efficiency analysis of methanol SOFC-PEMFC hybrid system

In order to improve the power generation efficiency of fuel cell systems employing liquid fuels, a hybrid system consisting of solid oxide fuel cell (SOFC) and proton exchange membrane fuel cell (PEMFC) is proposed. Utilize the high temperature heat generated by SOFC to reform as much methanol as possible to improve the overall energy efficiency of the system. When SOFC has a stable output of 100 kW, the amount of hydrogen after reforming is changed by changing the methanol flow rate. Three hybrid systems are proposed to compare and select the best system process suitable for different situations. The results show that the combined combustion system has the highest power generation, which can reach 350 kW and the total electrical efficiency is 57%. When the power of the tail gas preheating system is 160 kW, the electrical efficiency can reach 75%. The PEM water preheating system has the most balanced performance, with the electric power of 300 kW and the efficiency of 66%.

Enhancing heat dissipation to improve efficiency of two-stage electric air compressor for fuel cell vehicle

The electric air compressor is the most energy-consuming auxiliary component in the PEMFC (Proton Exchange Membrane Fuel Cell), and its power consumption accounts for more than 80% of the PEMFC parasitic power. Improving the efficiency of electric air compressor is of great significance to energy saving of the PEMFC. In this study, the numerical equation of the internal flow channel of the TSEAC (Two-stage Electric Air Compressor) was established. The validity of the numerical equation was verified by the experimental study. It is found that the heat generated by the electric air compressor for the PEMFC is 2–4 times higher than that of the turbocharger for a traditional diesel engine. Besides, the temperature-rising characteristics of gas in the inner flow passage of the TSEAC are analyzed. Under its normal working conditions, the temperature rise of gas passing through impeller and diffuser reaches the maximum of 33.97 K and 48.95 K, respectively. Higher temperatures cause gas to be heated and expand more, thus increasing the compression power of compressed gas consumed, and the efficiency of the TSEAC is reduced. The theoretical compression power of the TSEAC with cooling compression process is calculated. It is concluded that shell cooling can reduce the export of first and second level compression stress and the second level compression inlet temperature. Under constant inlet pressure and temperature, shell cooling can reduce the internal power consumption of the TSEAC. In order to verify the feasibility of this study, the thermal conductivity of the TSEAC shell was increased from 273W/(m·K) to 397W/(m·K) and 524W/(m·K), the outlet temperature was decreased by 7.5 K and 12 K, and the maximum efficiency was increased by 1.3% and 2.4%, respectively.

Retracted: “An Approach of Multistage Connected Ventilation Cooling Structure for Armored Vehicle Thermal Management” [ASME Journal of Thermal Science and Engineering Applications, 2021, 14(2), p. 021008; DOI: 10.1115/1.4051370

Abstract The thermal environment of the power cabin and high-temperature exhaust gas seriously affect the performance and survivability of the armored vehicle on the battlefield. In order to improve the hostile thermal environment of the enclosed power cabin and inhibit the infrared characteristics of exhaust gas, this paper puts forward a multistage connected ventilation cooling structure based on the unique structural characteristics of the armored vehicle. The structure utilizes the rotating action of the fans to introduce the cold air into the power cabin, volute, and smoke exhaust pipe in turn. The effects of the multistage connected structure on the temperature field and exhaust infrared detection power of the armored vehicle were studied by numerical simulation. It was indicated that the multistage connected ventilation cooling structure can effectively improve the thermal environment of the armored vehicle cabin by about 15.18% and reduce the infrared detection power of exhaust gas by about 11.35%. This paper is of great significance for studying the cooling of the power cabin and the design of armored vehicle’s infrared stealth.

Effect of solution pH and conductivity on nitrate synthesis by air contact glow discharge electrolysis method

This study aims to determine the effect of pH of the solution and conductivity on the yield of nitrates formed. The method is carried out by plasma electrolysis made from air injection. The electrolyte solution used is a mixture of K2HPO4 and K2SO4. The pH condition of the solution is getting longer decreasing also has an effect due to acidic nitrate ions which are more formed if dissolved in water. If the condition of the solution the more acidic, the absorption power of NO2 gas formed in the solution to to NO3 will decrease further, so that over time resulting in the production of nitrates in the solution will decrease. The research results showed that for 120 minutes the processing time was large The pH decreases due to the formation of acidic nitrates. Decreased pH can also be caused by H2O2 production. In minute 0 to minute 5, a significant decrease in pH of 2.99. This is due to accretion nitrate product for 5 minutes the process is very significant that is equal to 1277 ppm. While the decrease in pH at minute 5 to minute 120 is less significant, where the pH decreases around 0.09 to 0.02 due to increase nitrate products are not as large as 5 minutes of processing time. Then, the more acidic the solution causes nitrate production to decrease. In acidic conditions, absorption of NO2 gas formed in the solution to be converted to NO3 will decrease. The concentration of an electrolyte solution affects the conductivity of a solution, where the higher the concentration of an electrolyte solution, the conductivity of a solution will also be even greater. The amount of conductivity will affect the speed at which a plasma is formed.

Effect of Converter Shape on Reaction Rate between Slag and Metal in a Combined Blowing Converter with Inert Gas Bottom Blowing

The peroxidation of molten steel is a problem occurred in a combined blowing converter with inert gas blowing. It caused by a relatively weak mixing power of bottom blown inert gas compared with that of bottom blown oxygen gas. In order to resolve the problem, several methods for optimizing top and bottom blowing conditions has developed. However, the effect of the equipment condition such as converter shape on the metallurgical characteristics has not been investigated enough. In this study, the effect of H/D (ratio of bath depth H to bath diameter D) on the reaction rate between slag and metal, and furnace body vibration in converter was investigated by water model experiments. It was found that the apparent reaction rate constant, kA/Vw, increase with increasing H/D, except for the case of H/D=0.85. It seemed that the change of kA/Vw with increasing H/D has a relation to the behavior of bath vibration. From the analysis based on the bath surface vibration model, it was indicated that the change of H/D affects the bath surface vibration behavior and the formation behavior of slag emulsion, and these effects increase the reaction interface between slag and metal.

Analysis of optimal humidification temperature for a flue gas thermoelectric generation system with gas humidification

Using thermoelectric generator to recover the condensation latent heat of flue gas for power generation can not only improve the utilization efficiency of fuel but also recover the moisture in the flue gas, making the exhaust cleaner. Based on the heat transfer characteristics of flue gas condensation, a flue gas thermoelectric generation system with gas humidification is constructed, and the mathematical model is established in this paper. By comparing the power generation performance of dry and wet flue gas, it is found that the output power of wet flue gas can reach 2.24 times of dry flue gas, and the moisture recovery rate of flue gas can reach 65.7%. Through gas humidification, the output power of the system can be significantly improved. In addition, the existence of an optimum humidification temperature is found to minimize optimum module area and maximize power output. The mechanism that gives rise to the optimum humidification temperature is discussed, and the condition for the optimal humidification temperature is pointed out. A thermal resistance model of the thermoelectric generator is employed to deduce the relationship between the optimum humidification temperature and initial parameters of the system. It is found that the variation of flue gas and vapor parameters can make the optimal humidification temperature higher than 150 °C. The moisture content of flue gas, heat transfer coefficient of flue gas, and cooling water temperature are the main factors affecting the optimal humidification temperature. The research results have a certain guiding significance for the deep utilization of wet flue gas and clean operation of boilers.

Solar Integrated Unit to Reduce Power and Cooling Penalty of a Natural Gas Combined Cycle Plant integrated with a Carbon Capture System

Integrating solar assisted plant with a carbon capture unit to provide the required reboiler heat duty has been recently investigated extensively to reduce the negative impact of carbon capture unit on plant performance. However, using solar assisted plant to provide the required energy in the reboiler of the stripper leads to increase plant’s condenser duty unfavorably. In the present study, two novel configurations have been proposed for a concentrated solar assisted power plant to generate the required reboiler duty in the stripper of a post-combustion carbon capture unit (PCCC-SAPP) in a (630 MWe) natural gas combined cycle (NGCC) power plant to reduce both the condenser duty and power penalty of the plant simultaneously. In the present study, both the solar plant and plant’s low-pressure steam (LPS) are contributing to deliver the required reboiler thermal energy in the first method while the extraction is from the cooling system load in addition to the solar plant in the second method. Solar contribution factor (SCF) is the main criteria which has been used to evaluate the findings. Condenser duty with its associated water requirements, power penalty, and the required solar field land area are the parameters which have been investigated in the preset study. It has been found that the second configuration method has better impact on the performance of the plant and its associated cooling system than the first configuration method where zero power penalty is consumed in the second configuration as well as reducing the condenser duty with its related water usage amounts. In addition, it was shown that raw water withdrawal and consumption amounts in term of (gal/min)/MWnet decrease with increasing SCF in the first configuration where raw water withdrawal and consumption amounts are 7.23 (gal/min)/MWnet, and 5.17 (gal/min)/MWnet at SCF equals to 0 while these amounts reach to 6.74 (gal/min)/MWnet and 4.82 (gal/min)/MWnet at SCF of 0.95 respectively. On the other hand, these amounts increase with increasing SCF in the second configuration where water withdrawal and consumption values approach 6.75 (gal/min)/MWnet, and 4.92 (gal/min)/MWnet at SCF equals to 0 while the amounts are equal to 7.93 (gal/min)/MWnet and 5.81 (gal/min)/MWnet at SCF equals to 0.95 respectively despite that condenser duty is increasing in the both methods. This comes from the fact that the net produced power is increasing in the first scenario with SCF while it keeps constant in the second scenario. Furthermore, the relationship between the solar field’s required land area and solar direct normal irradiation (DNI) was investigated in the present paper under four different SCF; 0.2, 0.4, 0.6, and 0.8. It was found that reducing the solar field’s required land area requires increase in the DNI and decrease in the SCF where the reboiler heat duty is constant in the PCCC and the relationship is almost exponential. The validation was performed with an American governmental report (NETL, 2015) showing that the presented results has a significant agreement with the report.

Hydrogeological Modeling in Tropical Regions via FeFlow

hydrological modeling is commonly crossed by the solution of inverse problems and the estimation for non-linear parameters techniques. Despite this common scenario, the use of these guidelines is limited to the proper sampling of in-field data. This sampling involves a variety of data that generally have little availability, especially in regions where geographical and climatic variability does not allow a constant measurement. In this article, we present the analysis of a regional underground flow model using two techniques: pilot points (PP) and constant zones (CZ). This methodologies allow identifying properly if there are any biased parameters and heterogeneity of hydraulic properties. For this purpose, we developed a numerical variable density model that is limited with reinterpreted data from real measurements. For the CZ technique, the initial parameters are assigned according to its layer, and every layer is considered constant for parameter values; in contrast for PP technique, the initial parameters are assigned according to interpolations using in-situ point measurements. The developed model was applied in an area under the influence of the ITCZ, located in the middle valley of Magdalena (MMV). This area is important on the development of the country due to its contribution to GDP and has been subject to significant changes in land use, as a result of intense economic activities, for example, agriculture, hydroelectric power, and production of oil and gas. The established model shows a scarce link with the observed state variable (hydraulic head -K), this proves the importance of spatial heterogeneity in K. The model is calibrated in order to establish K (as an anisotropic variable that varies spatially), the porosity (η) and the specific storage capacity (Ss) in the PP and CZ, reducing a “mean square” error of state variable dependable on the observation points. The results show that the PP system approach provides a better heterogeneity representation and shows that each parameter is sensitive, and does not depend on other parameters, giving to the parameter evaluation results factual independence and authenticity. This research compiles a methodology to assertively restrict a highly parameterized inverse model with field data to estimate aquifer parameters that vary spatially at a regional scale

Prediction and Analysis of Abnormal Gas Emission Law in Low-Gas Tunnel Based on K-Line Diagram

The risk of gas disaster in the low-gas tunnel is easy to be ignored. By tracking and analyzing the gas monitoring data of the low-gas tunnel, it is found that the cyclic abnormal gas emission occurred many times during the construction period, leading to local gas accumulation, which greatly increases the risk of gas explosion accidents. To scientifically predict the abnormal gas emission in low-gas tunnels, the idea of K-line diagram-based prediction of abnormal gas emission in low-gas tunnels is put forward, and in combination with the field monitoring data of low-gas tunnel (Huangguashan Tunnel), the prediction results with different prediction indexes of K-line diagram are compared and analyzed. The results show that the K-line diagram can reflect the changing trend of gas concentration in real time accurately and show the change law of gas concentration during different construction processes; the moving average (MA) of the K-line diagram can accurately reflect the time of abnormal gas emission, the moving average convergence divergence (MACD) index can reflect the upward or downward power and trend of gas, and the Bollinger Band (BOLL) index can reflect the fluctuation range of gas concentration. The research results can provide a reference for the prediction and prevention of abnormal gas emission in low-gas tunnels.

Modeling gas–shell mixing in ICF with separated reactants

Mixing between fuel and shell materials in ICF implosions can affect implosion dynamics and even prevent ignition. We use data from a series of separated reactant experiments on the National Ignition Facility to calibrate and test the predictive power of gas–shell mix models. Two models are used to estimate fuel–shell mix: a Reynolds-averaged turbulence model and molecular diffusion. Minor uncertainties in capsule manufacture, experimental conditions, and values for mix model parameters produce significant variation in simulation results. Using input/output pairs from 1D simulations, we train Gaussian process surrogate models to predict experimental quantities of interest. The surrogates are used to construct posteriors for mix model parameters by marginalizing over uncertainties in capsule manufacture and experimental conditions. Mix models are calibrated with a subset of experimental data (neutron yields, ion temperature, and bang time) and tested using the remaining data. In general, both the diffusion and turbulence model correctly predict experimental DT and TT neutron yields. Despite having more free parameters, the turbulence model underpredicts ion temperature at high convergence ratio. The simpler diffusion model correctly predicts these temperatures, suggesting nonhydrodynamic gas–shell mix. The computational model consistently overpredicts DD neutron yield, indicating possible shortcomings outside of the mix model.

Machine-learning-assisted fabrication: Bayesian optimization of laser-induced graphene patterning using in-situ Raman analysis

The control of the physical, chemical, and electronic properties of laser-induced graphene (LIG) is crucial in the fabrication of flexible electronic devices. However, the optimization of LIG production is time-consuming and costly. Here, we demonstrate state-of-the-art automated parameter tuning techniques using Bayesian optimization to advance rapid single-step laser patterning and structuring capabilities with a view to fabricate graphene-based electronic devices. In particular, a large search space of parameters for LIG explored efficiently. As a result, high-quality LIG patterns exhibiting high Raman G/D ratios at least a factor of four larger than those found in the literature were achieved within 50 optimization iterations in which the laser power, irradiation time, pressure and type of gas were optimized. Human-interpretable conclusions may be derived from our machine learning model to aid our understanding of the underlying mechanism for substrate-dependent LIG growth, e.g. high-quality graphene patterns are obtained at low and high gas pressures for quartz and polyimide, respectively. Our Bayesian optimization search method allows for an efficient experimental design that is independent of the experience and skills of individual researchers, while reducing experimental time and cost and accelerating materials research.

A novel configuration of ejector refrigeration cycle coupled with organic Rankine cycle for transformer and space cooling applications

Abstract To provide stable voltage at some nodes of electricity grid network, gas engines are used for generating and injecting electricity to those specific nodes. A transformer is also required for increasing the voltage from that generated by the gas engine to the voltage of grid network. This transformer warms up due to power losses and needs to be cooled. Thus an ejector refrigeration cycle (ERC) which uses a part of available exhaust gas heating power in its generator for free, is selected for providing the required cooling effect. Furthermore the excess heating power of engine exhaust gas is used in an Organic Rankine Cycle (ORC) to generate electricity for selling to the grid. The proposed ERC-ORC configuration is novel, as the generator of ERC uses the rejecting heating power of ORC condenser. Modeling and optimizing the proposed ERC-ORC configuration are performed here for four selected gas engines. For example, results for 1948 MW gas engine integrated with ERC-ORC show that the ejector refrigeration system provides 271.1 kW cooling capacity with 0.33 coefficient of performance (COP) which decreases the transformer oil temperature for 20.2 °C and increases the transformer capacity for about 20%. Furthermore, 225.6 kW power output by the ORC system with 26.2% thermal efficiency is also generated.

Smart bin monitoring system for smart waste management

The fourth industrial revolution offers new technologies and solutions to increase efficiency, availability, flexibility, and decrease the economical footprint of manufacturing and service processes. In smart cities, a wide range of Industry 4.0 technologies can be used in the field of road traffic monitoring, health monitoring, and many operations, like the municipal waste collection. Internet of Things makes it possible to reduce the required material handling solutions of municipal waste collection, like loading and unloading, transportation, and warehousing. With smart waste management, no need for trucks to come every day and check every single dustbin if it is full or not as in the traditional situation, therefore the human power, time, cost, and spreading of toxic gas will be reduced. The amounts of the garbage will be monitored by sensors, pollution level by moisture sensor, and an odor sensor. The collected data can also be used to find the optimal path for the truck’s drivers. Within the frame of this article, the authors describe an on-line smart bin monitoring system.