Journal articles on the topic 'Smart city, Energy management, Energy simulation'
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Reis, Fernando B., Reinaldo Tonkoski, and Timothy M. Hansen. "Synthetic residential load models for smart city energy management simulations." IET Smart Grid 3, no. 3 (May 19, 2020): 342–54. http://dx.doi.org/10.1049/iet-stg.2019.0296.
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Gururani, Hemlata, Aman Kumar, Dinesh Waghamode, Ekanki Jain, and Anshika Garg. "Smart City using IOT simulation design in Cisco Packet Tracer." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (May 31, 2022): 2544–51. http://dx.doi.org/10.22214/ijraset.2022.42904.
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Abstract: IoT is a system of interconnected devices which can collect and transfer data without human interference. Now-days IoT is used in various sectors including industries, agriculture, medical, smart city etc. This article review about smart city including – smart home which measures temperature according environment, smart garden which is sprinkling water according to water lever, smart grid which taking energy from solar panel and transfers it to power meter which charge the battery and helps in glowing the bulb. Smart city are the modern urban concepts that are essential for people to have quality of life. In view of the fact that high-tech, reasonable and control obstacle, the smart city opinion is still not extensive through the world. As a consequence, the major purpose of this paper is to carry the personification of smart city. We explain many challenges and opportunities in smart city. The enormity and diversity of devices and their and configuration provide inventive services and frameworks that need a new stimulating sight in integration, reliability and management of data. In this paper the simulation of related work is done by CISCO PACKET TRACER (7.3.1). Keywords: IOT, Smart City, Smart home, Smart grid, Smart garden. RFID, CISCO PACKET TRACER
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Garlík, Bohumír. "Energy Sustainability of a Cluster of Buildings with the Application of Smart Grids and the Decentralization of Renewable Energy Sources." Energies 15, no. 5 (February 23, 2022): 1649. http://dx.doi.org/10.3390/en15051649.
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The optimal design of a building and city, including the balance of their energy performance, must include requirements from a wide range of areas, especially electrical engineering, informatics, technical equipment of buildings, construction and architecture, psychology and many other fields. It is the optimal design, simulation and modelling that are most reflected in the energy requirements of buildings while meeting the requirements of energy sustainability. The impact of buildings and cities on the environment is crucial and unmistakable. It should be emphasized that an inappropriately (architecturally or technologically) designed building with state-of-the-art control technology will still have worse properties than an optimally designed building without a control system. This inspired us to design a building energy model (BEM) with the implementation of a Smart Grid in a decentralized sustainable energy system, which is a microgrid from renewable energy sources (RES). This inspired us to conduct an analysis of simulation models (simultaneous simulations) to show the possibility of their application in the process of fully satisfying energy needs in a given urban region. The main goal is to design an original methodology for the design of smart “Nearly Zero Energy Buildings” (NZEB) and subsequent energy sustainability solutions. This led us to use Hybrid Optimization of Multiple Energy Resources (HOMER), PV*SOL (2D solar software design tool for the photovoltaic system performance), Monte Carlo and DesignBuilder. The EMB was designed based on the Six Sigma design quality management methodology. In the process of integrating Smart Grids with energy efficiency solutions for buildings, an original optimization basis was designed for smart buildings and smart urban areas. The proposed EMB was verified in an experiment.
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Maatoug, Abdelfettah, Ghalem Belalem, and Kadda Mostefaoui. "Modeling and Simulation of Energy Management System for Smart City with the Formalism DEVS: Towards Reducing the Energy Consumption." International Journal of Computer Applications 90, no. 18 (March 26, 2014): 38–43. http://dx.doi.org/10.5120/15824-4710.
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Marques, Daniel, Carlos Senna, and Miguel Luís. "Forwarding in Energy-Constrained Wireless Information Centric Networks." Sensors 22, no. 4 (February 13, 2022): 1438. http://dx.doi.org/10.3390/s22041438.
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Information Centric Networks (ICNs) have been considered one of the most promising candidates to overcome the disadvantages of host-centric architectures when applied to IoT networks, having the potential to address the challenges of a smart city. One of the foundations of a smart city is its sensory capacity, which is obtained through devices associated with the IoT concept. The more sensors spread out, the greater the ability to sense the city. However, such a scale demands high energy requirements and an effective improvement in the energy management is unavoidable. To improve the energy management, we are proposing an efficient forwarding scheme in energy-constrained wireless ICNs. To achieve this goal, we consider the type of devices, their internal energy and the network context, among other parameters. The proposed forwarding strategy extends and adapts concepts of ICNs, by means of packet domain analysis, neighbourhood evaluation and node sleeping and waking strategies. The proposed solution takes advantage of the neighbourhood to be aware of the moments to listen and forward packets in order to consistently address mobility, improving the quality of content delivery. The evaluation is performed by simulation with real datasets of urban mobility, one from the lagoon of “Ria de Aveiro” and the other from a vehicular network in the city of Porto. The results show that the proposed forwarding scheme resulted in significant improvements in network content availability, in the overall energy saving and, consequently, in the network lifetime.
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Loose, Nils, Christian Thommessen, Jan Mehlich, Christian Derksen, and Stefan Eicker. "Unified Energy Agents for Combined District Heating and Electrical Network Simulation." Sustainability 12, no. 21 (November 9, 2020): 9301. http://dx.doi.org/10.3390/su12219301.
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A sustainable and climate-friendly energy supply needs flexible and efficient distribution systems. Key factors to implement this kind of systems are intelligent coordination (smart grid approaches) and the integration of different energy sectors. This article introduces the unified energy agent as an agent-based approach for a comprehensive modelling and control of energy conversion systems. This approach enables both the simulation and optimization of coupled energy networks, and then in a next step, the development of corresponding smart grid solutions to be applied in the field. Its applicability for the simulation of coupled networks is presented by a real-world use-case of an innovative combined heat and electrical network, which was implemented for the city of Lemgo, Germany. Preliminary results from the project are discussed and an outlook on future work is given.
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Wu, Fengzhi, Gaofeng Xu, Ziyi Qi, Zhi Qi, Meng Zhang, and Rong He. "Research on Multi-level Distribution Strategy Based on Energy Internet." E3S Web of Conferences 252 (2021): 03031. http://dx.doi.org/10.1051/e3sconf/202125203031.
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Smart city energy Internet is to comply with the trend of sustainable energy development, urban power energy as the center, comprehensive utilization of all kinds of energy, especially renewable energy, to achieve interconnection and common optimization. Based on the background of distribution network in Disney Park, this paper studies the regulation, operation and management strategy of distribution network of smart city energy Internet. This paper describes the characteristics of the energy Internet, and then analyzes the key technologies that affect power grid regulation, operation and management. The paper investigated the distribution network construction in Shanghai Disney Park under the background of urban energy Internet pilot region to understand the allocation of distributed energy in the park grid. Through simulation calculation and analysis, this paper puts forward a distribution network regulation and management scheme suitable for the characteristics of energy Internet. In this paper, the study found that with the rapid development of power grid, especially all kinds of distributed energy access, the new lines are becoming more. In a wide range of power grid structure is becoming more and more complex, in order to ensure the reliability of power supply and power supply quality, scientific regulation under the background of urban energy Internet development mode, enhancing the management level of power grid is the inevitable developing trend of power grid.
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Mousavi Rad, Eisa, Zahra Mousavi, and Mehro Razmjou. "A review of zero energy residential complex in the smart city environment." Repa Proceeding Series 3, no. 1 (June 30, 2022): 6–11. http://dx.doi.org/10.37357/1068/crgs2022.3.1.02.
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According to the studies conducted by the Energy Consumption Management and Optimization Organization, in the common constructions of the country, energy loss in buildings is often 22% through windows, 22% from floors, and 30% from walls. Applying the principles of energy consumption optimization in coordination with climatic conditions and design uses, as well as the use of active and passive methods, can play an effective role in reducing energy consumption in conventional urban buildings. This research aims to provide solutions that address how to reduce energy consumption while creating quality in the architectural space. These solutions are obtained by recognizing the indicators of sustainable and comparative study with the climate of the desired design context. In the present study, the role of technology and digital tools in the field, which is the first and most important step in locating roles and functions, as well as small-scale designs such as building facades. Then, the architectural recommendations of the climate and international standards were examined, and a total of solutions were presented to reach the zero energy building (ZEB). Finally, the simulation method in Design Builder software analyzed the amount of energy consumption in the residential complex and using the analysis of the researchers' efforts and finding the best answer to the problems of architecture and urban planning; results show a significant reduction in energy consumption to be able to manage available resources in the best way.
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Canizes, Bruno, João Soares, Angelo Costa, Tiago Pinto, Fernando Lezama, Paulo Novais, and Zita Vale. "Electric Vehicles’ User Charging Behaviour Simulator for a Smart City." Energies 12, no. 8 (April 18, 2019): 1470. http://dx.doi.org/10.3390/en12081470.
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The increase of variable renewable energy generation has brought several new challenges to power and energy systems. Solutions based on storage systems and consumption flexibility are being proposed to balance the variability from generation sources that depend directly on environmental conditions. The widespread use of electric vehicles is seen as a resource that includes both distributed storage capabilities and the potential for consumption (charging) flexibility. However, to take advantage of the full potential of electric vehicles’ flexibility, it is essential that proper incentives are provided and that the management is performed with the variation of generation. This paper presents a research study on the impact of the variation of the electricity prices on the behavior of electric vehicle’s users. This study compared the benefits when using the variable and fixed charging prices. The variable prices are determined based on the calculation of distribution locational marginal pricing, which are recalculated and adapted continuously accordingly to the users’ trips and behavior. A travel simulation tool was developed for simulating real environments taking into account the behavior of real users. Results show that variable-rate of electricity prices demonstrate to be more advantageous to the users, enabling them to reduce charging costs while contributing to the required flexibility for the system.
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Singh, Parminder, Anand Nayyar, Avinash Kaur, and Uttam Ghosh. "Blockchain and Fog Based Architecture for Internet of Everything in Smart Cities." Future Internet 12, no. 4 (March 26, 2020): 61. http://dx.doi.org/10.3390/fi12040061.
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Fog computing (FC) is used to reduce the energy consumption and latency for the heterogeneous communication approaches in the smart cities’ applications of the Internet of Everything (IoE). Fog computing nodes are connected through wired or wireless medium. The goal of smart city applications is to develop the transaction relationship of real-time response applications. There are various frameworks in real-world to support the IoE in smart-cities but they face the issues like security, platform Independence, multi-application assistance, and resource management. This article is motivated from the Blockchain and Fog computing technologies and presents a secured architecture Blockchain and Fog-based Architecture Network (BFAN) for IoE applications in the smart cities. The proposed architecture secures sensitive data with encryption, authentication, and Blockchain. It assists the System-developers and Architects to deploy the applications in smart city paradigm. The goal of the proposed architecture is to reduce the latency and energy, and ensure improved security features through Blockchain technology. The simulation results demonstrate that the proposed architecture performs better than the existing frameworks for smart-cities.
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Yamagata, Yoshiki, and Hajime Seya. "Simulating a future smart city: An integrated land use-energy model." Applied Energy 112 (December 2013): 1466–74. http://dx.doi.org/10.1016/j.apenergy.2013.01.061.
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Doshi, Aayush. "BINTERNET: Smart Waste Management System." International Journal for Research in Applied Science and Engineering Technology 9, no. 11 (November 30, 2021): 703–7. http://dx.doi.org/10.22214/ijraset.2021.38882.
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Abstract: To make the cities greener, safer, and more efficient, Internet of Things (IoT) can play an important role. Improvement in safety and quality of life can be achieved by connecting devices, vehicles and infrastructure all around in a city. We present a waste collection management solution based on providing intelligence to waste bins, using an IOT prototype with sensors. It can read, collect, and transmit huge volume of data over the Internet. Such data, when put into a spatial-temporal context and processed by intelligent and optimized algorithms, can be used to dynamically manage waste collection mechanism. Simulations for several cases are carried out to investigate the benefits of such system over a traditional system
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Azri, S., U. Ujang, and A. Abdul Rahman. "3D GEO-CLUSTERING FOR WIRELESS SENSOR NETWORK IN SMART CITY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W12 (February 21, 2019): 11–16. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w12-11-2019.
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<p><strong>Abstract.</strong> Smart city is a connection of physical and social infrastructure together with the information technology to leverage the collective intelligence of the city. Smart cities depend on a great extent on wireless sensor network to manage and maintain their services. Advanced sensor technologies are used to acquire information and help dealing with issues like air pollution, waste management, traffic optimization, and energy efficiency. However, no matter how much smart city may focus on sensor technology, data that are produced from sensors do not organize themselves in a database. Such tasks require a sophisticated database structure to produce informative data output. Besides that, wireless sensor network requires a proper design to improve the energy efficiency. The design will aid to prolong the lifespan of wireless network efficiently. In this study, we proposed a new technique that will be used to organize the information of wireless sensor network in the spatial database. Specific algorithm which is 3D geo-clustering algorithm is used to tackle several issues of location of the sensor in three-dimensional urban area in smart city. The algorithm is designed to minimizing the overlap among group clusters. Overlap plays an important role for energy efficiency. Thus, detection of sensors in two or more group clusters will avoid it from transmitting the same signal to cluster head node. It is prove that this algorithm would only create 5% to 10% overlap among group clusters. Several experiments are performed in this study to evaluate the algorithm. Based on the simulation results indicate that this algorithm can balance nodes energy consumption and prolong the network’s life span. It also has good stability and extensibility. Several tests are performed to validate the efficiency of the technique to measure the database performance.</p>
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Perko, Jurica, Danijel Topić, and Damir Šljivac. "Providing Power Supply to Other Use Cases Integrated in the System of Public Lighting." International journal of electrical and computer engineering systems 8, no. 1 (2017): 33–40. http://dx.doi.org/10.32985/ijeces.8.1.5.
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Smart city is an attractive way of making the city more livable through intelligent solutions that are enabled by information and communication technology. Regarding the lighting system, it achieves the perfect balance between beautiful city ambience and preserving the darkness that makes cities more livable. As a smart city component, a public lighting system offers much more than light itself. Integration of other use cases has given a new dimension to the public lighting system in visual and functional terms. All those features that could be integrated into the public lighting infrastructure require additional power supply. This paper deals with possibilities of providing electricity to other power use cases integrated into the system of public lighting. Simulation results in DIALux showed that it is possible to save energy by a transition to LED lighting technology and establishment of a smart lighting management system using a dynamic operational profile proposed in the paper. By means of that, it is possible to reduce energy consumption in the public lighting system by at least 50 % up to 80 %, which could be enough for power use cases integrated into the public lighting infrastructure
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Rahman, Md Samin, and Md Humayun Kabir. "Social Internet of Things (SIoT) Enabled System Model for Smart Integration of Building‟s Energy, Water and Safety Management: Dhaka City, Bangladesh Perspective." AIUB Journal of Science and Engineering (AJSE) 18, no. 1 (May 31, 2019): 19–26. http://dx.doi.org/10.53799/ajse.v18i1.18.
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Dhaka, being the largest township of Bangladesh City Buildings is excreted by in-migration, a rapid growth of population, withering of living and infrastructure standard, which eventually is threatening overall sustainability and well beings. Modernization and digitalization of building infrastructure is not only an important step towards resolving the problems but also it will be a facilitator for smart, efficient and optimized urbanization. On May 2018, the authors conducted a survey among 51 Residential Building’s owner/building managers, 25 Non-residential Building’s owner/building managers and 25 corporate building’s owner/building managers to find market adoptable IoT solutions for building’s smart efficient energy, water and safety managements. The features requested in this survey are optimized and implemented by the authors and finally, here the system model with simulation results is presented. This system shows promising energy, water resource management optimization and some intriguing factors that validate its objectives, social characteristics, market usability.
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Masompe, K. B., T. Madiba, T. S. Bungu, and F. T. Kadinda. "Smart Grid Method for the Lubumbashi Distribution Network Based on Provision of Renewable Energy Resources." Journal of Solar Energy Research Updates 9 (August 13, 2022): 16–26. http://dx.doi.org/10.31875/2410-2199.2022.09.03.
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Abstract: The development of smart grids (SG) in the electrical network is the subject of many studies nowadays. This new technology seems to be as an additional tool and the perfect solution which the D.R. Congo could use to achieve the objectives of the efficient management of electrical energy, electrical network security, and the inclusion of renewable energy sources. The rise of these new networks brings together many economic issues.
This study is essentially focused on the incapability of the National Electricity Company (SNEL) which still retains the monopoly of production and distribution of energy to individuals, industries and mining companies. The incorporation of a system of control and management of the two-ways energy flow between the sources of electricity production and users via an intelligent distribution network, considering several specific constraints and performance required, will allow us to highlight the influence of intelligence in a distribution network as complex as that of the city of Lubumbashi. This study reviews the challenges of renewable energies in the environment of the city of Lubumbashi, the modeling of the distribution network, the introduction of intelligence control in the network and simulation using computer tools to see the contribution of these results to the entire electrical system. Finally, the integration of new renewable energy sources associated with its monitoring system is planned to stabilize this network by increasing the efficiency of the system with 25 percent in power quality.
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Alagbu, Ekene. "Hierarchical Power Scheduling Algorithm and Energy Management System in a Smart Solar Micro Grid." International Journal for Research in Applied Science and Engineering Technology 9, no. 10 (October 31, 2021): 251–66. http://dx.doi.org/10.22214/ijraset.2021.38347.
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Abstract: In recent years, as the development of the modern technologies in information, communication, control and computing, our living environment is becoming ”smart.” Smart Home and Smart City have gradually become part of our lives, and are no longer merely future concepts for the public. Microgrids have been set up to try and bring electricity to people even living in remote and rural areas. Even though different techniques have been applied to solve this problem, nevertheless there seems to be scarcity in deep exploration of local and indigenous solar power generation and weather data unique to the African context while dealing with this issue. In this dissertation, an optimal configuration algorithm for sharing energy resources in a microgrid using data collected from a microgrid located in Nigeria has been developed. The microgrid was divided into three (3) blocks (containing different offices) with different load distribution. The system was analyzed to determine the degree of deviation of the supplied power from the load demand. Results showed that in one of the blocks, the developed system showed a 89.2% improvement in the amount of surplus energy generated by the system. Simulation results also showed that the conventional system suffered the worst draw down during peak load demands. The battery SoC in block A went below the acceptable 30% threshold, while at that instance the SoC for the developed system in this work was about 57%. The developed worked showed about 27% improvement on the existing system even at peak load periods. Simulation results showed that as at 100 seconds, the error percentage of the existing design spiked to 7% while that of the developed algorithm was tending to zero. The system response when switching between different scenarios was also examined, and it was discovered that the developed algorithm responded to the switch in just 80mS. Keywords: Microgrid, Solar PV, ELDI, Scheduling algorithm, Energy Management
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Ogbodo, Emmanuel Utochukwu, Adnan M. Abu-Mahfouz, and Anish M. Kurien. "Enabling LPWANs for Coexistence and Diverse IoT Applications in Smart Cities Using Lightweight Heterogenous Multihomed Network Model." Journal of Sensor and Actuator Networks 11, no. 4 (December 19, 2022): 87. http://dx.doi.org/10.3390/jsan11040087.
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Smart cities have been envisioned to provide smartness in managing internet of things (IoT) application domains, such as transport and mobility, health care, natural resources, electricity and energy, homes and buildings, commerce and retail, society and workplace, industry, agriculture, and the environment. The growth trajectory in usage of these IoT domains has led to a heterogeneous dense network in a smart city environment. The heterogeneous dense network in smart cities has led to challenges, such as difficulties in the management of LPWAN coexistence, interference, spectrum insufficiency, QoS, and scalability issues. The existing LPWAN technologies cannot support the heterogeneous dense network challenges in smart cities. Further, it cannot support diverse IoT, including medium- to high-bandwidth applications, due to the power, complexity, and resource constraints of the LPWAN devices. Hence, this paper addresses high data rate IoT applications and heterogeneous dense networks. This paper proposes a lightweight heterogenous multihomed network (LHM-N) model for diverse smart city applications that will address dense heterogeneity network challenges in a smart city. The work aims to advocate and integrate a manageable license-free LPWAN that will coexist with 5G private and public cellular networks in the LHM-N model. This will help to provide a cost-effective solution model in a heterogeneous dense smart city environment. Further, a secured lightweight energy-efficient packet-size forwarding engine (PSFE) algorithm is presented using the discrete event simulation (DES) methodological approach in MATLAB for complexity evaluation. In addition, a 5G reduced capability (RedCap) IoT device is integrated into the (LHM-N) model to support smart city. Finally, the results show that the LHM-N model outperforms the conventional quadrature amplitude modulation (QAM) protocol scheme in terms of error rate, latency, and data throughput with reduced energy costs for medium- to high-bandwidth industrial IoT applications. This validates the suitability of the LHM-N model for high data rate IoT applications.
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Mao, Bo, Yifang Ban, and Björn Laumert. "Dynamic Online 3D Visualization Framework for Real-Time Energy Simulation Based on 3D Tiles." ISPRS International Journal of Geo-Information 9, no. 3 (March 11, 2020): 166. http://dx.doi.org/10.3390/ijgi9030166.
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Energy co-simulation can be used to analyze the dynamic energy consumption of a building or a region, which is essential for decision making in the planning and management of smart cities. To increase the accessibility of energy simulation results, a dynamic online 3D city model visualization framework based on 3D Tiles is proposed in this paper. Two types of styling methods are studied, attribute-based and ID map-based. We first perform the energy co-simulation and save the results in CityGML format with EnergyADE. Then the 3D geometry data of these city objects are combined with its simulation results as attributes or just with object ID information to generate Batched 3D Models (B3DM) in 3D Tiles. Next, styling strategies are pre-defined and can be selected by end-users to show different scenarios. Finally, during the visualization process, dynamic interactions and data sources are integrated into the styling generation to support real-time visualization. This framework is implemented with Cesium. Compared with existing dynamic online 3D visualization framework such as directly styling or Cesium Language (CZML), a JSON format for describing a time-dynamic graphical scene, primarily for display in a web browser running Cesium, the proposed framework is more flexible and has higher performance in both data transmission and rendering which is essential for real-time GIS applications.
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Ijemaru, Gerald K., Li-Minn Ang, and Kah Phooi Seng. "Swarm Intelligence Internet of Vehicles Approaches for Opportunistic Data Collection and Traffic Engineering in Smart City Waste Management." Sensors 23, no. 5 (March 6, 2023): 2860. http://dx.doi.org/10.3390/s23052860.
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Recent studies have shown the efficacy of mobile elements in optimizing the energy consumption of sensor nodes. Current data collection approaches for waste management applications focus on exploiting IoT-enabled technologies. However, these techniques are no longer sustainable in the context of smart city (SC) waste management applications due to the emergence of large-scale wireless sensor networks (LS-WSNs) in smart cities with sensor-based big data architectures. This paper proposes an energy-efficient swarm intelligence (SI) Internet of Vehicles (IoV)-based technique for opportunistic data collection and traffic engineering for SC waste management strategies. This is a novel IoV-based architecture exploiting the potential of vehicular networks for SC waste management strategies. The proposed technique involves deploying multiple data collector vehicles (DCVs) traversing the entire network for data gathering via a single-hop transmission. However, employing multiple DCVs comes with additional challenges including costs and network complexity. Thus, this paper proposes analytical-based methods to investigate critical tradeoffs in optimizing energy consumption for big data collection and transmission in an LS-WSN such as (1) finding the optimal number of data collector vehicles (DCVs) required in the network and (2) determining the optimal number of data collection points (DCPs) for the DCVs. These critical issues affect efficient SC waste management and have been overlooked by previous studies exploring waste management strategies. Simulation-based experiments using SI-based routing protocols validate the efficacy of the proposed method in terms of the evaluation metrics.
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Causone, Francesco, and Martina Pelle. "Building stock simulation to support the development of a district multi-energy grid." E3S Web of Conferences 111 (2019): 06027. http://dx.doi.org/10.1051/e3sconf/201911106027.
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The urbanization process is constantly increasing worldwide. Today over 50 % of the population resides in urban areas and this value is expected to grow up to 68 % by 2050. In this scenario, the development of district scale energy grids and management systems has become crucial to optimize energy use and to balance energy flows within the cities, encouraging the use of renewable sources and self-consumption. This study focusses on a district under development in the city of Milan, involving an urban area of about 920 000 m2, which, once completed, will count for about 4 500 apartments, a school and a few other commercial uses. The existing energy systems consist of an electric grid, including a small photovoltaic field, a district heating system and a local district cooling system exploiting groundwater via heat pumps. They serve, at present, seven residential tower buildings (400 apartments). The overarching aim of the research is to evolve the existing grid into a smart energy grid able to guarantee an intelligent management of the district, empowering eventually people to apply for demand-response schemes, electric mobility and other innovative services. In order to perform such an improvement and extension of the exiting grid, it is necessary to evaluate and simulate the profiles and dynamics of the final energy uses for the residential buildings, that will represent the major load on site. Since monitoring data are not yet available for the district, the evaluation of the energy performance of the existing buildings has been developed through dynamic energy simulations via the definition of profile loads of the most frequent apartment typologies, that allow, moreover, to simulate further developments in the districts. Besides, a monitoring plan for the existing systems has been developed and implemented. Monitoring data will be used at first for validating the developed load profiles; then, they will be analysed to develop optimisation algorithms for the management of the upgraded energy grid. In this paper, the case study is presented and the results of the analysis, via energy simulation, on the existing building stock are reported.
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Tian, Kang, Haojun Chai, Yameng Liu, and Boyang Liu. "Edge Intelligence Empowered Dynamic Offloading and Resource Management of MEC for Smart City Internet of Things." Electronics 11, no. 6 (March 10, 2022): 879. http://dx.doi.org/10.3390/electronics11060879.
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Internet of Things (IoT) has emerged as an enabling platform for smart cities. In this paper, the IoT devices’ offloading decisions, CPU frequencies and transmit powers joint optimization problem is investigated for a multi-mobile edge computing (MEC) server and multi-IoT device cellular network. An optimization problem is formulated to minimize the weighted sum of the computing pressure on the primary MEC server (PMS), the sum of energy consumption of the network, and the task dropping cost. The formulated problem is a mixed integer nonlinear program (MINLP) problem, which is difficult to solve since it contains strongly coupled constraints and discrete integer variables. Taking the dynamic of the environment into account, a deep reinforcement learning (DRL)-based optimization algorithm is developed to solve the nonconvex problem. The simulation results demonstrate the correctness and the effectiveness of the proposed algorithm.
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Galvão, João Rafael, Licinio Moreira, Gonçalo Gaspar, Samuel Vindeirinho, and Sérgio Leitão. "Energy system retrofit in a public services building." Management of Environmental Quality: An International Journal 28, no. 3 (April 10, 2017): 302–14. http://dx.doi.org/10.1108/meq-02-2014-0028.
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Purpose Taking into account the current relevance of the concept of smart city connected with the Internet of Things, this work aims to study the implementation of this concept by applying a new energy model in an existing public building. The purpose of this paper is to enhance the sustainability and energy autonomy of the building. Design/methodology/approach The building referred to in the case study is a library, and simulations related to the ongoing study are based on an energy audit, comprising a survey on electrical and thermal energy consumption. The innovative proposed model consists of a mix of energy production processes based on photovoltaic panels and biomass boilers. Economic analysis of the energy model has already yielded some results regarding the payback on investment, as well as avoided emissions in the context of development of a low-carbon economy with avoided emissions and socioeconomic advantages. Findings It is possible to enhance the sustainability of the library studied by the retrofit of the current energy system. With the integration of photovoltaic panels and the conversion or replacement of boilers from natural gas to biomass, the GHG emissions could drop around 121 t CO2 per year. Another benefit would be the inclusion of endogenous resources over imported energy resources. The payback period for the measures proposed ranges from 2.5 to 8 years, proving that the increase in environmental sustainability is viable. Originality/value The intention here is to implement the concept of smart city, in more sustainable buildings, bringing them to the lowest possible energy consumption levels, hence increasing performance and comfort. Also, taking into account that the energy-consuming buildings are already constructed, it is urgent to reconvert them to lower the use of energy and emissions using technologies based on renewable energy, boosting the use of local resources.
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Gorbunova, Anastasia, Ilya Anisimov, and Elena Magaril. "Studying the Formation of the Charging Session Number at Public Charging Stations for Electric Vehicles." Sustainability 12, no. 14 (July 10, 2020): 5571. http://dx.doi.org/10.3390/su12145571.
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The energy industry is a leader of introduction and development of energy supply technologies from renewable energy sources. However, there are some disadvantages of these energy systems, namely, the low density and inconsistent nature of the energy input, which leads to an increase in the cost of the produced electric energy in comparison to the traditional energy complexes using hydrocarbon fuel resources. Therefore, the smart grid technology based on preliminary calculation parameters of the energy system develops in cities. This area should also be used to organize the charging infrastructure of electric vehicles, as the electrification of road transport is one of the global trends. As a result, a current task of the transport and energy field is the development of scientifically based approaches to the formation of the urban charging infrastructure for electric vehicles. The purpose of the article is to identify the features of the application flow formation for the charge of the electric vehicle battery. The results obtained provide a basis for building a simulation model for determining the required number of charging stations in the city, taking into account the criteria of minimizing operating costs for electric vehicle owners and energy companies.
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Feng, Huibin, Zhaocai Yu, Jian Guan, and Geng Lin. "A Hybrid Spectrum Combinational Auction Mechanism Based on a Weighted Bipartite Graph for Energy Internet in Smart Cities." Wireless Communications and Mobile Computing 2020 (November 5, 2020): 1–13. http://dx.doi.org/10.1155/2020/8829602.
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Energy Internet (EI) is aimed at sustainable computing by integrating various energy forms into a highly flexible grid similar to the Internet. The network subsystems of EI connect different components to enable real-time monitoring, controlling, and management. In this paper, the spectrum allocation problem of the cognitive radio network for EI in a smart city is investigated. The network spectrum allocation with both heterogeneous primary operators and secondary users is formulated as the combinatorial auction problem and then is converted to a subset selection problem on a weighted bipartite graph. We propose a hybrid algorithm to solve the problem. Firstly, the proposed algorithm uses a constructive procedure based on the Kuhn-Munkres algorithm to obtain an initial solution. Then, a local search is used to improve the solution quality. In addition, the truthfulness of the auction is guaranteed by adopting a “Vickrey-like” mechanism. Simulation results show that the performance of the proposed algorithm is better than existing greedy algorithms in terms of the social welfare, seller revenue, buyer satisfaction ratio, and winning buyer ratio.
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Makieła, Zbigniew J., Grzegorz Kinelski, Jakub Stęchły, Mariusz Raczek, Krzysztof Wrana, and Janusz Michałek. "Tools for Network Smart City Management—The Case Study of Potential Possibility of Managing Energy and Associated Emissions in Metropolitan Areas." Energies 15, no. 7 (March 22, 2022): 2316. http://dx.doi.org/10.3390/en15072316.
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The article uses the case study of a polycentric metropolitan area as a starting point for a debate about the available tools for managing the network aspects of intelligent cities. We show that the construction of talents, the development of knowledge among officials and inhabitants, and technological tools such as Hubgrade (which allows for heat delivery process control, supervision, inspection, and results in emission reduction) are prerequisites for the sustainable development of cities. It is critical to understand that technological solutions are insufficient to accomplish such a task. Relevant stakeholders need to consciously take advantage of technological tools and build and utilise 4T potential and the self-learning capabilities of the organisations. An inherent feature of an organisation, such as a city, is cooperation between the people who build it. The main challenges of cities includes the reduction of pollutants resulting from the use of transport, heat sources, or energy production. In many cities, an efficient manner of reducing carbon dioxide emissions is to limit the consumption of thermal energy. In order to simultaneously maintain thermal comfort, in this situation, it is necessary to use intelligent technologies. The paper includes research related to the knowledge and development of 4T potentials (technology, trust, talent, tolerance) and to networking expansion by introducing the automated Hubgrade system, used in Warsaw district heating, into a similar metropolitan area. Along with an increase in the significance of relations, information, and knowledge as a key organisational resource, cities, as organisations, have become an important element of contemporary communities and organisations. They have the possibility of a positive climate change. The possibility of cooperation and networking between people forming an organisation is its inherent feature, such as in the Hubgrade project. Conclusions and recommendations are drawn for the analysed case—linking 4T potentials and the Hubgrade system—with the potential for future generalisations and extrapolations. The authors performed a simulation of possible energy savings and the reduction of harmful emissions in Metropolis GZM.
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Lenfers, Ulfia A., Nima Ahmady-Moghaddam, Daniel Glake, Florian Ocker, Daniel Osterholz, Jonathan Ströbele, and Thomas Clemen. "Improving Model Predictions—Integration of Real-Time Sensor Data into a Running Simulation of an Agent-Based Model." Sustainability 13, no. 13 (June 22, 2021): 7000. http://dx.doi.org/10.3390/su13137000.
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The current trend towards living in big cities contributes to an increased demand for efficient and sustainable space and resource allocation in urban environments. This leads to enormous pressure for resource minimization in city planning. One pillar of efficient city management is a smart intermodal traffic system. Planning and organizing the various kinds of modes of transport in a complex and dynamically adaptive system such as a city is inherently challenging. By deliberately simplifying reality, models can help decision-makers shape the traffic systems of tomorrow. Meanwhile, Smart City initiatives are investing in sensors to observe and manage many kinds of urban resources, making up a part of the Internet of Things (IoT) that produces massive amounts of data relevant for urban planning and monitoring. We use these new data sources of smart cities by integrating real-time data of IoT sensors in an ongoing simulation. In this sense, the model is a digital twin of its real-world counterpart, being augmented with real-world data. To our knowledge, this is a novel instance of real-time correction during simulation of an agent-based model. The process of creating a valid mapping between model components and real-world objects posed several challenges and offered valuable insights, particularly when studying the interaction between humans and their environment. As a proof-of-concept for our implementation, we designed a showcase with bike rental stations in Hamburg-Harburg, a southern district of Hamburg, Germany. Our objective was to investigate the concept of real-time data correction in agent-based modeling, which we consider to hold great potential for improving the predictive capabilities of models. In particular, we hope that the chosen proof-of-concept informs the ongoing politically supported trends in mobility—away from individual and private transport and towards—in Hamburg.
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Islam, Shayla, Anil Kumar Budati, Mohammad Kamrul Hasan, Hima Bindu Valiveti, and Sridhar Reddy Vulupala. "Sustainable Non-Cooperative User Detection Techniques in 5G Communications for Smart City Users." Sustainability 15, no. 1 (December 21, 2022): 118. http://dx.doi.org/10.3390/su15010118.
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The 4G network is not sufficient for achieving the high data requirements of smart city users. The 5G network intends to meet these requirements and overcome other application issues, such as fast data transmission, video buffering, and coverage issues, providing excellent mobile data services to smart city users. To allocate a channel or spectrum to a smart city user for error-free transmission with low latency, the accurate information of the spectrum should be detected. In this study, we determined the range of non-cooperative detection techniques, such as matched filter detection with inverse covariance approach (MFDI), cyclostationary feature detection with inverse covariance approach (CFDI), and hybrid filter detection with inverse covariance approach (HFDI); based on the results of these methods, we provided highly accurate spectrum information for smart city users, enabling sustainable development. To evaluate the performance of the proposed detection techniques, the following parameters are used: probability of detection (PD), probability of false alarms (Pfa), probability of miss detection (Pmd), sensing time, and throughput. The simulation results revealed that the HFDI detection method provided sustainable results at low signal-to-noise ratio ranges and improved channel detection and throughput of approximately 17% and 10%, respectively.
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Liu, Zheng, Bin Hu, Bangtong Huang, Lingling Lang, Hangxin Guo, and Yuanjun Zhao. "Decision Optimization of Low-Carbon Dual-Channel Supply Chain of Auto Parts Based on Smart City Architecture." Complexity 2020 (May 21, 2020): 1–14. http://dx.doi.org/10.1155/2020/2145951.
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Affected by the Internet, computer, information technology, etc., building a smart city has become a key task of socialist construction work. The smart city has always regarded green and low-carbon development as one of the goals, and the carbon emissions of the auto parts industry cannot be ignored, so we should carry out energy conservation and emission reduction. With the rapid development of the domestic auto parts industry, the number of car ownership has increased dramatically, producing more and more CO2 and waste. Facing the pressure of resources, energy, and environment, the effective and circular operation of the auto parts supply chain under the low-carbon transformation is not only a great challenge, but also a development opportunity. Under the background of carbon emission, this paper establishes a decision-making optimization model of the low-carbon supply chain of auto parts based on carbon emission responsibility sharing and resource sharing. This paper analyzes the optimal decision-making behavior and interaction of suppliers, producers, physical retailers, online retailers, demand markets, and recyclers in the auto parts industry, constructs the economic and environmental objective functions of low-carbon supply chain management, applies variational inequality to analyze the optimal conditions of the whole low-carbon supply chain system, and finally carries out simulation calculation. The research shows that the upstream and downstream auto parts enterprises based on low-carbon competition and cooperation can effectively manage the carbon footprint of the whole supply chain through the sharing of responsibilities and resources among enterprises, so as to reduce the overall carbon emissions of the supply chain system.
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Li, Lianyan, and Xiaobin Ren. "A Novel Evaluation Model for Urban Smart Growth Based on Principal Component Regression and Radial Basis Function Neural Network." Sustainability 11, no. 21 (November 3, 2019): 6125. http://dx.doi.org/10.3390/su11216125.
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Smart growth is widely adopted by urban planners as an innovative approach, which can guide a city to develop into an environmentally friendly modern city. Therefore, determining the degree of smart growth is quite significant. In this paper, sustainable degree (SD) is proposed to evaluate the level of urban smart growth, which is established by principal component regression (PCR) and the radial basis function (RBF) neural network. In the case study of Yumen and Otago, the SD values of Yumen and Otago are 0.04482 and 0.04591, respectively, and both plans are moderately successful. Yumen should give more attention to environmental development while Otago should concentrate on economic development. In order to make a reliable future plan, a self-organizing map (SOM) is conducted to classify all indicators and the RBF neural network-trained indicators are separate under different classifications to output new plans. Finally, the reliability of the plan is confirmed by cellular automata (CA). Through simulation of the trend of urban development, it is found that the development speed of Yumen and Otago would increase slowly in the long term. This paper provides a powerful reference for cities pursuing smart growth.
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Manogaran, Gunasekaran, Bharat S. Rawal, Houbing Song, Huihui Wang, Chinghsien Hsu, Vijayalakshmi Saravanan, Seifedine Nimer Kadry, and P. Mohamed Shakeel. "Optimal Energy-Centric Resource Allocation and Offloading Scheme for Green Internet of Things Using Machine Learning." ACM Transactions on Internet Technology 22, no. 2 (May 31, 2022): 1–19. http://dx.doi.org/10.1145/3431500.
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Resource allocation and offloading in green Internet of Things (IoT) relies on the multi-level heterogeneous platforms. The energy expenses of the platform determine the reliability of green IoT based services and applications. This manuscript introduces a decisive energy management scheme for optimal resource allocation and offloading along with energy constraints. This scheme handles both the allocation and energy-cost in a balanced manner through deterministic task offloading. In particular, resource allocation solution for non-delay tolerant green IoT applications is focused by confining the failures of discrete tasks through neural learning. The dropout process augmented with the learning process improves the feasible conditions for resource handling and task offloading among the active IoT service providers. Through extensive simulations the performance of the proposed scheme is analyzed and energy consumption, failure rate, processing, and completion time metrics are used for a comparative study. Further, the optimal utilization and on-demand dissipation of such stored resources help to improve the sustainability of green power and communication technologies in the smart city environment.
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Ren, Jun, Wei Zhou, Xuelu Liu, Liang Zhou, Jing Guo, Yonghao Wang, Yanjun Guan, Jingtian Mao, Yuhan Huang, and Rongrong Ma. "Urban Expansion and Growth Boundaries in an Oasis City in an Arid Region: A Case Study of Jiayuguan City, China." Sustainability 12, no. 1 (December 25, 2019): 210. http://dx.doi.org/10.3390/su12010210.
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China is undergoing rapid urbanization, which has caused undesirable urban sprawl and ecological deterioration. Urban growth boundaries (UGBs) are an effective measure to restrict the irrational urban sprawl and protect the green space. However, the delimiting method and control measures of the UGBs is at the exploratory stage in China. In this paper, a cellular automata model based on multi-criteria evaluation (MCE-CA) was proposed to delimit the UGBs. The MCE-CA model considers influencing factors related to urban growth and generates UGBs based on spatiotemporally dynamic simulations. The MCE-CA model was applied to generate the UGBs of Jiayuguan City in 2020 and 2030, the results show that the simulation accuracy is higher than 0.8 and the compactness increases to 0.23, which demonstrates that the MCE-CA model is an effective model for delimiting UGBs. Moreover, the MCE-CA model can corporate the contradiction between environmental protection and urban development, promoting urban smart growth and sustainable development. UGBs is an effective tool for China to realize ecological civilization construction and improve the spatial governance ability, and the MCE-CA model can be used to assist planners in delimiting future UGBs, this study provides a methodological reference for future research of UGBs in Chinese cities.
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Davydenko, Liudmyla, Nina Davydenko, Andrii Bosak, Alla Bosak, Agnieszka Deja, and Tygran Dzhuguryan. "Smart Sustainable Freight Transport for a City Multi-Floor Manufacturing Cluster: A Framework of the Energy Efficiency Monitoring of Electric Vehicle Fleet Charging." Energies 15, no. 10 (May 20, 2022): 3780. http://dx.doi.org/10.3390/en15103780.
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This study focuses on the problem of the efficient energy management of an independent fleet of freight electric vehicles (EVs) providing service to a city multi-floor manufacturing cluster (CMFMC) within a metropolis while considering the requirements of smart sustainable electromobility and the limitations of the power system. The energy efficiency monitoring system is considered an information support tool for the management process. An object-oriented formalization of monitoring information technology is proposed which has a block structure and contains three categories of classes (information acquisition, calculation algorithms, and control procedures). An example of the implementation of the class “Operation with the electrical grid” of information technology is presented. The planning of the freight EVs charging under power limits of the charging station (CS) was carried out using a situational algorithm based on a Fuzzy expert system. The situational algorithm provides for monitoring the charging of a freight EV at a charging station, taking into account the charge weight index (CWI) assigned to it. The optimization of the CS electrical load is carried out from the standpoint of minimizing electricity costs and ensuring the demand for EV charging without going beyond its limits. A computer simulation of the EV charging mode and the CS load was performed. The results of modeling the electrical grid and CS load using the proposed algorithm were compared with the results of modeling using a controlled charging algorithm with electrical grid limitations and an uncontrolled charging algorithm. The proposed approach provides a reduction in power consumption during peak hours of the electrical grid and charging of connected EVs for an on-demand state of charge (SOC).
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García-Suárez, Amaro, José-Luis Guisado-Lizar, Fernando Diaz-del-Rio, and Francisco Jiménez-Morales. "A Cellular Automata Agent-Based Hybrid Simulation Tool to Analyze the Deployment of Electric Vehicle Charging Stations." Sustainability 13, no. 10 (May 12, 2021): 5421. http://dx.doi.org/10.3390/su13105421.
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We present a hybrid model combining cellular automata (CA) and agent-based modeling (ABM) to analyze the deployment of electric vehicle charging stations through microscopic traffic simulations. This model is implemented in a simulation tool called SIMTRAVEL, which allows combining electric vehicles (EVs) and internal combustion engine vehicles (ICEVs) that navigate in a city composed of streets, avenues, intersections, roundabouts, and including charging stations (CSs). Each EV is modeled as an agent that incorporates complex behaviors, such as decisions about the route to destination or CS, when to drive to a CS, or which CS to choose. We studied three different CS arrangements for a synthetic city: a single large central CS, four medium sized distributed CSs or multiple small distributed CSs, with diverse amounts of traffic and proportions of EVs. The simulator output is found to be robust and meaningful and allows one to extract a first useful conclusion: traffic conditions that create bottlenecks around the CSs play a crucial role, leading to a deadlock in the city when the traffic density is above a certain critical level. Our results show that the best disposition is a distributed network, but it is fundamental to introduce smart routing measures to balance the distribution of EVs among CSs.
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Rath, Mamata, Bibudhendu Pati, and Binod Kumar Pattanayak. "Design and Development of Secured Framework for Efficient Routing in Vehicular Ad-Hoc Network." International Journal of Business Data Communications and Networking 15, no. 2 (July 2019): 55–72. http://dx.doi.org/10.4018/ijbdcn.2019070104.
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Due to many challenging issues in vehicular ad-hoc networks (VANETs), such as high mobility and network instability, this has led to insecurity and vulnerability to attacks. Due to dynamic network topology changes and frequent network re-configuration, security is a major target in VANET research domains. VANETs have gained significant attention in the current wireless network scenario, due to their exclusive characteristics which are different from other wireless networks such as rapid link failure and high vehicle mobility. In this are, the authors present a Secured and Safety Protocol for VANET (STVAN), as an intelligent Ad-Hoc On Demand Distance Vector (AODV)-based routing mechanism that prevents the Denial of Service attack (DoS) and improves the quality of service for secured communications in a VANET. In order to build a STVAN, the authors have considered a smart traffic environment in a smart city and introduced the concept of load balancing over VANET vehicles in a best effort manner. Simulation results reveal that the proposed STVAN accomplishes enhanced performance when compared with other similar protocols in terms of reduced delay, better packet delivery ratio, reasonable energy efficiency, increased network throughput and decreased data drop compared to other similar approach.
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Villegas-Ch, William, Xavier Palacios-Pacheco, and Sergio Luján-Mora. "Application of a Smart City Model to a Traditional University Campus with a Big Data Architecture: A Sustainable Smart Campus." Sustainability 11, no. 10 (May 20, 2019): 2857. http://dx.doi.org/10.3390/su11102857.
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Currently, the integration of technologies such as the Internet of Things and big data seeks to cover the needs of an increasingly demanding society that consumes more resources. The massification of these technologies fosters the transformation of cities into smart cities. Smart cities improve the comfort of people in areas such as security, mobility, energy consumption and so forth. However, this transformation requires a high investment in both socioeconomic and technical resources. To make the most of the resources, it is important to make prototypes capable of simulating urban environments and for the results to set the standard for implementation in real environments. The search for an environment that represents the socioeconomic organization of a city led us to consider universities as a perfect environment for small-scale testing. The proposal integrates these technologies in a traditional university campus, mainly through the acquisition of data through the Internet of Things, the centralization of data in proprietary infrastructure and the use of big data for the management and analysis of data. The mechanisms of distributed and multilevel analysis proposed here could be a powerful starting point to find a reliable and efficient solution for the implementation of an intelligent environment based on sustainability.
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Nasralla, Moustafa M. "Sustainable Virtual Reality Patient Rehabilitation Systems with IoT Sensors Using Virtual Smart Cities." Sustainability 13, no. 9 (April 23, 2021): 4716. http://dx.doi.org/10.3390/su13094716.
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To develop sustainable rehabilitation systems, these should consider common problems on IoT devices such as low battery, connection issues and hardware damages. These should be able to rapidly detect any kind of problem incorporating the capacity of warning users about failures without interrupting rehabilitation services. A novel methodology is presented to guide the design and development of sustainable rehabilitation systems focusing on communication and networking among IoT devices in rehabilitation systems with virtual smart cities by using time series analysis for identifying malfunctioning IoT devices. This work is illustrated in a realistic rehabilitation simulation scenario in a virtual smart city using machine learning on time series for identifying and anticipating failures for supporting sustainability.
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Ahmed, Mostafa, Ali Radwan, Ahmed Serageldin, Saim Memon, Takao Katsura, and Katsunori Nagano. "Thermal Analysis of a New Sliding Smart Window Integrated with Vacuum Insulation, Photovoltaic, and Phase Change Material." Sustainability 12, no. 19 (September 23, 2020): 7846. http://dx.doi.org/10.3390/su12197846.
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A zero-energy building (ZEB) requires an innovative integration of technologies, in which windows play a paramount role in energy reduction, storage, and generation. This study contributes to four innovative designs of sliding smart windows. It integrates air-gap (AG), phase change material (PCM), photovoltaic (PV), and vacuum glazing (VG) technologies. These smart sliding windows are proposed to generate electricity along with achieving efficient thermal insulations and heat storage simultaneously. A two-dimensional multiphysics thermal model that couples the PCM melting and solidification model, PV model, natural convection in the cavity, and the surface-to-surface radiation model in the vacuum gap are developed for the first time. The model is validated with data in the literature. The transient simulations were carried out to investigate the thermo-electrical performance of a window with an area of 1 m by 1 m for the meteorological conditions of Kuwait city on the 10th of June 2018, where the window was oriented to south direction. The results showed that the total solar heat energy gain per unit window area is 2.6 kWh, 0.02 kWh, 0.22 kWh, 1.48 kWh, and 0.2 kWh for the double AG, AG + PV + PCM + VG, PV + PCM + VG, AG + PV + PCM, and the ventilated AG + PV + PCM + VG, respectively. The results elucidate the advantages of the integration of VG in this integrated sliding smart window. The daily generated PV electrical energy in these systems is around 1.3 kWh, 1.43 kWh, and 1.38 kWh for the base case with double AG, PV + PCM + VG, and the ventilated AG + PV + PCM + VG respectively per unit window area.
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Jiang, Jinfang, Wenxing Tian, and Guangjie Han. "A Medium Access Control Protocol Based on Interference Cancellation Graph for AUV-Assisted Internet of Underwater Things." Sustainability 15, no. 6 (March 9, 2023): 4876. http://dx.doi.org/10.3390/su15064876.
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With the booming development of marine exploration technology, new studies such as the oceanix city, smart coastal city, and underwater smart cities have been proposed, and the Internet of Underwater Things (IoUT) has received a lot of attention. Data collection is an important application of the IoUT. The common method is to collect data by traversing the network using underwater intelligent devices, such as Autonomous Underwater Vehicles (AUVs). However, traditional data collection methods focus more on issues, such as path planning or the task assignment of AUVs. It is commonly known that the MAC protocol plays a crucial role in data transmission, which is designed to solve the competition issue for shared channels. However, the research on MAC is very challenging owing to the characteristics of hydroacoustic communication, e.g., the low bandwidth, high error rate, and long transmission latency. Hence, this paper proposes a MAC protocol based on an Interference Cancellation Graph (ICG-MAC) for AUV-assisted IoUT. It ensures that AUVs can join the network for data transmission immediately after arriving at the target area and they do not interfere with the normal work of other sensor nodes. Firstly, the target area to be reached by an AUV for data collection is defined according to the node degree and residual energy; then the interference model between neighboring nodes is analyzed and an Interference Cancellation Graphx is established, based on which the time slots are allocated for sensor nodes; and finally, the AUV moves to the target area for conflict-free data collection. The simulation results show that the proposed algorithm outperforms the comparison algorithms in terms of the network throughput and energy consumption. With the assistance of an AUV, better network connectivity and higher network traffic can be obtained.
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Huang, Xinxin, Gang Xu, and Fengtao Xiao. "Optimization of a Novel Urban Growth Simulation Model Integrating an Artificial Fish Swarm Algorithm and Cellular Automata for a Smart City." Sustainability 13, no. 4 (February 22, 2021): 2338. http://dx.doi.org/10.3390/su13042338.
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As one of the 17 Sustainable Development Goals, it is sensible to analysis historical urban land use characteristics and project the potentials of urban sustainable development for a smart city. The cellular automaton (CA) model is the widely applied in simulating urban growth, but the optimum parameters of variables driving urban growth in the model remains to be continued to improve. We propose a novel model integrating an artificial fish swarm algorithm (AFSA) and CA for optimizing parameters of variables in the urban growth model and make a comparison between AFSA-CA and other five models, which is used to study a 40-year urban land growth of Wuhan. We found that the urban growth types from 1995 to 2015 appeared relatively consistent, mainly including infilling, edge-expansion and distant-leap types in Wuhan, which a certain range of urban land growth on the periphery of the central area. Additionally, although the genetic algorithms (GA)-CA model and the AFSA-CA model among the six models due to the distance variables, the parameter value of the GA-CA model is −15.5409 according to the fact that the population (POP) variable should be positively. As a result, the AFSA-CA model regardless of the initial parameter setting is superior to the GA-CA model and the GA-CA model is superior to all the other models. Finally, it is projected that the potentials of urban growth in Wuhan for 2025 and 2035 under three scenarios (natural urban land growth without any restrictions (NULG), sustainable urban land growth with cropland protection and ecological security (SULG), and economic urban land growth with sustainable development and economic development in the core area (EULG)) focus mainly on existing urban land and some new town centers based on AFSA-CA urban growth simulation model. An increasingly precise simulation can determine the potential increase area and quantity of urban land, providing a basis to judge the layout of urban land use for urban planners.
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Anusha, T., and M. Pushpalatha. "Efficient Communication Model for a Smart Parking System with Multiple Data Consumers." Smart Cities 5, no. 4 (November 2, 2022): 1536–53. http://dx.doi.org/10.3390/smartcities5040078.
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A smart parking system (SPS) is an integral part of smart cities where Internet of Things (IoT) technology provides many innovative urban digital solutions. It offers hassle-free parking convenience to the city dwellers, metering facilities, and a revenue source for businesses, and it also protects the environment by cutting down drive-around emissions. The real-time availability information of parking slots and the duration of occupancy are valuable data utilized by multiple sectors such as parking management, charging electric vehicles (EV), car servicing, urban infrastructure planning, traffic regulation, etc. IPv6 wireless mesh networks are a good choice to implement a fail-safe, low-power and Internet protocol (IP)-based secure communication infrastructure for connecting heterogeneous IoT devices. In a smart parking lot, there could be a variety of local IoT devices that consume the occupancy data generated from the parking sensors. For instance, there could be a central parking management system, ticketing booths, display boards showing a count of free slots and color-coded lights indicating visual clues for vacancy. Apart from this, there are remote user applications that access occupancy data from browsers and mobile phones over the Internet. Both the types of data consumers need not collect their inputs from the cloud, as it is beneficial to offer local data within the network. Hence, an SPS with multiple data consumers needs an efficient communication model that provides reliable data transfers among producers and consumers while minimizing the overall energy consumption and data transit time. This paper explores different SPS communication models by varying the number of occupancy data collators, their positions, hybrid power cycles and data aggregation strategies. In addition, it proposes a concise data format for effective data dissemination. Based on the simulation studies, a multi-collator model along with a data superimposition technique is found to be the best for realizing an efficient smart parking system.
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Al-Turki, Mohammed, Arshad Jamal, Hassan M. Al-Ahmadi, Mohammed A. Al-Sughaiyer, and Muhammad Zahid. "On the Potential Impacts of Smart Traffic Control for Delay, Fuel Energy Consumption, and Emissions: An NSGA-II-Based Optimization Case Study from Dhahran, Saudi Arabia." Sustainability 12, no. 18 (September 9, 2020): 7394. http://dx.doi.org/10.3390/su12187394.
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Intelligent traffic control at urban intersections is vital to ensure efficient and sustainable traffic operations. Urban road intersections are hotspots of congestion and traffic accidents. Poor traffic management at these locations could cause numerous issues, such as longer travel time, low travel speed, long vehicle queues, delays, increased fuel consumption, and environmental emissions, and so forth. Previous studies have shown that the mentioned traffic performance measures or measures of effectiveness (MOEs) could be significantly improved by adopting intelligent traffic control protocols. The majority of studies in this regard have focused on mono or bi-objective optimization with homogenous and lane-based traffic conditions. However, decision-makers often have to deal with multiple conflicting objectives to find an optimal solution under heterogeneous stochastic traffic conditions. Therefore, it is essential to determine the optimum decision plan that offers the least conflict among several objectives. Hence, the current study aimed to develop a multi-objective intelligent traffic control protocol based on the non-dominated sorting genetic algorithm II (NSGA-II) at isolated signalized intersections in the city of Dhahran, Kingdom of Saudi Arabia. The MOEs (optimization objectives) that were considered included average vehicle delay, the total number of vehicle stops, average fuel consumption, and vehicular emissions. NSGA-II simulations were run with different initial populations. The study results showed that the proposed method was effective in optimizing considered performance measures along the optimal Pareto front. MOEs were improved in the range of 16% to 23% compared to existing conditions. To assess the efficacy of the proposed approach, an optimization analysis was performed using a Synchro traffic light simulation and optimization tool. Although the Synchro optimization resulted in a relatively lower signal timing plan than NSGA-II, the proposed algorithm outperformed the Synchro optimization results in terms of percentage reduction in MOE values.
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Osman, Ibrahim Sufian, and Nasir Ghazi Hariri. "Thermal Investigation and Optimized Design of a Novel Solar Self-Driven Thermomechanical Actuator." Sustainability 14, no. 9 (April 23, 2022): 5078. http://dx.doi.org/10.3390/su14095078.
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As the world moves toward cleaner and greener sources of energy, the use of solar energy appeals the most for countries in the Middle East and North Africa (MENA) region, since they have an abundant amount of solar radiation throughout the year. This paper offers a novel design for a shape memory alloy (SMA) actuator that uses solar energy to trigger thermomechanical behavior. Additionally, the proposed design of the thermomechanical actuator aims to be a piston-based linear actuator covered by a solar heat collector (SHC). Furthermore, the thermal behavior of the actuator has been studied in detail using a simulation-based study under the real-time weather conditions of Dammam city, Kingdom of Saudi Arabia (KSA). The thermal study proves that the optimized design of the thermomechanical actuator has achieved a minimum daily temperature variation of 10 °C, which enables the SMA-based thermomechanical actuator to operate in a daily manner throughout the year. Moreover, the presented numerical results show that the proposed thermomechanical actuator requires a twice-maintenance routine yearly. Additionally, it has been observed that the SHC, which is the central part of the designed thermomechanical actuator, can increase the temperature inside the actuator by about 15 °C more than ambient temperature. The proposed study adds to the body of knowledge a design for a passive, solar-driven, and self-actuating smart thermomechanical SMA actuator that is capable of integration with various solar applications, such as the cleaning and tracking of photovoltaic systems.
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Han, Tianran, Jianming Zhao, and Wenquan Li. "Smart-Guided Pedestrian Emergency Evacuation in Slender-Shape Infrastructure with Digital Twin Simulations." Sustainability 12, no. 22 (November 20, 2020): 9701. http://dx.doi.org/10.3390/su12229701.
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Rapid exploitation of city underground space has led to the development of increasingly more underground slender-shape infrastructure like pedestrian tunnels, concourses, subway walkways, underground shopping streets, etc. Pedestrian evacuation in those public places in case of emergency can be disastrous if not properly guided. Therefore, it is important to understand how to enhance the evacuation efficiency through proper active guidance. In this study, we propose a digital twin based guiding system for pedestrian emergency evacuation inside a slender-shape infrastructure, aiming at enhancing the overall evacuation efficiency. Composition and calibration process of the guiding system are described, and a cellular automata based model is established to serve as the digital twin model. Two guidance strategies, namely traditional fixed guidance and smart guidance, are adopted by the digital twin to generate guidance instructions. A smart guidance strategy using a semi-empirical approach is proposed based on the understanding of the free movement and congested movement of pedestrian flow. Systems under different guiding strategies are compared and discussed over their effectiveness to promote excavation efficiency in different pedestrian population distribution settings. The simulation results show that a system under smart guidance tends to have shorter evacuation time (up to 23.8% time saving) and performs with more stability for pedestrian evacuations over the traditional fixed guided systems. The study provides insight for potential real applications of a similar kind.
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Judeh, Tariq, Isam Shahrour, and Fadi Comair. "Smart Rainwater Harvesting for Sustainable Potable Water Supply in Arid and Semi-Arid Areas." Sustainability 14, no. 15 (July 28, 2022): 9271. http://dx.doi.org/10.3390/su14159271.
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This paper presents a smart rainwater harvesting (RWH) system to address water scarcity in Palestine. This system aims to improve the water harvesting capacity by using a shared harvesting system at the neighborhood level and digital technology. The presentation of this system is organized as follows: (i) identification of the challenges of the rainwater harvesting at the neighborhood level, (ii) design of the smart RWH system architecture that addresses the challenges identified in the first phase, (iii) realization of a simulation-based reliability analysis for the smart system performance. This methodology was applied to a residential neighborhood in the city of Jenin, Palestine. The main challenges of smart water harvesting included optimizing the shared tank capacity, and the smart control of the water quality and leakage. The smart RWH system architecture design is proposed to imply the crowdsourcing-based and automated-based smart chlorination unit to control and monitor fecal coliform and residual chlorine: screens, filters, and the first flush diverter address RWH turbidity. Water level sensors/meters, water flow sensors/meters, and water leak sensors help detect a water leak and water allocation. The potential time-based reliability (Re) and volumetric reliability (Rv) for the smart RWH system can reach 38% and 41%, respectively. The implication of the smart RWH system with a dual water supply results in full reliability indices (100%). As a result, a zero potable water shortage could be reached for the dual water supply system, compared to 36% for the municipal water supply and 59% for the smart RWH system. Results show that the smart RWH system is efficient in addressing potable water security, especially when combined with a dual water supply system.
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Corrado, Casey R., Suzanne M. DeLong, Emily G. Holt, Edward Y. Hua, and Andreas Tolk. "Combining Green Metrics and Digital Twins for Sustainability Planning and Governance of Smart Buildings and Cities." Sustainability 14, no. 20 (October 11, 2022): 12988. http://dx.doi.org/10.3390/su142012988.
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Creating a more sustainable world will require a coordinated effort to address the rise of social, economic, and environmental concerns resulting from the continuous growth of cities. Supporting planners with tools to address them is pivotal, and sustainability is one of the main objectives. Modeling and simulation augmenting digital twins can play an important role to implement these tools. Although various green best practices have been utilized over time and there are related attempts at measuring green success, works in the published literature tend to focus on addressing a single problem (e.g., energy efficiency), and a comprehensive approach that takes the multiple facets of sustainable urban planning into consideration has not yet been identified. This paper begins with a review of recent research efforts in green metrics and digital twins. This leads to developing an approach that evaluates organizational green best practices to derive metrics, which are used for computational decision support by digital twins. Furthermore, it leverages these research results and proposes a metric-driven framework for sustainability planning that understands a city as a sociotechnical complex system. Such a framework allows the practitioner to take advantage of recent developments and provides computational decision support for the complex challenge of sustainability planning at the various levels of urban planning and governance.
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Truong-Hong, L., F. Jia, E. Che, S. Emamgholian, D. Laefer, and A. V. Vo. "Preface: 3D GeoInfo 2021." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVI-4/W4-2021 (October 7, 2021): 1–4. http://dx.doi.org/10.5194/isprs-archives-xlvi-4-w4-2021-1-2021.
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Abstract. 3D GeoInfo 2021, the 16th GeoInfo conference, is an annual ISPRS workshop offering a forum for leading international decision makers and prominent voices in the field of 3D Geoinformation across the academic, commercial, and public sectors. The 2021 workshop is organized in conjunction with the 7th International FIG workshop on 3D Cadastres. The 2021 event was held virtually. Topics included: 3D data creation and acquisition 3D data processing and analysis 3D data management - data quality, metadata, provenance and trust Data integration, information fusion, multi-modal data analysis 3D visualization, including gamification, virtual reality, augmented reality 3D and Artificial Intelligence/Machine Learning 3D and Big Data, parallel computing, cloud computing 3D city modeling, underground infrastructure modeling, topography, and bathymetry modeling Building Information Modeling, Digital Twins, Smart Cities, Smart Infrastructure Usability and Human-Computer interaction in 3D GIS 3D GIS, spatial analysis and other applications (such as 3D cadastral systems, land administration, utilities, asset management, infrastructure, navigation, urban planning, geology, archaeology, marine systems, simulations, autonomous vehicles, facilities management, energy modeling, disaster and risk management, pandemic monitoring) The 3D GeoInfo 2021 tracks received 73 manuscripts including 30 full papers and 43 extended abstracts. The manuscripts were reviewed with a double-blind review process by members of the organizing and scientific committee and external reviewers. Ultimately 24 papers were accepted for the ISPRS Annals and 24 papers for the ISPRS Archives. We thank all of the authors and reviewers for their contributions.We look forward to the 3D GeoInfo 2021 virtual oral presentations and the opportunity to exchange ideas within our workshop and with the presenters and visitors of the 7th International FIG workshop on 3D Cadastres.
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Truong-Hong, L., F. Jia, E. Che, S. Emamgholian, D. Laefer, and A. V. Vo. "Preface: 3D GeoInfo 2021." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences VIII-4/W2-2021 (October 7, 2021): 1–4. http://dx.doi.org/10.5194/isprs-annals-viii-4-w2-2021-1-2021.
Full textAbstract:
Abstract. 3D GeoInfo 2021, the 16th GeoInfo conference, is an annual ISPRS workshop offering a forum for leading international decision makers and prominent voices in the field of 3D Geoinformation across the academic, commercial, and public sectors. The 2021 workshop is organized in conjunction with the 7th International FIG workshop on 3D Cadastres. The 2021 event was held virtually. Topics included: 3D data creation and acquisition 3D data processing and analysis 3D data management - data quality, metadata, provenance and trust Data integration, information fusion, multi-modal data analysis 3D visualization, including gamification, virtual reality, augmented reality 3D and Artificial Intelligence/Machine Learning 3D and Big Data, parallel computing, cloud computing 3D city modeling, underground infrastructure modeling, topography, and bathymetry modeling Building Information Modeling, Digital Twins, Smart Cities, Smart Infrastructure Usability and Human-Computer interaction in 3D GIS 3D GIS, spatial analysis and other applications (such as 3D cadastral systems, land administration, utilities, asset management, infrastructure, navigation, urban planning, geology, archaeology, marine systems, simulations, autonomous vehicles, facilities management, energy modeling, disaster and risk management, pandemic monitoring) The 3D GeoInfo 2021 tracks received 73 manuscripts including 30 full papers and 43 extended abstracts. The manuscripts were reviewed with a double-blind review process by members of the organizing and scientific committee and external reviewers. Ultimately 24 papers were accepted for the ISPRS Annals and 24 papers for the ISPRS Archives. We thank all of the authors and reviewers for their contributions.We look forward to the 3D GeoInfo 2021 virtual oral presentations and the opportunity to exchange ideas within our workshop and with the presenters and visitors of the 7th International FIG workshop on 3D Cadastres.
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He, Qing, Zhouxin Lan, Damin Zhang, Liu Yang, and Shihang Luo. "Improved Marine Predator Algorithm for Wireless Sensor Network Coverage Optimization Problem." Sustainability 14, no. 16 (August 11, 2022): 9944. http://dx.doi.org/10.3390/su14169944.
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A wireless sensor network (WSN) is a distributed network system composed of a great many sensor nodes that rely on self-organization. The random deployment of WSNs in city planning often leads to the problem of low coverage of monitoring areas. In the construction of smart cities in particular, a large number of sensor nodes need to be deployed to maintain the reception, processing, and transmission of data throughout the city. However, the uneven distribution of nodes can cause a lot of wasted resources. To solve this problem, this paper proposes a WSN coverage optimization model based on an improved marine predator algorithm (IMPA). The algorithm introduces a dynamic inertia weight adjustment strategy in the global exploration and local exploitation stages of the standard marine predator algorithm to balance the exploration and exploitation capabilities of the algorithm and improve its solution accuracy. At the same time, the improved algorithm uses a multi-elite random leading strategy to enhance the information exchange rate between population individuals and improve the algorithm’s ability to jump out of the local optimum. The optimization experiment results of 11 benchmark test functions and part of the CEC2014 test functions show that the optimization performance of the improved algorithm is significantly better than the standard marine predator algorithm and other algorithms in the literature. Finally, the improved algorithm is applied to the WSN coverage optimization problem. The simulation results demonstrate that the IMPA has a better coverage rate than other metaheuristic algorithms and other improved algorithms in the literature for solving the WSN coverage optimization problem.
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Zhao, Ziyao, Yi Zhang, Yi Zhang, Kaifeng Ji, and He Qi. "Neural-Network-Based Dynamic Distribution Model of Parking Space Under Sharing and Non-Sharing Modes." Sustainability 12, no. 12 (June 15, 2020): 4864. http://dx.doi.org/10.3390/su12124864.
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In recent years, with the rapid development of China’s automobile industry, the number of vehicles in China has been increasing steadily. Vehicles represent a convenient mode of travel, but the growth rate of the number of urban motor vehicles far exceeds the construction rate of parking facilities. The continuous improvement of parking allocation methods has always been key for ensuring sustainable city management. Thus, developing an efficient and dynamic parking distribution algorithm will be an important breakthrough to alleviate the urban parking shortage problem. However, the existing parking distribution models do not adequately consider the influence of real-time changes in parking demand and supply on parking space assignment. Therefore, this study proposed a method for dynamic parking allocation using parking demand predictions and a predictive control method. A neural-network-based dynamic parking distribution model was developed considering seven influencing factors: driving duration, walking distance, parking fee, traffic congestion, possibility of finding a parking space in the target parking lot and adjacent parking lot, and parking satisfaction degree. Considering whether the parking spaces in the targeted parking lots are shared or not, two allocation modes—sharing mode and non-sharing mode—were proposed and embedded into the model. At the experimental stage, a simulation case and a real-time case were performed to evaluate the developed models. The experimental results show that the dynamic parking distribution model based on neural networks can not only allocate parking spaces in real time but also improve the utilisation rate of different types of parking spaces. The performance score of the dynamic parking distribution model for a time interval of 2–20 min was maintained above 80%. In addition, the distribution performance of the sharing mode was better than that of the non-sharing mode and contributed to a better overall effectiveness. This model can effectively improve the utilisation rate of resources and the uniformity of distribution and can reduce the failure rate of parking; thus, it significantly contributes to more smart and sustainable urban parking management.