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Journal articles on the topic 'Urban optical network reliability'
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1
Dilmurod, Abdujalilovich Davronbeko, Karimovich Matyokubov O'tkir, and Alimboyevich Matqurbanov To'lqin. "RELIABILITY RESEARCH IS URBAN OPTICAL NETWORK." CENTRAL ASIAN JOURNAL OF EDUCATION AND COMPUTER SCIENCES (CAJECS) 1, no. 1 (2022): 28–33. https://doi.org/10.5281/zenodo.7247997.
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This article analyzes the structure of the optical communication network of a small city and considers the integration of traditional telephone networks with new generation converged networks during its modernization. This allows users to meet the needs of modern telecommunications services and create highly reliable communication networks. It involves the use of PON (Passive Optical Network) technology. The structure of PON technology in different topologies has been analyzed and the reliability of the selected topology has been evaluated.
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Yang, Jing. "Optimization of Logistics Distribution Network based on Ant Colony Optimization Neural Network Algorithm." Scalable Computing: Practice and Experience 25, no. 5 (2024): 3641–50. http://dx.doi.org/10.12694/scpe.v25i5.3203.
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In order to improve the timeliness of logistics distribution, based on the theory of road network smoothness and reliability, the author conducted a study on the optimization of urban logistics distribution and transportation networks based on smoothness and reliability. The concept of logistics distribution and transportation network smoothness and reliability was proposed, and a logistics distribution and transportation network optimization model was established. The solving process of ant colony algorithm was given, and finally, a comparative analysis of a case was conducted. The results showed that: With a 6% increase in total delivery distance, the reliability of the delivery network has increased by 30%. This indicates that when using the model built by the author for distribution network optimization, effective optimization of network smoothness and reliability can be achieved, while only increasing the distance by a small amount. The optimal reliability of a smooth distribution network means that the probability of delivery delays is minimized, which is the most powerful guarantee for the effective accessibility of delivery. Verified the practicality of the constructed model. The proposed logistics distribution network optimization model has practical significance in guiding decision-making for optimizing urban logistics distribution transportation networks and reducing uncertainty in the process of urban logistics distribution.
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Madryas, C., and A. Kuliczkowski. "Reliability of Sewage Systems as an Element of Environmental Protection in Urban Areas." Water Science and Technology 27, no. 5-6 (1993): 197–205. http://dx.doi.org/10.2166/wst.1993.0499.
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This paper discusses some results of research into reliability engineering for urban sewerage networks, and the possibility of parameter estimation for particular reliability functions so as to establish a database which will enable operational control of the network and its renovation programme. A description and classification of the network failures is proposed for the sewers and the mechanism of their effects upon the soil-water environment will be presented. Very serious consequences are indicated for parametric failures of the networks operated without any program of regular technical state supervision, in the first place without network integrity inspection. The paper aims to underpin the theoretical background for optimal coordination of the renovation process, based upon typical technologies applied nowadays.
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Bozorg-Haddad, Omid, Milad Latifi, Atiyeh Bozorgi, Mohammad-Mehdi Rajabi, Seyed-Taghi Naeeni, and Hugo A. Loáiciga. "Development and application of the anarchic society algorithm (ASO) to the optimal operation of water distribution networks." Water Supply 18, no. 1 (2017): 318–32. http://dx.doi.org/10.2166/ws.2017.117.
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Abstract Optimizing the design and operation of urban water distribution networks (WDNs) is a complex, nonlinear problem. The optimization of WDNs can be performed for the pumping schedule, the location and elevation of reservoirs, the physical characteristics of pipes, and the placement of pressure-reducing valves, among other objectives. This study applies the anarchic society optimization (ASO) algorithm to find the optimal location and elevation of auxiliary tanks in urban water networks. The ASO is validated with mathematical benchmark functions, and is implemented to determine the location and elevation of auxiliary tanks in two urban water networks. The fuzzy reliability index for urban water network ranges between 74 and 79%, which is close to the global optima. The ASO exhibited better performance optimizing the reliability of WDNs than the genetic algorithm.
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Martyushev, Nikita V., Boris V. Malozyomov, Vladislav V. Kukartsev, et al. "Determination of the Reliability of Urban Electric Transport Running Autonomously through Diagnostic Parameters." World Electric Vehicle Journal 14, no. 12 (2023): 334. http://dx.doi.org/10.3390/wevj14120334.
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The urban transport network involves complex processes, operating 24 h a day and 365 days a year. The sustainable development of the urban transport network using electric buses and trolleybuses that run autonomously is an urgent task since the transport network performs integral social functions and is the transport artery of any urban center. The social and economic life of a city as a whole depends on the reliability of the transportation network. A theory is proposed for the technical and economic evaluation of reliability improvement in electric buses and trolleybuses running autonomously, which enables the determination of the reliability parameters of electric buses and forecasts for the future from the point of view of optimal economic costs for the operation of electric equipment in electric buses. As a result of the application of the proposed theory, it was found that increasing the reliability of the transportation fleet can lead to a decrease in both specific operating costs and capital investments in the development of the fleet. This is achieved as a result of increasing the annual productivity of vehicles by reducing the time they are out of service to eliminate the consequences of failures and carry out maintenance and repair. The conducted experiments confirmed that the theory and methodology of optimal reliability level selection not only enable the rational use of the material resources of the urban transport network but also the release of funds for its scientific and technical development by reducing the number of failures in the electrical equipment of transport systems by 14%.
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Hong, Rongrong, Huan Liu, Chengchuan An, Bing Wang, Zhenbo Lu, and Jingxin Xia. "An MFD Construction Method Considering Multi-Source Data Reliability for Urban Road Networks." Sustainability 14, no. 10 (2022): 6188. http://dx.doi.org/10.3390/su14106188.
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Road network traffic management and control are the key mechanisms to alleviate urban traffic congestion. With this study, we aimed to characterize the traffic flow state of urban road networks using the Macroscopic Fundamental Diagram (MFD) to support area traffic control. The core property of an MFD is that the network flow is maximized when network traffic stays at an optimal accumulation state. The property can be used to optimize the temporal and spatial distribution of traffic flow with applications such as gating control. MFD construction is the basis of these MFD-based applications. Although many studies have been conducted to construct MFDs, few studies are dedicated to improving the accuracy considering the reliability of different sources of data. To this end, we propose an MFD construction method using multi-source data based on Dempster–Shafer evidence (DS evidence) theory considering the reliability of different data sources. First, the MFD was constructed using VTD and CSD, separately. Then, the fused MFD was derived by quantifying the reliability of different sources of data for each MFD parameter based on DS evidence theory. The results under real data and simulated data show that the accuracy of the constructed MFDs was greatly improved considering the reliability of different data sources (the maximum MFD estimation error was reduced by 22.3%). The proposed method has the potential to support the evaluation of traffic operations and the optimization of signal control schemes for urban traffic networks.
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Pliuhin, Vladyslav, Gennadii Loktionov, Taras Sachoshko, Anatolii Zhylin, and Denys Haponov. "Optimization Of The Urban Power Supply Network." Lighting Engineering & Power Engineering 63, no. 3 (2024): 101–10. https://doi.org/10.33042/2079-424x.2024.63.3.04.
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The paper is devoted to the development of a methodology for reducing the cost of cable products during the construction of low-voltage networks of urban micro-districts, as well as minimizing the impact of the human factor during design. To achieve this goal, an optimization mechanism is proposed, which is based on the use of the Cartesian product of sets in combination with the gradient descent algorithm. In the optimization process, the best options for connecting consumers to substations are searched, which consider the optimal load parameters and cable line lengths. The optimal grouping of consumers be-tween substations is also studied, which ensures the effective distribution of energy re-sources. The developed approach includes automated calculation of the obtained options with their subsequent optimization according to the criteria of uniform loading of each substation and the minimum total length of low-voltage cable lines in the micro-district. This allows not only to increase the efficiency of network design, but also to ensure significant savings in material resources and time. The proposed methodology can be used to design new neighborhoods or modernize existing power supply networks, contributing to their greater reliability and cost-effectiveness.
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Ramani, Katineni, G. K. Rudraswamy, and Nanduri V. Umamahesh. "Optimal Design of Intermittent Water Distribution Network Considering Network Resilience and Equity in Water Supply." Water 15, no. 18 (2023): 3265. http://dx.doi.org/10.3390/w15183265.
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In urban areas of developing countries, due to industrialization and population growth, water demand has been increasing significantly, thereby increasing stress on the existing water distribution systems (WDSs). Under these circumstances, maintaining equity in the allocation of water becomes a significant challenge. When building an intermittent water distribution system, it is important to provide a minimum level of supply that is acceptable as well as water supply equity. A non-dominated sorting genetic algorithm (NSGA-II) is employed for the optimal design of an intermittent water distribution network (WDN). Network resilience is taken as a measure of reliability (In), while the uniformity coefficient (CU) is taken as a measure of equity in the water supply. Maximizing network resilience, uniformity coefficient, and minimization of cost of the network are considered as the objectives in the multi-objective optimization model. Pressure-driven analysis (PDA) is used for the hydraulic simulation of the network. The NSGA-II model is applied and demonstrated over two water distribution networks taken from the literature. The results indicate that reliability and equity in WDNs can be accomplished to a reasonable extent with minimal cost.
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Krstivojević, Jelisaveta, and Jelena Stojković Terzić. "Enhancing Reliability Performance in Distribution Networks Using Monte Carlo Simulation for Optimal Investment Option Selection." Applied Sciences 15, no. 8 (2025): 4209. https://doi.org/10.3390/app15084209.
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Limited financial resources significantly impact the ability of distribution system operators to prioritize maintenance, upgrade infrastructure, and integrate advanced technologies. To optimize resource allocation, a structured and detailed analysis is essential for maximizing reliability improvements within budget constraints. This paper presents a methodology for enhancing the reliability performance of semi-urban and rural distribution networks by identifying optimal investment strategies under financial limitations. Investment options are categorized into three groups: (1) installing new components where none previously existed, (2) replacing aging, higher-failure-rate equipment with new components, and (3) upgrading both network components and operational strategies. To determine the most effective investments, the selection process aims to minimize the System Average Interruption Duration Index (SAIDI) and Energy Not Supplied (ENS), while also considering an economic metric that quantifies reliability in monetary terms. The methodology was tested on networks with diverse consumer types, incorporating Monte Carlo simulation to account for uncertainties in component reliability indices and node loads. An optimization algorithm was developed, implemented, and validated using representative test networks, demonstrating its effectiveness in guiding investment decisions for improved distribution system reliability.
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Silva, Luis Guilherme, Israel Cardoso, Carlos Brito, et al. "Urban Advanced Mobility Dependability: A Model-Based Quantification on Vehicular Ad Hoc Networks with Virtual Machine Migration." Sensors 23, no. 23 (2023): 9485. http://dx.doi.org/10.3390/s23239485.
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In the rapidly evolving urban advanced mobility (UAM) sphere, Vehicular Ad Hoc Networks (VANETs) are crucial for robust communication and operational efficiency in future urban environments. This paper quantifies VANETs to improve their reliability and availability, essential for integrating UAM into urban infrastructures. It proposes a novel Stochastic Petri Nets (SPN) method for evaluating VANET-based Vehicle Communication and Control (VCC) architectures, crucial given the dynamic demands of UAM. The SPN model, incorporating virtual machine (VM) migration and Edge Computing, addresses VANET integration challenges with Edge Computing. It uses stochastic elements to mirror VANET scenarios, enhancing network robustness and dependability, vital for the operational integrity of UAM. Case studies using this model offer insights into system availability and reliability, guiding VANET optimizations for UAM. The paper also applies a Design of Experiments (DoE) approach for a sensitivity analysis of SPN components, identifying key parameters affecting system availability. This is critical for refining the model for UAM efficiency. This research is significant for monitoring UAM systems in future cities, presenting a cost-effective framework over traditional methods and advancing VANET reliability and availability in urban mobility contexts.
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Torres-Zapata, Edmundo, Victor Guerra, Jose Rabadan, Martin Luna-Rivera, and Rafael Perez-Jimenez. "VLC Network Design for High Mobility Users in Urban Tunnels." Sensors 22, no. 1 (2021): 88. http://dx.doi.org/10.3390/s22010088.
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Current vehicular systems require real-time information to keep drivers safer and more secure on the road. In addition to the radio frequency (RF) based communication technologies, Visible Light Communication (VLC) has emerged as a complementary way to enable wireless access in intelligent transportation systems (ITS) with a simple design and low-cost deployment. However, integrating VLC in vehicular networks poses some fundamental challenges. In particular, the limited coverage range of the VLC access points and the high speed of vehicles create time-limited links that the existing handover procedures of VLC networks can not be accomplished timely. Therefore, this paper addresses the problem of designing a vehicular VLC network that supports high mobility users. We first modify the traditional VLC network topology to increase uplink reliability. Then, a low-latency handover scheme is proposed to enable mobility in a VLC network. Furthermore, we validate the functionality of the proposed VLC network design method by using system-level simulations of a vehicular tunnel scenario. The analysis and the results show that the proposed method provides a steady connection, where the vehicular node is available more than 99% of the time regardless of the number of vehicular nodes on this network. Additionally, the system is able to achieve a Frame-Error-Rate (FER) performance lower than 10−3.
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Ye, Fan, Qiang Xiao, Shiling Zhang, Mi Zhang, Ruizhang Wang, and Yu Bai. "Reliability expansion method of urban distribution network based on mixed integer programming and multi-objective optimization." Journal of Physics: Conference Series 2728, no. 1 (2024): 012085. http://dx.doi.org/10.1088/1742-6596/2728/1/012085.
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Abstract The power supply system in urban area has high complexity, and its expansion is difficult. Therefore, a reliability expansion method of urban distribution network based on mixed integer programming and multi-objective optimization is proposed in this paper. Considering the economic benefits and voltage difference of investment and operation, a general model for optimizing the overall installation of the power grid has been established. Enable particle swarm optimization algorithm to increase the energy storage capacity of the power grid and solve the optimal expansion rate through mixed integer linear programming. Finally, research has shown that this research method can achieve the best scaling effect.
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Bai, Longju. "Reconfiguration Performance of the Urban Power Distribution System Based on the Genetic-Ant Colony Fusion Algorithm." E3S Web of Conferences 257 (2021): 02062. http://dx.doi.org/10.1051/e3sconf/202125702062.
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This study aims to enhance the reliability of the urban power grid system and decrease the economic loss due to power network faults. Based on the analysis of the traditional algorithms for restructuring the urban distribution system after faults, this study proposes an upgraded genetic algorithm (GA) and ant colony algorithm (ACA) and combines these two to overcome the limitations of the local optimum of GAs and low convergence speed of ACAs. Taking the IEEE33-node system as the research object, the network loss, maximum recovery of the power-loss load, and the number of switching operations as the objective function, the impact of different algorithms on the restoration and reconfiguration of the distribution system was examined according to MATLAB system simulation and the optimal algorithm for the reconfiguration of the urban distribution system failure recovery. The experimental results revealed that compared with the current distribution system reconfiguration algorithm, the genetic-ant colony algorithm (GACA) has higher algorithm time efficiency and solution accuracy and can markedly decrease the recovery time and improve the impact of the distribution system in a short period. Overall, the proposed GACA is an efficient self-healing algorithm of urban distribution systems and useful for augmenting the reliability of the urban power system.
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Tanjung, Dion, Seunggyu Byeon, Junhwan Huh, Dong Hyun Kim, and Jong Deok Kim. "Opportunistic and On-Demand Network Coding-Based Solutions for LPWAN Forwarding." Sensors 20, no. 20 (2020): 5792. http://dx.doi.org/10.3390/s20205792.
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The single-hop star-of-stars topology in low-power and wide-area networks (LPWAN) exhibits reliability and substandard coverage issues, especially in urban areas where line-of-sight (LoS) communication is difficult to achieve. Moreover, LPWAN trade-off the data rate to achieve longer coverage, preventing other end-devices from using the time resource. Locating other gateways is uneconomical as it requires infrastructure, such as the internet and a power connection. In this study, we propose a forwarding scheme with a relay to increase LPWAN coverage and reliability while not degrading the network’s capacity. A relay tends to incur unnecessary forwarding that degrades the network capacity unless proper countermeasure is prepared. Our works, namely opportunistic and on-demand network coding (OODC), minimize unnecessary forwarding and make good use of multiple-receiving relays. Network coding is also applied in the relay for better transmission efficiency and reliability simultaneously. Because network coding occurs header overhead, we perform a header compression technique to counter it. According to our simulation result, our method shows better reliability than fixed path forwarding. In an adaptive data rate settings, the OODC achieves a 92% packet delivery ratio (PDR), whereas a fixed-path forwarding only achieves an 84% PDR.
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Researcher. "POWERING THE FUTURE: A COMPREHENSIVE STUDY ON UPGRADING CHHATRAPATI SAMBHAJI NAGAR'S TRANSMISSION INFRASTRUCTURE." International Journal of Electrical Engineering and Technology (IJEET) 15, no. 5 (2024): 1–14. https://doi.org/10.5281/zenodo.13902252.
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This paper presents a comprehensive analysis of the 132kV and 220kV substations in Chhatrapati Sambhaji Nagar, Maharashtra, under the operational jurisdiction of MSETCL (Maharashtra State Electricity Transmission Company Limited). With a view towards enhancing network reliability, addressing load growth, and preparing for future urban and industrial demands, a new network proposal is presented. This proposal aligns with the upcoming State Transmission Utility (STU) plan and aims to improve transmission efficiency through strategic substation upgrades, the formation of a 132kV ring network, and optimal feeder realignments.
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Zhou, Jing, and Yunhong Shao. "Rational Selection of Rail Transit Emergency Site Using Complex Network Topology and Genetic Algorithm." Scientific Programming 2022 (February 24, 2022): 1–8. http://dx.doi.org/10.1155/2022/6420806.
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Rail transit network is a convenient and reliable transportation mode in urban areas. With every surge in transportation demand, the network undergoes operational changes like restructuring and making of multiline tracks. Urban rail transit network is a complex network and needs proper emergency services and controlling mechanisms. Unexpected mishaps in rail transit will cause more hazard and panic than the other transportation systems. Therefore, a reliable emergency service station is required to ensure the safety and security of passengers. In the proposed method, the basic statistical properties of complex network topology are considered to construct a P-center site selection model for urban rail transit emergency service stations. The P-center site selection model is solved by genetic algorithm. Validity and reasonableness of the model are demonstrated by implementing it in the Hangzhou emergency service stations for rail transportation. The results show that the P-center site selection model based on statistical properties of complex network topologies can better solve the urban rail transit emergency service station site selection problems. The model minimizes the number of emergency service stations while satisfying the optimal objective function and reduces the construction cost of emergency service stations. The approach has a significant effect on improving system reliability and reducing the risk of emergencies.
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Masharipov, Otoboy Matyoqubovich. "On The Possibility of Improving the Reliability of Communication in Fiber-Optic Systems with Spectral Compaction." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 3 (2020): 2210–14. https://doi.org/10.35940/ijeat.C4832.029320.
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In the article, the authors present a concrete example of a block diagram of a signal transmission device at WDM. Operation of this device with the representation of plots of pulse diagram of operation at standard characteristics of services and evaluation of their quality indicators depending on the fault tolerance in the whole system under study. Recommendations for practical use in various types of network topology are given. Spectral compaction technologies such as CWDM, DWDM, HDWDM, principles of construction of these technologies, as well as advantages and disadvantages are considered. The functional schemes of the signal transmission device and the functional scheme of the optical transceiver and the principle of operation of these devices are given. The frequency plan for CWDM systems is defined by ITU G. 694.2. The scope of CWDM technology is urban networks with a distance of up to 50 km. The advantage of this type of WDM systems is low (compared to other types) the cost of equipment due to lower requirements for the constituent equipment of the fiber optic network. The frequency plan for DWDM systems is defined by ITU G. 694.1. The field of application — backbone network. This kind of WDM systems has higher requirements for components than CWDM (radiation source spectrum width, source temperature stabilization, etc.). The impetus for the rapid development of DWDM networks was given by the appearance of inexpensive and efficient fiber erbium amplifiers (EDFA) operating in the range from 1525 to 1565 nm (the third window of transparency of quartz fiber). For simplicity, the model is limited to a frequency plan DWDM with a step of 100 GHz, and CWDM has eight main channels in the range of 1470-1610 nm. The calculations of reliability indicators of the basic version and the modified version of the signal transmission device are given.
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Shabrina, Anggi. "ANALISIS IMPLEMENTASI FREQUENCY DIVERSITY TERHADAP NILAI AVAILABILITY SYSTEM PADA WILAYAH URBAN DAN RURAL." Jurnal Elektro dan Telekomunikasi Terapan 7, no. 1 (2020): 805. http://dx.doi.org/10.25124/jett.v7i1.2932.
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The widely used transmission media, one of which is transmission media using microwave. Microwaves are still needed today as not all locations allow for network performances using cables, in addition to the influence of small natural disasters, and are more practical to implement in urban and rural areas. But in the use of micro wave transmission there are constraints that can cause the transmission process to experience interference in the process of conveying information. One obstacle that affects transmission of radio waves is the presence of fading effect that causes the decline in the receiving power and damage transmission quality. Therefore, the optimization process is necessary to increase the availability of the microwave communication system. The use of a diversity technique can increase the value of system reliability. In this research the diversity technique used is frequency diversity. The result of the design simulation of microwave transmission network in this study obtained the value of system reliability before using the diversity technique of 99.99348%. Whereas after using frequency diversity technique obtained the result of 99.99934%. The final result of this simulation is as expected by the application of frequency diversity technique will optimize service to users with a system reliability level of 0.00586% more optimal.
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Chicherin, Stanislav. "The Reliability and Efficiency of Medium-Temperature District Heating." St. Petersburg Polytechnic University Journal of Engineering Science and Technology 23, no. 02 (2017): 75–80. https://doi.org/10.18721/JEST.230207.
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The goal of this paper is to provide a scenario and a methodology that focuses on solutions for optimal network design to enable failure-free operation.If both reliability and energy-effi ciency are the focus targets, low operating temperatures are desirable in a district heating system, from standpoint of the distribution network and the heat source. The equivalent diameter of the network using the medium pipe diameter, its length, and the total network length was defined. For simplification, we propose to determine the calculated and the standard heat losses by modeling the object of research using mathematical flow distribution models implemented in the corresponding geoinformation systems and software simulation package complexes (for example, Zulu). An urban area of the town of Barabinsk was designated as a test site; the area represented the attributes of many communities across Russia. We have proposed a concept for introducing medium-temperature district heating systems and a method of using existing tools to justify its implementation. The procedure we have developed allows to quickly compare the generalized technical and economic indicators of various reconstruction options for such facilities without resorting to purely economic characteristics and monetary indicators. We aimed at organizing the successive steps of a typical feasibility study, pointing out the critical issues and discussing the possible solutions. We applied the methodology to a specific case study, but it can be applied elsewhere, after making sure that the economic and technical input data match the actual conditions of the site considered. Medium-temperature district heating had a better energy performance than high-temperature district heating, decreasing the heat loss by approximately 5%. The sizes of the pipes size equivalent and the only difference was the necessity of using steel pipes. The low-temperature networks required more energy and additional capital investment. At the same time, the introduction of low-temperature heating should be considered as a long-term measure, since from a socio-economic standpoint this will allow to connect individual renewable energy sources and consumers using heat power with a high effi ciency to the existing heat networks.
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Boubaker, Sahbi, Noha Hamdy Radwan, Moatamad Refaat Hassan, Faisal S. Alsubaei, Ahmed Younes, and Hameda A. Sennary. "Robust Design Problem for Multi-Source Multi-Sink Flow Networks Based on Genetic Algorithm Approach." Mathematics 11, no. 18 (2023): 3902. http://dx.doi.org/10.3390/math11183902.
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Robust design problems in flow networks involve determining the optimal capacity assignments that enable the network to operate effectively even in the case of events’ occurrence such as arcs or nodes’ failures. Multi-source multi-sink flow networks (MMSFNs) are frequent in many real-life systems such as computer and telecommunication, logistics and supply-chain, and urban traffic. Although numerous studies on the design of MMSFNs have been conducted, the robust design problem for multi-source multi-sink stochastic-flow networks (MMSFNs) remains unexplored. To contribute to this field, this study addresses the robust design problem for MMSFNs using an approach of two steps. First, the problem is mathematically formulated as an optimization problem and second, a sub-optimal solution is proposed based on a genetic algorithm (GA) involving two components. The first component, an outer genetic algorithm, is employed to search the optimal capacity assigned to the network components with minimum sum. The second component, an inner genetic algorithm, is used to find the optimal flow vectors that maximize the system’s reliability. Through extensive experimentation on three different networks with different topologies, the proposed solution has been found to be efficient.
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Renzler, Tobias, Michael Stolz, and Daniel Watzenig. "Feudalistic Platooning: Subdivide Platoons, Unite Networks, and Conquer Efficiency and Reliability." Sensors 22, no. 12 (2022): 4484. http://dx.doi.org/10.3390/s22124484.
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Cooperative intelligent transportation systems (C-ITSs) such as platooning rely on a robust and timely network that may not always be available in sufficient quality. Out of the box hybrid networks only partly eliminate shortcomings: mutual interference avoidance, data load balancing, and data dissemination must be sophisticated. Lacking network quality may lead to safety bottlenecks that require that the distance between the following vehicles be increased. However, increasing gaps result in efficiency loss and additionally compromise safety as the platoon is split into smaller parts by traffic: maneuvers, e.g., cut-in maneuvers bear safety risks, and consequently lower efficiency even further. However, platoons, especially if they are very long, can negatively affect the flow of traffic. This mainly applies on entry or exit lanes, on narrow lanes, or in intersection areas: automated and non-automated vehicles in traffic do affect each other and are interdependent. To account for varying network quality and enable the coexistence of non-automated and platooned traffic, we present in this paper a new concept of platooning that unites ad hoc—in form of IEEE 802.11p—and cellular communication: feudalistic platooning. Platooned vehicles are divided into smaller groups, inseparable by surrounding traffic, and are assigned roles that determine the communication flow between vehicles, other groups and platoons, and infrastructure. Critical vehicle data are redundantly sent while the ad hoc network is only used for this purpose. The remaining data are sent—relying on cellular infrastructure once it is available—directly between vehicles with or without the use of network involvement for scheduling. The presented approach was tested in simulations using Omnet++ and Simulation of Urban Mobility (SUMO).
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BenRhouma, Ons, Chiheb Rebai, Manel Ben-Romdhane, Dario Di Cara, Giovanni Artale, and Nicola Panzavecchia. "The Environmental Impacts of Radio Frequency and Power Line Communication for Advanced Metering Infrastructures in Smart Grids." Sensors 23, no. 24 (2023): 9621. http://dx.doi.org/10.3390/s23249621.
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In the neighborhood area network (NAN), the advanced metering infrastructure (AMI) enables a bidirectional connection between the smart meter (SM) and the data concentrator (DC). Sensors, such as smart meter nodes or environmental sensor nodes, play a crucial role in measuring and transmitting data to central units for advanced monitoring, management, and analysis of energy consumption. Wired and wireless communication technologies are used to implement the AMI-NAN. This paper delves into a novel approach for optimizing the choice of communication medium, air for radio frequency (RF) or power lines for power line communication (PLC), between the SM and DC in the context of the AMI-NAN. The authors methodically select the specific technologies, RF and NB-PLC (narrowband power line communication), and meticulously characterize their attributes. Then, a comparative analysis spanning rural, urban, and industrial settings is conducted to evaluate the proposed method. The overall reliability performance of the AMI-NAN system requires a packet error rate (PER) lower than 10%. To this end, an efficient approach is introduced to assess and enhance the reliability of NB-PLC and RF for AMI-NAN applications. Simulation results demonstrate that wireless communication is the optimal choice for the rural scenario, especially for a signal-to-noise ratio (SNR) lower than 25 dB. However, in urban environments characterized by higher SNR values and moderately dense networks, NB-PLC gains prominence. In denser networks, it outperforms wireless communication, exhibiting a remarkable 10 dB gain for a bit error rate (BER) of 10−3. Moreover, in industrial zones characterized by intricate network topologies and non-linear loads, the power line channel emerges as the optimal choice for data transmission.
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Yao, Gang, Su Fei Liu, and Jia Jin. "Complex Urban Distribution Network Wiring Pattern Matching Research Related to the Load Density." Advanced Materials Research 860-863 (December 2013): 2137–42. http://dx.doi.org/10.4028/www.scientific.net/amr.860-863.2137.
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With the rapid advance of the urbanization process, the majority of cities come into the size of millions or more population. Therefore, the urban distribution network are becoming complex increasingly accordingly.How to meet the needs of complex urban distribution network safety and reliable power supply quality, reasonable construction investment better is one of the problems that plagued powered enterprise.It is an important research topic that wiring mode are choosed with good indicator of safe and high reliability, power supply quality and reasonable construction investment, combination load density characteristics of different medium-sized cities in the electricity sector. We have constructed a wiring mode analysis platform in this paper, it can calculate various operation indicators in different wiring mode by load density as the basic parameter variables.The adaptability of different wiring mode can be assessed comprehensively, and the optimal distribution network connection mode is selected in the different load density.
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Phuchortham, Sabai, and Hakilo Sabit. "A Survey on Free-Space Optical Communication with RF Backup: Models, Simulations, Experience, Machine Learning, Challenges and Future Directions." Sensors 25, no. 11 (2025): 3310. https://doi.org/10.3390/s25113310.
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As sensor technology integrates into modern life, diverse sensing devices have become essential for collecting critical data that enables human–machine interfaces such as autonomous vehicles and healthcare monitoring systems. However, the growing number of sensor devices places significant demands on network capacity, which is constrained by the limitations of radio frequency (RF) technology. RF-based communication faces challenges such as bandwidth congestion and interference in densely populated areas. To overcome these challenges, a combination of RF with free-space optical (FSO) communication is presented. FSO is a laser-based wireless solution that offers high data rates and secure communication, similar to fiber optics but without the need for physical cables. However, FSO is highly susceptible to atmospheric turbulence and conditions such as fog and smoke, which can degrade performance. By combining the strengths of both RF and FSO, a hybrid FSO/RF system can enhance network reliability, ensuring seamless communication in dynamic urban environments. This review examines hybrid FSO/RF systems, covering both theoretical models and real-world applications. Three categories of hybrid systems, namely hard switching, soft switching, and relay-based mechanisms, are proposed, with graphical models provided to improve understanding. In addition, multi-platform applications, including autonomous, unmanned aerial vehicles (UAVs), high-altitude platforms (HAPs), and satellites, are presented. Finally, the paper identifies key challenges and outlines future research directions for hybrid communication networks.
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Putra, Fauzan Prasetyo Eka, Ubaidi Ubaidi, Mohammad Aziz, Moh Irfan, and Royfal Alim. "Improving Network Service Quality in parts of Sampang City: QoS Evaluation and User Perception of QoE." Brilliance: Research of Artificial Intelligence 4, no. 1 (2024): 408–12. http://dx.doi.org/10.47709/brilliance.v4i1.4311.
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In an era of rapid urbanization, the quality of network services in urban environments is becoming increasingly important. This article explores efforts to improve network service quality in several sampang cities through an evaluation of Quality of Service (QoS) and user perceptions of Quality of Experience (QoE). The research is based on a survey conducted at various locations in sampang city to collect data on the reliability, speed, and availability of network services. The survey involved a diverse sample of users, covering a wide range of ages, professions, and levels of technology usage. In addition, we also analyzed users' perceptions of service quality based on their experiences of using the network in an urban environment. The results highlighted several key challenges in improving QoS, such as user density, signal interference, and network infrastructure limitations. However, we also found that strategies such as the use of advanced network technologies, such as 5G and beamforming, as well as traffic prioritization based on application type, can help to significantly improve QoS. In addition, we found a strong positive correlation between improved QoS and improved QoE, suggesting that improved quality of service has a direct impact on improving user experience. These findings provide valuable insights for network operators and policy makers in their efforts to improve network services in dense urban environments. The research also recommends further investment in network technologies and the development of policies that support more effective management of network traffic to ensure optimal quality of service.
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Sun, Yi, Sirui Wang, Xiang Xu, and Liang Shen. "Identification of critical links based on the optimal reliable path in stochastic traffic networks." PLOS ONE 19, no. 4 (2024): e0301272. http://dx.doi.org/10.1371/journal.pone.0301272.
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In urban stochastic transportation networks, there are specific links that hold great importance. Disruptions or failures in these critical links can lead to reduced connectivity within the road network. Under this circumstance, this manuscript proposed a novel identification of critical links mathematical optimization model based on the optimal reliable path with consideration of link correlations under demand uncertainty. The method presented in this paper offers a solution to bypass the necessity of conducting a full scan of the entire road network. Due to the non-additive and non-linear properties of the proposed model, a modified heuristic algorithm based on K-shortest algorithm and inequality technical is presented. The numerical experiments are conducted to show that improve a certain road link may not necessarily improve the overall traffic conditions. Moreover, the results indicate that if the travel time reliability is not considered, it will bring errors to the identification of key links.
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Sun, Baofeng, Jiaojiao Liu, Junyi Hao, Xiuxiu Shen, Xinhua Mao, and Xianmin Song. "Maintenance Decision-Making of an Urban Rail Transit System in a Regionalized Network-Wide Perspective." Sustainability 12, no. 22 (2020): 9734. http://dx.doi.org/10.3390/su12229734.
Full textAbstract:
The networked operation of Urban Rail Transit (URT) brings the new challenge of network-wide maintenance. This research focuses on the URT Network-Wide Maintenance Decision-Making Problem (URT-NMDP), including regionalized maintenance network design and maintenance resource allocation. In this work, we proposed a bi-objective integer programming model that integrates the characteristics of set coverage and P-median models, resulting in the regionalized maintenance network design model. Some critical factors are considered in the model, such as the importance of node, the maximum failure response time, and maintenance guarantee rules. We designed a NSGA-II based algorithm to solve the model. Moreover, due to the uncertainty of failures in the URT network, we developed the method of allocating maintenance resources based on Monte Carlo simulation to strengthen the reliability of the regionalized maintenance network. With the model and algorithm presented in this work, we obtained Pareto optimal solutions of URT-NMDP, i.e., URT network-wide maintenance planning schemes, which include the number and location of maintenance points, the allocation of demand points, and the amount of maintenance units. Finally, a real-world case is studied to evaluate the operating performance of these schemes for verifying the method in our paper. The results of the case study demonstrate that the reasonable and tested-in-practice maximum failure response time is the precondition for the efficient URT maintenance network. The maintenance scheme considered the weighted importance of node shows the optimal performance, with the shortest overall maintenance path and the minimum average failure response time and investment cost on maintenance resources.
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Fang, Hui, and Wei Zhang. "Optimization and Application of Communication Resource Allocation Algorithm for Urban Rail Transit Planning." Computational Intelligence and Neuroscience 2022 (August 25, 2022): 1–9. http://dx.doi.org/10.1155/2022/5608665.
Full textAbstract:
The construction and operation of China’s rail transit system have entered a high-speed development stage, and the rapid increase of train speed and mileage has brought greater challenges to the safety and reliability of the rail transit system. Network planning evaluation is the key to the early decision-making of urban rail transit project, which directly determines the success or failure of the whole project. How to scientifically and reasonably evaluate the urban rail transit information resource network planning has become a difficult problem for many urban planners to solve. Therefore, this paper studies the optimization of the communication resource allocation algorithm and the comprehensive evaluation of its application for urban rail transit planning. In this paper, based on CVNN structure, the network prototype is an extension of RVNN structure. In the abstract, its processing unit is composed of a pair of real-number processors that can realize certain operations. HNN is a fully connected recurrent neural network based on the idea of the energy function, which is helpful to understand the calculation mode of HNN, and the research shows that HNN can solve many combinatorial optimization problems. In addition, the combination of neural network and genetic algorithm with simulated annealing mechanism can also bring new directions for research. On the basis of experimental analysis, it can be concluded that in general, the error reduction rate of the optimization scheme designed in this paper can reach 58.6% on average. In practical application, the accuracy of the optimal bit error rate is 52.4%.
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Toledo, Karel, Hector Kaschel, and Mauricio Rodriguez. "Probabilistic Risk Assessment for Data Rate Maximization in Unmanned Aerial Vehicle-Assisted Wireless Networks." Drones 8, no. 10 (2024): 592. http://dx.doi.org/10.3390/drones8100592.
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The evolution of beyond fifth generation (B5G) wireless networks poses significant technical and economic challenges across urban, suburban, and rural areas, demanding increased capacity for users whose positions continually change. This study investigated the dynamic positioning of an unmanned aerial vehicle (UAV), acting as a mobile base station (MoBS) to enhance network efficiency and meet ground terminals (GTs) expectations for data rates, particularly in emergency scenarios or temporary events. While UAVs show great promise, existing research often assumes certainty in network architecture, overlooking the complexities of unpredictable user movements. We introduce a decision-making framework utilizing the ordered weighted averaging (OWA) operator to address uncertainties in GT locations, enabling the optimization of UAV trajectories to maximize the overall network data rate. An optimization problem is formulated by modeling GT dynamics through a Markov process and discretizing UAV movements while accounting for communication thresholds and movement constraints. Extensive simulations reveal that our approach significantly improves expected data rates by up to 48% compared to traditional fixed base stations (BSs) and predefined UAV movement patterns. This research underscores the potential of UAV-assisted networks to bolster communication reliability while effectively managing dynamic user movements to maintain optimal quality of service (QoS).
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Franchi, Fabio, Andrea Marotta, Claudia Rinaldi, Fabio Graziosi, Luciano Fratocchi, and Massimo Parisse. "What Can 5G Do for Public Safety? Structural Health Monitoring and Earthquake Early Warning Scenarios." Sensors 22, no. 8 (2022): 3020. http://dx.doi.org/10.3390/s22083020.
Full textAbstract:
The 5th generation of mobile networks has come to the market bringing the promise of disruptive performances as low latency, availability and reliability, imposing the development of the so-called “killer applications”. This contribution presents a 5G use case in the context of Structural Health Monitoring which guarantees an unprecedented level of reliability when exploited for public safety purposes as Earthquake Early Warning. The interest on this topic is at first justified through a deep market analysis, and subsequently declined in terms of public safety benefits. A specific sensor board, guaranteeing real-time processing and 5G connectivity, is presented as the foundation on which the architecture of the network is designed and developed. Advantages of 5G-enabled urban safety are then discussed and proven in the experimentation results, showing that the proposed architecture guarantees lower latency delays and overcome the impairments of cloud solutions especially in terms of delays variability.
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HNATUSHENKO, Володимир, Vita KASHTAN, Denys CHUMYCHOV, and Serhii NIKULIN. "COMPARATIVE ANALYSIS OF CLASSIFICATION METHODS FOR HIGH-RESOLUTION OPTICAL SATELLITE IMAGES." Computer systems and information technologies, no. 4 (December 26, 2024): 134–42. https://doi.org/10.31891/csit-2024-4-16.
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High-resolution satellite image classification is used in various applications, such as urban planning, environmental monitoring, disaster management, and agricultural assessment. Traditional classification methods are ineffective due to the complex characteristics of high-resolution multichannel images: the presence of shadows, complex textures, and overlapping objects. This necessitates selecting an efficient classification method for further thematic data analysis. In this study, a comprehensive assessment of the accuracy of the most well-known classification methods (parallelepiped, minimum distance, Mahalanobis distance, maximum similarity, spectral angle map, spectral information difference, binary coding, neural network, decision tree, random forest, support vector machine, K-nearest neighbour, and spectral correlation map) is performed. This study comprehensively evaluates various classification algorithms applied to high-resolution satellite imagery, focusing on their accuracy and suitability for different use cases. To ensure the robustness of the evaluation, high-quality WorldView-3 satellite imagery, known for its exceptional spatial and spectral resolution, was utilized as the dataset. To assess the performance of these methods, error matrices were generated for each algorithm, providing detailed insights into their classification accuracy. The average values along the main diagonal of these matrices, representing the proportion of correctly classified pixels, served as a key metric for evaluating overall effectiveness. Results indicate that advanced machine learning approaches, such as neural networks and support vector machines, consistently outperform traditional techniques, achieving superior accuracy across various classes. Despite their high average accuracy, a deeper analysis revealed that only some algorithms are universally optimal. For instance, some methods, such as random forests or spectral angle mappers, exhibited strength in classifying specific features like vegetation or urban structures but performed less effectively for others. This underscores the importance of tailoring algorithm selection to the specific objectives of individual classification tasks and the unique characteristics of the target datasets. This study can be used to select the most effective method of classifying the earth's surface, depending on the tasks of further thematic analysis of high-resolution satellite imagery. Furthermore, it highlights the potential of integrating machine learning-based approaches to enhance the accuracy and reliability of classification outcomes, ultimately contributing to more practical applications.
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Zhu, Zimin, Dongliang Nan, Qingxi Duan, Zhen Liu, and Xiaofang Wu. "Flexible DC Optimization Control Technology Based on Zonal Interconnection of Urban Power Grids." Electronics 13, no. 23 (2024): 4679. http://dx.doi.org/10.3390/electronics13234679.
Full textAbstract:
Aiming at the problems of insufficient power supply capacity, unbalanced load, and poor safety and reliability of the urban power grid, a flexible DC optimization control strategy is proposed to support the interconnection of power grid zones. Firstly, the steady-state and transient optimal control objectives are established to meet the safety and economic operation requirements of the grid; secondly, comprehensive evaluation indexes are constructed, covering load balancing, network loss, and voltage deviation, and a step-by-step approximation method is used to quickly solve the optimal power of the flexible DC, so as to realize the optimal control of the urban grid in the steady state. Meanwhile, a multi-terminal flexible DC adaptive sag control strategy based on the power margin of the converter station is designed to reasonably allocate the emergency power support in each partition after a fault and reduce the frequency deviation of the heavily loaded nodes. Taking the urban grid as an example, a simulation model of the grid structure with a 750 KV outer ring and a 220 KV inner ring is constructed, and the simulation results verify the effectiveness of the proposed method and its engineering practicability.
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Stavroulas, Iasonas, Georgios Grivas, Panagiotis Michalopoulos, et al. "Field Evaluation of Low-Cost PM Sensors (Purple Air PA-II) Under Variable Urban Air Quality Conditions, in Greece." Atmosphere 11, no. 9 (2020): 926. http://dx.doi.org/10.3390/atmos11090926.
Full textAbstract:
Recent advances in particle sensor technologies have led to an increased development and utilization of low-cost, compact, particulate matter (PM) monitors. These devices can be deployed in dense monitoring networks, enabling an improved characterization of the spatiotemporal variability in ambient levels and exposure. However, the reliability of their measurements is an important prerequisite, necessitating rigorous performance evaluation and calibration in comparison to reference-grade instrumentation. In this study, field evaluation of Purple Air PA-II devices (low-cost PM sensors) is performed in two urban environments and across three seasons in Greece, in comparison to different types of reference instruments. Measurements were conducted in Athens (the largest city in Greece with nearly four-million inhabitants) for five months spanning over the summer of 2019 and winter/spring of 2020 and in Ioannina, a medium-sized city in northwestern Greece (100,000 inhabitants) during winter/spring 2019–2020. The PM2.5 sensor output correlates strongly with reference measurements (R2 = 0.87 against a beta attenuation monitor and R2 = 0.98 against an optical reference-grade monitor). Deviations in the sensor-reference agreement are identified as mainly related to elevated coarse particle concentrations and high ambient relative humidity. Simple and multiple regression models are tested to compensate for these biases, drastically improving the sensor’s response. Large decreases in sensor error are observed after implementation of models, leading to mean absolute percentage errors of 0.18 and 0.12 for the Athens and Ioannina datasets, respectively. Overall, a quality-controlled and robustly evaluated low-cost network can be an integral component for air quality monitoring in a smart city. Case studies are presented along this line, where a network of PA-II devices is used to monitor the air quality deterioration during a peri-urban forest fire event affecting the area of Athens and during extreme wintertime smog events in Ioannina, related to wood burning for residential heating.
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Padmavathi*, T., Dr Kusma Kumari Cheepurupalli, and Dr R. Madhu. "Optimal Power Allocation and Capacity Analysis for D2D-Enabled Vehicular Communications." International Journal of Recent Technology and Engineering (IJRTE) 8, no. 4 (2019): 4110–16. http://dx.doi.org/10.35940/ijrte.d873141.118419.
Full textAbstract:
Wireless Communication is important to recover transmitted information by accommodating reliable Information flow to allow safety, mobility and environmental applications. In cellular communication resources are shared with the users to improve spectral reuse and enhance channel capacity. Device-to-Device (D2D) communication has become a promising technology for wireless engineers to optimize the network performance. In vehicular environment, the design of resource allocation schemes for D2D-enabled networks need to be properly addressed because of the fast channel variations due to high mobility. In this work, Radio Resource Management (RRM) for D2D-based V2X (Vehicle to Everything) communications including both vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication are implemented. Power is allocated based on slowly varying large-scale fading information of wireless channels of LTE standard The objective is to maximize the ergodic capacity of V2I connections by ensuring reliability for each V2V link. Sum ergodic capacity of all V2I links is first taken as the optimization goal to maximize the general V2I link throughput. Minimum ergodic capacity maximization is then taken into consideration to offer a more uniform capacity performance throughout all V2I links. Various algorithms that gives optimal power allocation are proposed and compared. Here, the capacity maximization between highway areas and urban areas are compared and concluded that capacity maximization will be higher in urban areas then on highways.
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Grudz, Ya V., R. B. Stasyuk, and M. Ya Krill. "Research on energy efficiency of operation of city gas networks." Oil and Gas Power Engineering, no. 2(32) (December 27, 2019): 29–34. http://dx.doi.org/10.31471/1993-9868-2019-2(32)-29-34.
Full textAbstract:
The task of choosing the criterion of energy efficiency of operation of city gas networks of high and medium pressure, under the condition of transition to the system of individual energy supply is set and solved. It is shown
 that in conditions of substantial increase of prices for natural gas and deepening of its deficit, the city gas network is often not able to provide consumers with energy in a given volume, so the approach to forecasting its operating modes should fundamentally change. First of all it concerns the field of permissible modes, which in such conditions considerably expands. Given the reloading of the gas distribution network as a result of changing the nature of gas consumption, a large role is given to the criteria for energy efficiency of gas transportation and to ensure maximum operational reliability while being within the scope of optimal maintenance.
 In order to assess the energy efficiency of gas transportation by gas pipelines of a distribution network, it is suggested to use the notion of the net efficiency coefficient, which is determined by the ratio of useful work performed when providing a given volume of gas transportation by pipelines to total energy consumption. It is shown that the efficiency of the distribution network or its individual elements differs fundamentally from the coefficient of its hydraulic efficiency, which is a characteristic of the technical state of the system. On the basis of analytical studies, the correlation between them is established.
 Calculated dependencies are proposed for determining the coefficient of hydraulic efficiency of a branched gas pipeline as an element of an urban gas distribution network. The influence of various factors on the value of the coefficient of hydraulic efficiency of the urban gas distribution network has been analyzed. The examples of calculating the efficiency of the network are given, conclusions on improving the efficiency of operation are made.
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Кapansky, А. А. "Key directions and global practices of efficiency and reliability improvement of water supply." Bulletin Sukhoi State Technical University of Gomel, no. 1 (March 26, 2024): 82–98. http://dx.doi.org/10.62595/1819-5245-2024-1-82-98.
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The article reviews modern research and practical developments in the field of increasing the efficiency and reliability of water supply systems. The analysis covers both the micro level, which includes optimizing the opera-tion of individual components of the system, and the macro level, related to the management and optimization of the water supply system as a whole. Particular attention is paid to improving the efficiency of pumping units, leaks and pressure losses management, as well as water treatment processes optimization. At the macro level, the article presents a review of strategies for the optimal distribution of water between water intakes, a study of the zones of water intakes influence on the hydraulic network, dynamic pressure planning and power consump-tion management of pumping stations. The importance of monitoring and diagnostics systems for increasing the reliability of water supply systems is emphasized. Key areas of research and current problems are identified, and promising approaches to improving the management of urban water supply systems are proposed
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S.G.Mungale. "Critical Review of Fault Tolerance Methods used in Wireless Sensor Networks." Advances in Nonlinear Variational Inequalities 28, no. 5s (2025): 521–56. https://doi.org/10.52783/anvi.v28.3920.
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This paper addresses the critical necessity for developing robust fault-tolerant and resilient systems within the domain of Wireless Sensor Networks (WSNs), a field where the reliability and continuity of data collection and transmission are paramount. Given the inherent challenges of WSNs, including resource constraints, environmental adversities, and operational failures, this work embarks on a comprehensive review of the existing methodologies aimed at identifying and mitigating faults. Notably, techniques such as Distributed Fault Detection, Energy-Efficient Fault Identification, and Machine Learning-based Fault Diagnosis are scrutinized for their efficacy in enhancing network resilience. Central to our investigation is a meticulously designed review process, which employs a multi-faceted evaluation framework to dissect the operational principles, strengths, and limitations of each identified method. By leveraging evaluation metrics such as fault detection accuracy, energy consumption, scalability, and recovery time, this study not only sheds light on the performance of existing solutions but also facilitates a nuanced comparison across different operational scenarios. The implications of this research are manifold. Firstly, it furnishes network designers and operators with a nuanced understanding of the trade-offs associated with each fault-tolerant technique, guiding the selection of optimal methods tailored to specific network requirements and constraints. Secondly, by highlighting the gaps and challenges in current approaches, this work sets the stage for future innovations in the design of more efficient, scalable, and resilient fault-tolerant systems for WSNs. Ultimately, the findings of this review hold the potential to significantly advance the reliability and efficiency of WSNs, thereby bolstering their applicability in critical applications ranging from environmental monitoring to disaster management and urban planning.
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S.G.Mungale. "Critical Review of Fault Tolerance Methods used in Wireless Sensor Networks." Advances in Nonlinear Variational Inequalities 28, no. 6s (2025): 611–50. https://doi.org/10.52783/anvi.v28.4343.
Full textAbstract:
This paper addresses the critical necessity for developing robust fault-tolerant and resilient systems within the domain of Wireless Sensor Networks (WSNs), a field where the reliability and continuity of data collection and transmission are paramount. Given the inherent challenges of WSNs, including resource constraints, environmental adversities, and operational failures, this work embarks on a comprehensive review of the existing methodologies aimed at identifying and mitigating faults. Notably, techniques such as Distributed Fault Detection, Energy-Efficient Fault Identification, and Machine Learning-based Fault Diagnosis are scrutinized for their efficacy in enhancing network resilience. Central to our investigation is a meticulously designed review process, which employs a multi-faceted evaluation framework to dissect the operational principles, strengths, and limitations of each identified method. By leveraging evaluation metrics such as fault detection accuracy, energy consumption, scalability, and recovery time, this study not only sheds light on the performance of existing solutions but also facilitates a nuanced comparison across different operational scenarios. The implications of this research are manifold. Firstly, it furnishes network designers and operators with a nuanced understanding of the trade-offs associated with each fault-tolerant technique, guiding the selection of optimal methods tailored to specific network requirements and constraints. Secondly, by highlighting the gaps and challenges in current approaches, this work sets the stage for future innovations in the design of more efficient, scalable, and resilient fault-tolerant systems for WSNs. Ultimately, the findings of this review hold the potential to significantly advance the reliability and efficiency of WSNs, thereby bolstering their applicability in critical applications ranging from environmental monitoring to disaster management and urban planning.
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Li, Xia, Ying Sun, Xiao Han, and Xin Hua Zhao. "Water Quality Reliability Analysis of Water Distribution Systems Based on Monte-Carlo Simulation." Advanced Materials Research 777 (September 2013): 401–6. http://dx.doi.org/10.4028/www.scientific.net/amr.777.401.
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Water distribution systems (WDS) are important urban infrastructures which are designed for safely conveying potable water from treatment plant to users tap with adequate quantity and desired quality. The water quality reliability evaluation of WDS has positive and critical meanings for ensuring water supply security, reliability and maintaining a high level of service. In this paper, firstly the evaluation index of water quality reliability of municipal water distribution systems has been set up which is characterized by the residual chlorine availability. Then, taking into account the random nature of component failures, the variation of water demand through the 24 hours of a day and the chlorine variation of the treated water in water plant through the 24 hours of a day, the Monte Carlo-based reliability model are established based on the dynamic link library toolkit provided by EPANET 2.0 for the hydraulic and water quality calculation engine. Finally, the water quality reliability of each node and system is evaluated taking water network of some region in Tianjin Binhai High-tech Area (BHA) as example. The research results can be applied to the whole process from planning and design to operation of WDS, and the theoretical basis and decision support for optimal design and operation of WDS are provided for designers and decision-makers.
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Sambito, Mariacrocetta, and Gabriele Freni. "Strategies for Improving Optimal Positioning of Quality Sensors in Urban Drainage Systems for Non-Conservative Contaminants." Water 13, no. 7 (2021): 934. http://dx.doi.org/10.3390/w13070934.
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In the urban drainage sector, the problem of polluting discharges in sewers may act on the proper functioning of the sewer system, on the wastewater treatment plant reliability and on the receiving water body preservation. Therefore, the implementation of a chemical monitoring network is necessary to promptly detect and contain the event of contamination. Sensor location is usually an optimization exercise that is based on probabilistic or black-box methods and their efficiency is usually dependent on the initial assumption made on possible eligibility of nodes to become a monitoring point. It is a common practice to establish an initial non-informative assumption by considering all network nodes to have equal possibilities to allocate a sensor. In the present study, such a common approach is compared with different initial strategies to pre-screen eligible nodes as a function of topological and hydraulic information, and non-formal ‘grey’ information on the most probable locations of the contamination source. Such strategies were previously compared for conservative xenobiotic contaminations and now they are compared for a more difficult identification exercise: the detection of nonconservative immanent contaminants. The strategies are applied to a Bayesian optimization approach that demonstrated to be efficient in contamination source location. The case study is the literature network of the Storm Water Management Model (SWMM) manual, Example 8. The results show that the pre-screening and ‘grey’ information are able to reduce the computational effort needed to obtain the optimal solution or, with equal computational effort, to improve location efficiency. The nature of the contamination is highly relevant, affecting monitoring efficiency, sensor location and computational efforts to reach optimality.
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Ji, Xiang, Huiqun Yu, Guisheng Fan, Huaiying Sun, and Liqiong Chen. "Efficient and Reliable Cluster-Based Data Transmission for Vehicular Ad Hoc Networks." Mobile Information Systems 2018 (July 30, 2018): 1–15. http://dx.doi.org/10.1155/2018/9826782.
Full textAbstract:
Vehicular ad hoc network (VANET) is an emerging technology for the future intelligent transportation systems (ITSs). The current researches are intensely focusing on the problems of routing protocol reliability and scalability across the urban VANETs. Vehicle clustering is testified to be a promising approach to improve routing reliability and scalability by grouping vehicles together to serve as the foundation for ITS applications. However, some prominent characteristics, like high mobility and uneven spatial distribution of vehicles, may affect the clustering performance. Therefore, how to establish and maintain stable clusters has become a challenging problem in VANETs. This paper proposes a link reliability-based clustering algorithm (LRCA) to provide efficient and reliable data transmission in VANETs. Before clustering, a novel link lifetime-based (LLT-based) neighbor sampling strategy is put forward to filter out the redundant unstable neighbors. The proposed clustering scheme mainly composes of three parts: cluster head selection, cluster formation, and cluster maintenance. Furthermore, we propose a routing protocol of LRCA to serve the infotainment applications in VANET. To make routing decisions appropriate, we nominate special nodes at intersections to evaluate the network condition by assigning weights to the road segments. Routes with the lowest weights are then selected as the optimal data forwarding paths. We evaluate clustering stability and routing performance of the proposed approach by comparing with some existing schemes. The extensive simulation results show that our approach outperforms in both cluster stability and data transmission.
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Zhang, Xiao, Chenghao Zheng, and Lingdong Su. "A comprehensive evaluation method for economic collaborative planning evaluation of main distribution network based on rough set and scale extension method." Journal of Physics: Conference Series 2522, no. 1 (2023): 012028. http://dx.doi.org/10.1088/1742-6596/2522/1/012028.
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Abstract The urban 35kV substation is the link between the main network and the distribution network, and the economic power supply and site selection optimization are the keys to the coordinated planning of the main network and the distribution network. A comprehensive evaluation system is established for collaborative economic planning of the main distribution network from three aspects: social benefit, construction economy, and operation economy, and the combination of scale expansion method and rough set method is applied to determine the combined weight of indicators. Based on this index system, a comprehensive evaluation model for economic coordination planning of an intelligent main distribution network is established. It is applied to the economic effect evaluation of the main distribution network planning of a power supply company and the optimal location selection of substations. The results show that the proposed method is a new evaluation method for power grid collaborative planning. Under the premise of ensuring the economy and reliability of power supply, the collaborative planning level of the main distribution network has been significantly improved, and the planning results are better than the traditional site selection results. It not only expands the evaluation system for coordinated planning of the main network and distribution network but also provides guidance for the planning and construction of the main distribution network.
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Ali Rehab, Hashem Khaled Hashem Abdelkader, Eugeniy V. Rogozhnikov, Edgar M. Dmitriyev, and Alexander M. Zabolotsky. "COMPARATIVE ANALYSIS OF CF-MMIMO AND MMIMO SYSTEMS WITH DIVERSE ALGORITHMS IN URBAN AND RURAL ENVIRONMENTS: EVALUATION AND INSIGHTS." T-Comm 17, no. 9 (2023): 67–74. http://dx.doi.org/10.36724/2072-8735-2023-17-9-67-74.
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The rapid advancement of 6G wireless communication systems brings forth unprecedented opportunities for improving coverage, data rates, and quality of service. As the demand for higher capacity and enhanced reliability continues to escalate, it becomes imperative to develop novel techniques that address the challenges of future wireless networks. One such technique is Cell-Free massive multiple-input multiple-output (CF-mMIMO) [1], which holds immense potential for augmenting coverage and reducing bit error rates (BER) across diverse area types, including urban and rural environments. CF-mMIMO represents a state-of-the-art technology that harnesses the synergy between cloud computing and massive MIMO systems. By combining the scalability of cloud resources with the spatial multiplexing capabilities of massive MIMO, CF-mMIMO introduces substantial improvements in coverage and spectral efficiency. Nevertheless, to achieve optimal performance in varying area types, the selection of appropriate precoding techniques assumes paramount importance. This paper conducts a comprehensive investigation into the effects of different precoding schemes, such as channel inversion, block diagonalization, and dirty paper coding, on the performance of CF-mMIMO in urban and rural areas. The outcomes of this research hold significant implications for the design and deployment of 6G networks, providing valuable guidance to network planners and engineers aiming to optimize coverage and minimize bit error rates across diverse area types.
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Arifin, Zainal, Muhammad Zulham, and Eko Prasetyo. "Impact of optical current transformer on protection scheme of hybrid transmission line." Indonesian Journal of Electrical Engineering and Computer Science 24, no. 1 (2021): 1. http://dx.doi.org/10.11591/ijeecs.v24.i1.pp1-11.
Full textAbstract:
Continuity of power transmission is important to ensure the reliability of the electricity supply. As most system faults are temporary, the auto reclose (AR) scheme has been used extensively to minimise the outage duration, prevent widespread outages, thus increase system stability. Meanwhile, the hybrid transmission line (HTL) combining overhead line (OHL) and high voltage cable has been introduced to provide an inexpensive solution for an urban power grid. Protecting HTL with a conventional protection system would forbid the operation of the AR scheme due to difficulty to ensure whether the fault occurred on the OHL or cable section. Therefore, the circulating current protection (CCP) scheme is used in the cable section to ensure the fault location and block the AR scheme. The technology of an optical current transformer (OCT) as one of the non-conventional instrument transformers (NCIT) has emerged to provide a solution to drawbacks on the conventional current transformer (CCT). Consequently, this paper investigated the impact of using OCT over the CCT for CCP of the HTL. The result shows that OCT could be used for CCP on much longer cable sections thus increase its reliability as the AR scheme can be used on longer or multiple cable section.
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Lenatti, Marta, Sara Narteni, Alessia Paglialonga, Vittorio Rampa, and Maurizio Mongelli. "Dual-View Single-Shot Multibox Detector at Urban Intersections: Settings and Performance Evaluation." Sensors 23, no. 6 (2023): 3195. http://dx.doi.org/10.3390/s23063195.
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The explosion of artificial intelligence methods has paved the way for more sophisticated smart mobility solutions. In this work, we present a multi-camera video content analysis (VCA) system that exploits a single-shot multibox detector (SSD) network to detect vehicles, riders, and pedestrians and triggers alerts to drivers of public transportation vehicles approaching the surveilled area. The evaluation of the VCA system will address both detection and alert generation performance by combining visual and quantitative approaches. Starting from a SSD model trained for a single camera, we added a second one, under a different field of view (FOV) to improve the accuracy and reliability of the system. Due to real-time constraints, the complexity of the VCA system must be limited, thus calling for a simple multi-view fusion method. According to the experimental test-bed, the use of two cameras achieves a better balance between precision (68%) and recall (84%) with respect to the use of a single camera (i.e., 62% precision and 86% recall). In addition, a system evaluation in temporal terms is provided, showing that missed alerts (false negatives) and wrong alerts (false positives) are typically transitory events. Therefore, adding spatial and temporal redundancy increases the overall reliability of the VCA system.
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Cwalina, Krzysztof K., Piotr Rajchowski, Alicja Olejniczak, Olga Błaszkiewicz, and Robert Burczyk. "Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning." Sensors 21, no. 22 (2021): 7716. http://dx.doi.org/10.3390/s21227716.
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Following the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides a significant gain (almost 40%) with 10.7% compared to the linear model with the lowest RMSE (Root Mean Squared Error) 17.01%. The solution can be adopted as a part of the data allocation algorithm implemented in the telemetry devices equipped with the 4G radio interface, or, after the adjustment, the NB-IoT (Narrowband Internet of Things), to maximize the reliability of the services in harsh indoor or urban environments. Presented results also prove the existence of the inverse proportional dependence between the number of hidden layers and the number of historical samples in terms of the obtained RMSE. The increase of the historical data memory allows using models with fewer hidden layers while maintaining a comparable RMSE value for each scenario, which reduces the total computational cost.
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Kashtan, V. Yu, and V. V. Hnatushenko. "MACHINE LEARNING FOR AUTOMATIC EXTRACTION OF WATER BODIES USING SENTINEL-2 IMAGERY." Radio Electronics, Computer Science, Control, no. 1 (April 2, 2024): 118. http://dx.doi.org/10.15588/1607-3274-2024-1-11.
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Context. Given the aggravation of environmental and water problems, there is a need to improve automated methods for extracting and monitoring water bodies in urban ecosystems. The problem of efficient and automated extraction of water bodies is becoming relevant given the large amount of data obtained from satellite systems. The object of study is water bodies that are automatically extracted from Sentinel-2 optical satellite images using machine learning methods.
 Objective. The goal of the work is to improve the efficiency of the process of extracting the boundaries of water bodies on digital optical satellite images by using machine learning methods.
 Method. The paper proposes an automated information technology for delineating the boundaries of water bodies on Sentinel-2 digital optical satellite images. The process includes eight stages, starting with data download and using topographic maps to obtain basic information about the study area. Then, the process involved data pre-processing, which included calibrating the images, removing atmospheric noise, and enhancing contrast. Next, the EfficientNet-B0 architecture is applied to identify water features, facilitating optimal network width scaling, depth, and image resolution. ResNet blocks compress and expand channels. It allows for optimal connectivity of large-scale and multi-channel links across layers. After that, the Regional Proposal Network defines regions of interest (ROI), and ROI alignment ensures data homogeneity. The Fully connected layer helps in segmenting the regions, and the Fully connected network creates binary masks for accurate identification of water bodies. The final step of the method is to analyze spatial and temporal changes in the images to identify differences, changes, and trends that may indicate specific phenomena or events. This approach allows automating and accurately identifying water features on satellite images using machine learning.
 Results. The implementation of the proposed technology is development through Python software development. An assessment of the technology’s accuracy, conducted through a comparative analysis with existing methods, such as water indices and K-means, confirms a high level of accuracy in the period from 2017 to 2023 (up to 98%). The Kappa coefficient, which considers the degree of consistency between the actual and predicted classification, confirms the stability and reliability of our approach, reaching a value of 0.96.
 Conclusions. The experiments confirm the effectiveness of the proposed automated information technology and allow us to recommend it for use in studies of changes in coastal areas, decision-making in the field of coastal resource management, and land use. Prospects for further research may include new methods that seasonal changes and provide robustness in the selection and mapping of water surfaces.
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Kuzmina, I. A. "Feasibility Assessment of Urban Electricity Distribution Networks Transition to the Voltage Level of 20 kV." Mechanical Engineering and Computer Science, no. 12 (January 4, 2018): 57–65. http://dx.doi.org/10.24108/1217.0001358.
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The article gives a feasibility assessment for increasing a voltage level of the urban electricity distribution networks from 6 and 10 kV to 20 kV.The emphasis is on the urban electricity distribution network in Moscow. It is noted that by now the reliability, efficiency and automation indicators of Moscow electrical grids are substantially lower than those of Europe, America, etc. The electrical grids in Moscow have a high wear and tear of equipment, a historically developed non-optimal structure, and a high loading level. In recent years, the situation has been significantly improved due to numerous government programs for the development of the electric power industry.It was noted that the high rate of development in Moscow resulted in a significantly increasing density of power loads. So modernisation of grids is a necessary-and-proper step to deliver electric power of good quality and in appropriate volume to all consumers. As the most promising option of such modernisation, the article’s proposal is to increase a voltage level of the electrical grid of medium voltage from 6 and 10 kV to 20 kV.The main advantages of the electrical grid transition to the higher voltage level is an increased power grid capacity and reduced losses of voltage and electric power when transmitting through the electrical grid elements. The article presents some calculations to prove decreasing several times losses in medium voltage cable lines. The shortcoming of the transition to an electrical grid of 20 / 0.4 kV is significant implementation costs, most of which will lead to increasing tariff for consumers.The experience of other countries examined in the article proves that increasing voltage level of the distribution network in Moscow and other megacities is expedient. At the same time, a gradual introduction of 20 / 0.4 kV substations to the electrical grid structure with a gradual unloading and elimination of 10 kV electrical grid elements is expected. The article appeals to successful experience available in the transition of large industrial enterprises to a voltage level of 20 / 0.4 kV.
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Rashvand, Narges, Sanaz Sadat Hosseini, Mona Azarbayjani, and Hamed Tabkhi. "Real-Time Bus Departure Prediction Using Neural Networks for Smart IoT Public Bus Transit." IoT 5, no. 4 (2024): 650–65. http://dx.doi.org/10.3390/iot5040029.
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Bus transit plays a vital role in urban public transportation but often struggles to provide accurate and reliable departure times. This leads to delays, passenger dissatisfaction, and decreased ridership, particularly in transit-dependent areas. A major challenge lies in the discrepancy between actual and scheduled bus departure times, which disrupts timetables and impacts overall operational efficiency. To address these challenges, this paper presents a neural network-based approach for real-time bus departure time prediction tailored for smart IoT public transit applications. We leverage AI-driven models to enhance the accuracy of bus schedules by preprocessing data, engineering relevant features, and implementing a fully connected neural network that utilizes historical departure data to predict departure times at subsequent stops. In our case study analyzing bus data from Boston, we observed an average deviation of nearly 4 minutes from scheduled times. However, our model, evaluated across 151 bus routes, demonstrates a significant improvement, predicting departure time deviations with an accuracy of under 80 s. This advancement not only improves the reliability of bus transit schedules but also plays a crucial role in enabling smart bus systems and IoT applications within public transit networks. By providing more accurate real-time predictions, our approach can facilitate the integration of IoT devices, such as smart bus stops and passenger information systems, that rely on precise data for optimal performance.
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Patil, Ravindra R., Rajnish Kaur Calay, Mohamad Y. Mustafa, and Saniya M. Ansari. "AI-Driven High-Precision Model for Blockage Detection in Urban Wastewater Systems." Electronics 12, no. 17 (2023): 3606. http://dx.doi.org/10.3390/electronics12173606.
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In artificial intelligence (AI), computer vision consists of intelligent models to interpret and recognize the visual world, similar to human vision. This technology relies on a synergy of extensive data and human expertise, meticulously structured to yield accurate results. Tackling the intricate task of locating and resolving blockages within sewer systems is a significant challenge due to their diverse nature and lack of robust technique. This research utilizes the previously introduced “S-BIRD” dataset, a collection of frames depicting sewer blockages, as the foundational training data for a deep neural network model. To enhance the model’s performance and attain optimal results, transfer learning and fine-tuning techniques are strategically implemented on the YOLOv5 architecture, using the corresponding dataset. The outcomes of the trained model exhibit a remarkable accuracy rate in sewer blockage detection, thereby boosting the reliability and efficacy of the associated robotic framework for proficient removal of various blockages. Particularly noteworthy is the achieved mean average precision (mAP) score of 96.30% at a confidence threshold of 0.5, maintaining a consistently high-performance level of 79.20% across Intersection over Union (IoU) thresholds ranging from 0.5 to 0.95. It is expected that this work contributes to advancing the applications of AI-driven solutions for modern urban sanitation systems.