Search results for: smart transportation network

Authors: Amir Azaron

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In this research, a stochastic programming approach is developed for designing supply chains with uncertain parameters. Demands and selling prices of products at markets are considered as the uncertain parameters. The proposed mathematical model will be multi-period two-stage stochastic programming, which takes into account the selection of retailer sites, suppliers, production levels, inventory levels, transportation modes to be used for shipping goods, and shipping quantities among the entities of the supply chain network. The objective function is to maximize the chain’s net present value. In order to maximize the chain’s NPV, the sum of first-stage investment costs on retailers, and the expected second-stage processing, inventory-holding and transportation costs should be kept as low as possible over multiple periods. The effects of supply uncertainty where suppliers are unreliable will also be investigated on the efficiency of the supply chain.

Keywords: supply chain management, stochastic programming, multiobjective programming, inventory control

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Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

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‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.

Keywords: deep learning network, smart metering, water end use, water-energy data

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Authors: Abdelhadi Lotfi, Abdelkader Benyettou

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In this work, a training algorithm for probabilistic neural networks (PNN) is presented. The algorithm addresses one of the major drawbacks of PNN, which is the size of the hidden layer in the network. By using a cross-validation training algorithm, the number of hidden neurons is shrunk to a smaller number consisting of the most representative samples of the training set. This is done without affecting the overall architecture of the network. Performance of the network is compared against performance of standard PNN for different databases from the UCI database repository. Results show an important gain in network size and performance.

Keywords: classification, probabilistic neural networks, network optimization, pattern recognition

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Authors: Anca Radulescu, Danae Evans

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The relationship between a network’s hardwiring and its emergent dynamics are central to neuroscience. We study the principles of this correspondence in a canonical setup (in which network nodes exhibit well-studied complex quadratic dynamics), then test their universality in biological networks. By extending methods from discrete dynamics, we study the effects of network connectivity on temporal patterns, encapsulating long-term behavior into the rich topology of network Mandelbrot sets. Then elements of fractal geometry can be used to predict and classify network behavior.

Keywords: canonical model, complex dynamics, dynamic networks, fractals, Mandelbrot set, network connectivity

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Authors: Ghassan Kbar, Shady Aly, Ibrahim Alsharawy, Akshay Bhatia, Nur Alhasan, Ronaldo Enriquez

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The Smart Help for persons with disability (PWD) is a part of the project SMARTDISABLE which aims to develop relevant solution for PWD that target to provide an adequate workplace environment for them. It would support PWD needs smartly through smart help to allow them access to relevant information and communicate with other effectively and flexibly, and smart editor that assist them in their daily work. It will assist PWD in knowledge processing and creation as well as being able to be productive at the work place. The technical work of the project involves design of a technological scenario for the Ambient Intelligence (AmI) - based assistive technologies at the workplace consisting of an integrated universal smart solution that suits many different impairment conditions and will be designed to empower the Physically disabled persons (PDP) with the capability to access and effectively utilize the ICTs in order to execute knowledge rich working tasks with minimum efforts and with sufficient comfort level. The proposed technology solution for PWD will support voice recognition along with normal keyboard and mouse to control the smart help and smart editor with dynamic auto display interface that satisfies the requirements for different PWD group. In addition, a smart help will provide intelligent intervention based on the behavior of PWD to guide them and warn them about possible misbehavior. PWD can communicate with others using Voice over IP controlled by voice recognition. Moreover, Auto Emergency Help Response would be supported to assist PWD in case of emergency. This proposed technology solution intended to make PWD very effective at the work environment and flexible using voice to conduct their tasks at the work environment. The proposed solution aims to provide favorable outcomes that assist PWD at the work place, with the opportunity to participate in PWD assistive technology innovation market which is still small and rapidly growing as well as upgrading their quality of life to become similar to the normal people at the workplace. Finally, the proposed smart help solution is applicable in all workplace setting, including offices, manufacturing, hospital, etc.

Keywords: ambient intelligence, ICT, persons with disability PWD, smart application, SHW

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Authors: Luca Lezzerini

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Albania is suffering a continuous shrinking of its population and demographic distribution that faces all the problems connected with age increase. The paper examines the case of Gjirokastër, a city in the south of Albania that, despite having a UNESCO label as a world heritage site, is experimenting with the same shrinking phenomenon. The paper analyses in detail the current situation and propose an interdisciplinary approach based on smart technologies and sunset tourism to restart Gjirokastër’s economy and invert bad demographic trends. The proposed approach needs to review the current urban planning, reshaping and connecting some areas. It also proposes a smart city architecture to support this process.

Keywords: smart city, sunset tourism, shrinking city, Gjirokastër

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Authors: Mohamed Raouf Benmakrelouf, Wafa Karouche, Joseph Rynkiewicz

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In this paper, we propose an alternative method to construct a Bayesian Network (BN). This method relies on a convolutional neural network (CNN classifier), which determinates the edges of the network skeleton. We train a CNN on a normalized empirical probability density distribution (NEPDF) for predicting causal interactions and relationships. We have to find the optimal Bayesian network structure for causal inference. Indeed, we are undertaking a search for pair-wise causality, depending on considered causal assumptions. In order to avoid unreasonable causal structure, we consider a blacklist and a whitelist of causality senses. We tested the method on real data to assess the influence of education on the voting intention for the extreme right-wing party. We show that, with this method, we get a safer causal structure of variables (Bayesian Network) and make to identify a variable that satisfies the backdoor criterion.

Keywords: Bayesian network, structure learning, optimal search, convolutional neural network, causal inference

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Authors: K. Govender, M. Sinclair

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This paper demonstrates a proof of concept whereby shorter trips and land use densification can be promoted through an alternative approach to planning and implementation of road infrastructure in the South African context. It briefly discusses how the development of the Compact City concept relies on a combination of promoting shorter trips and densification through a change in focus in road infrastructure provision. The methodology developed in this paper uses a traffic model to test the impact of synthesized deterrence functions on congestion locations in the road network through the assignment of traffic on the study network. The results from this study demonstrate that intelligent planning of road infrastructure can indeed promote reduced urban sprawl, increased residential density and mixed-use areas which are supported by an efficient public transport system; and reduced dependence on the freeway network with a fixed road infrastructure budget. The study has resonance for all cities where urban sprawl is seemingly unstoppable.

Keywords: compact cities, densification, road infrastructure planning, transportation modelling

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Authors: Christopher Godwin Udomboso, Angela Unna Chukwu, Isaac Kwame Dontwi

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In selecting a Statistical Neural Network model, the Network Information Criterion (NIC) has been observed to be sample biased, because it does not account for sample sizes. The selection of a model from a set of fitted candidate models requires objective data-driven criteria. In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC), based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The analyses show that on a general note, the ANIC improves model selection in more sample sizes than does the NIC.

Keywords: statistical neural network, network information criterion, adjusted network, information criterion, transfer function

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Authors: Jacob Wahl, Jane Zhang

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This paper describes the development and characterization of a prototype IoT network for use with agricultural imaging and monitoring applications. The sensor and gateway nodes are designed using the ESP32 SoC with integrated Bluetooth Low Energy 4.2 and Wi-Fi. A development board, the Arducam IoTai ESP32, is used for prototyping, testing, and power measurements. Google’s Firebase is used as the cloud storage site for image data collected by the sensor. The sensor node captures images using the OV2640 2MP camera module and transmits the image data to the gateway via Bluetooth Low Energy. The gateway then uploads the collected images to Firebase via a known nearby Wi-Fi network connection. This image data can then be processed and analyzed by computer vision and machine learning pipelines to assess crop growth or other needs. The sensor node achieves a wireless transmission data throughput of 220kbps while consuming 150mA of current; the sensor sleeps at 162µA. The sensor node device lifetime is estimated to be 682 days on a 6600mAh LiPo battery while acquiring five images per day based on the development board power measurements. This network can be utilized by any application that requires high data rates, low power consumption, short-range communication, and large amounts of data to be transmitted at low-frequency intervals.

Keywords: Bluetooth low energy, ESP32, firebase cloud, IoT, smart farming

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Authors: Elham Jelodari Mamaghani, Christian Prins, Haoxun Chen

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In this paper, there is concentration on collaborative transportation planning (CTP) among multiple carriers with pickup and delivery requests and time windows. This problem is a vehicle routing problem with constraints from standard vehicle routing problems and new constraints from a real-world application. In the problem, each carrier has a finite number of vehicles, and each request is a pickup and delivery request with time window. Moreover, each carrier has reserved requests, which must be served by itself, whereas its exchangeable requests can be outsourced to and served by other carriers. This collaboration among carriers can help them to reduce total transportation costs. A mixed integer programming model is proposed to the problem. To solve the model, a hybrid algorithm that combines Genetic Algorithm and Simulated Annealing (GASA) is proposed. This algorithm takes advantages of GASA at the same time. After tuning the parameters of the algorithm with the Taguchi method, the experiments are conducted and experimental results are provided for the hybrid algorithm. The results are compared with those obtained by a commercial solver. The comparison indicates that the GASA significantly outperforms the commercial solver.

Keywords: centralized collaborative transportation, collaborative transportation with pickup and delivery, collaborative transportation with time windows, hybrid algorithm of GA and SA

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Authors: Bhavishya Ramchandani

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A little electronic device that is worn on the finger is called a smart ring. It incorporates mobile technology and has features that make it simple to use the device. These gadgets, which resemble conventional rings and are usually made to fit on the finger, are outfitted with features including access management, gesture control, mobile payment processing, and activity tracking. A poor sleep pattern, an irregular schedule, and bad eating habits are all part of the problems with health that a lot of people today are facing. Diets lacking fruits, vegetables, legumes, nuts, and whole grains are common. Individuals in India also experience metabolic issues. In the medical field, smart rings will help patients with problems relating to stomach illnesses and the incapacity to consume meals that are tailored to their bodies' needs. The smart ring tracks all bodily functions, including blood sugar and glucose levels, and presents the information instantly. Based on this data, the ring generates what the body will find to be perfect insights and a workable site layout. In addition, we conducted focus groups and individual interviews as part of our core approach and discussed the difficulties they're having maintaining the right diet, as well as whether or not the smart ring will be beneficial to them. However, everyone was very enthusiastic about and supportive of the concept of using smart rings in healthcare, and they believed that these rings may assist them in maintaining their health and having a well-balanced diet plan. This response came from the primary data, and also working on the Emerging Technology Canvas Analysis of smart rings in healthcare has led to a significant improvement in our understanding of the technology's application in the medical field. It is believed that there will be a growing demand for smart health care as people become more conscious of their health. The majority of individuals will finally utilize this ring after three to four years when demand for it will have increased. Their daily lives will be significantly impacted by it.

Keywords: smart ring, healthcare, electronic wearable, emerging technology

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Authors: Yang Zhou, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

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Traffic prediction is a fundamental problem in urban environment, facilitating the smart management of various businesses, such as taxi dispatching, bike relocation, and stampede alert. Most earlier methods rely on identifying the intrinsic spatial-temporal correlation to forecast. However, the complex nature of this problem entails a more sophisticated solution that can simultaneously capture the mutual influence of both adjacent and far-flung areas, with the information of time-dimension also incorporated seamlessly. To tackle this difficulty, we propose a new multi-phase architecture, DSTDS (Dual Spatial-Temporal Data Scheme for traffic prediction), that aims to reveal the underlying relationship that determines future traffic trend. First, a graph-based neural network with an attention mechanism is devised to obtain the static features of the road network. Then, a multi-granularity recurrent neural network is built in conjunction with the knowledge from a grid-based model. Subsequently, the preceding output is fed into a spatial-temporal super-resolution module. With this 3-phase structure, we carry out extensive experiments on several real-world datasets to demonstrate the effectiveness of our approach, which surpasses several state-of-the-art methods.

Keywords: traffic prediction, spatial-temporal, recurrent neural network, dual data scheme

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Authors: Andrey A. Chernousov, Ben Y. B. Chan

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The use of the low-cost paraffinic phase change material can be rather effective in smart building envelopes in the South China region. Particular attention has to be paid to the PCM optimization as an exploitation conditions and the envelope insulation changes its thermal characteristics. The studied smart building envelope consists of a reinforced aluminum exterior, polymeric insulation foam, phase change material and reinforced interior gypsum board. A prototype sample was tested to validate the numerical scheme using EnergryPlus software. Three scenarios of insulation thermal resistance loss (ΔR/R = 0%, 25%, 50%) were compared with the different PCM thicknesses (tP=0, 1, 2.5, 5 mm). The comparisons were carried out for a west facing enveloped office building (50 storey). PCM optimization was applied to find the maximum efficiency for the different ΔR/R cases. It was found, during the optimization, that the PCM is an important smart component, lowering the peak energy demand up to 2.7 times. The results are not influenced by the insulation aging in terms of ΔR/R during long-term exploitation. In hot and humid climates like Hong Kong, the insulation core of the smart systems is recommended to be laminated completely. This can be very helpful in achieving an acceptable payback period.

Keywords: smart building envelope, thermal performance, phase change material, energy efficiency, large-scale sandwich panel

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Authors: Navaneeth Krishnan, Chandan N. Bhagwat, Aparajit P. Utpat

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Cloud Computing provides us a means to upload data and use applications over the internet. As the number of devices connecting to the cloud grows, there is undue pressure on the cloud infrastructure. Fog computing or Network Based Computing or Edge Computing allows to move a part of the processing in the cloud to the network devices present along the node to the cloud. Therefore the nodes connected to the cloud have a better response time. This paper proposes a method of moving the computation from the cloud to the network by introducing an android like appstore on the networking devices.

Keywords: cloud computing, fog computing, network devices, appstore

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Authors: M. Kollar, A. Zieba

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In this paper, we present a method for a time synchronization between the two eNodeBs (eNBs) in E-UTRAN (Evolved Universal Terrestrial Radio Access) network. The two eNBs are cooperating in so-called inter eNB CA (Carrier Aggregation) case and connected via asymmetrical IP network. We solve the problem by using broadcasting signals generated in E-UTRAN as synchronization signals. The results show that the time synchronization with the proposed method is possible with the error significantly less than 1 ms which is sufficient considering the time transmission interval is 1 ms in E-UTRAN. This makes this method (with low complexity) more suitable than Network Time Protocol (NTP) in the mobile applications with generated broadcasting signals where time synchronization in asymmetrical network is required.

Keywords: IP scheduled throughput, E-UTRAN, Evolved Universal Terrestrial Radio Access Network, NTP, Network Time Protocol, assymetric network, delay

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Authors: Kolesnik Nadezda A.

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The research aims to elaborate inter-organizational network relationships management model to maximize value co-creation. We propose a network management framework that requires evaluation of network partners with respect to their position and role in network; and elaboration of appropriate relationship development strategy with partners in network. Empirical research and approval is based on the case study method, including structured in-depth interviews with the companies from b2b market.

Keywords: inter-organizational networks, value co-creation, model, B2B market

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Authors: Xincheng He, Weijun Gao, Gangwei Cai

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In the process of rapid urbanization, large-scale industrial production, and unreasonable planning and construction have caused various ecological and environmental problems, while hindered the sustainable development of cities. The ecological district not only realizes the coordinated development of society, economy, and environment but also conforms to the trend of smart contraction of the development of cities in China from the periphery to the center. This paper reviews the development of China's ecological district, including the full life cycle process of policy, planning, implementation, and operation. Based on sorting out the concept, connotation, and development status of China’s ecological district, the relationship between the construction of the ecological district and the sustainable city is discussed. Summarizing the development trend of the ecological district, the ecological district should combine the construction of smart cities, actively respond to the digital information era, and improve the construction of the ecological district system. It proposes that the future direction of city's sustainable development needs to change from a thematic focus on ecology to the common urbanization of humanity, society, and nature. Focusing on people-oriented, ecological, and digital future communities will become an important construction method for the city's sustainable smart contraction.

Keywords: eco-district, smart contraction, sustainable development, future community

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Authors: Sourour Ramzi, Claudia Sarrico

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Little has been done on network DEA in education, and nobody has attempted to model the whole education supply chain using network DEA. As such the contribution of the present paper is to propose a model for measuring the efficiency of education supply chains using network DEA. First, we use a general survey of data envelopment analysis (DEA) to establish the emergent themes for research in DEA, and focus on the theme of Network DEA. Second, we use a survey on two-stage DEA models, and Network DEA to write a state of the art on Network DEA, particularly applied to supply chain management. Third, we use a survey on DEA applications to establish the most influential papers on DEA education applications, in order to establish the state of the art on applications of DEA in education, in general, and applications of DEA to education using network DEA, in particular. Finally, we propose a model for measuring the performance of education supply chains of different education systems (countries or states within a country, for instance). We then use this model on some empirical data.

Keywords: supply chain, education, data envelopment analysis, network DEA

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Authors: Muhammad Ahnaf Zahin, Yaw Adu-Gyamfi

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Bus transit is a crucial component of transportation networks, especially in urban areas. Any intelligent transportation system must have accurate real-time information on bus travel times since it minimizes waiting times for passengers at different stations along a route, improves service reliability, and significantly optimizes travel patterns. Bus agencies must enhance the quality of their information service to serve their passengers better and draw in more travelers since people waiting at bus stops are frequently anxious about when the bus will arrive at their starting point and when it will reach their destination. For solving this issue, different models have been developed for predicting bus travel times recently, but most of them are focused on smaller road networks due to their relatively subpar performance in high-density urban areas on a vast network. This paper develops a deep learning-based architecture using a single-step multi-station forecasting approach to predict average bus travel times for numerous routes, stops, and trips on a large-scale network using heterogeneous bus transit data collected from the GTFS database. Over one week, data was gathered from multiple bus routes in Saint Louis, Missouri. In this study, Gated Recurrent Unit (GRU) neural network was followed to predict the mean vehicle travel times for different hours of the day for multiple stations along multiple routes. Historical time steps and prediction horizon were set up to 5 and 1, respectively, which means that five hours of historical average travel time data were used to predict average travel time for the following hour. The spatial and temporal information and the historical average travel times were captured from the dataset for model input parameters. As adjacency matrices for the spatial input parameters, the station distances and sequence numbers were used, and the time of day (hour) was considered for the temporal inputs. Other inputs, including volatility information such as standard deviation and variance of journey durations, were also included in the model to make it more robust. The model's performance was evaluated based on a metric called mean absolute percentage error (MAPE). The observed prediction errors for various routes, trips, and stations remained consistent throughout the day. The results showed that the developed model could predict travel times more accurately during peak traffic hours, having a MAPE of around 14%, and performed less accurately during the latter part of the day. In the context of a complicated transportation network in high-density urban areas, the model showed its applicability for real-time travel time prediction of public transportation and ensured the high quality of the predictions generated by the model.

Keywords: gated recurrent unit, mean absolute percentage error, single-step forecasting, travel time prediction.

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Authors: Jaqueline Nichi, Leila Da Costa Ferreira, Fabiana Barbi Seleguim, Gabriela Marques Di Giulio, Mariana Barbieri

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The transport sector is responsible for approximately 55% of global greenhouse gas (GHG) emissions, in addition to pollution and other negative externalities, such as road accidents and congestion, that impact the routine of those who live in large cities. The objective of this article is to discuss the application and use of distinct mobility technologies such as climate adaptation and mitigation measures in the context of smart cities in the Global South. The documentary analysis is associated with 22 semi structured interviews with managers who work with mobility technologies in the public and private sectors and in civil society organizations to explore solutions in multilevel governance for smart and low-carbon mobility based on the case study from the city of São Paulo, Brazil. The hypothesis that innovation and technology to mitigate and adapt to climate impacts are not yet sufficient to make mobility more sustainable has been confirmed. The results indicate four relevant aspects for advancing a climate agenda in smart cities: integrated planning, coproduction of knowledge, experiments in governance, and new means of financing to guarantee the sustainable sociotechnical transition of the sector.

Keywords: urban mobility, climate change, smart cities, multilevel governance

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Authors: Sandeep Singh Waraich

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Wireless sensor network (WSN ) consists of a large number of sensor nodes. The disparity in their energy consumption usually lead to the loss of equilibrium in wireless sensor network which may further results in an energy hole problem in wireless network. In this paper, we have considered the inclusion of orphan nodes which usually remain unutilized as intermediate nodes in multi-hop routing. The Orphan Node Inclusion (ONI) Protocol lets the cluster member to bring the orphan nodes into their clusters, thereby saving important resources and increasing network lifetime in critical applications of WSN.

Keywords: wireless sensor network, orphan node, clustering, ONI protocol

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Authors: Raymond Chi Fai Si Tou, Jacey Ja Young Choe, Amy Siu Ian So

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Smart hotels can be defined as the hotel which has an intelligent system, through digitalization and networking which achieve hotel management and service information. In addition, smart hotels include high-end designs that integrate information and communication technology with hotel management fulfilling the guests’ needs and improving the quality, efficiency and satisfaction of hotel management. The purpose of this study is to identify appropriate factors that may influence guests’ satisfaction and intention to revisit Smart Hotels based on service quality measurement of lodging quality index and extended UTAUT theory. Unified Theory of Acceptance and Use of Technology (UTAUT) is adopted as a framework to explain technology acceptance and use. Since smart hotels are technology-based infrastructure hotels, UTATU theory could be as the theoretical background to examine the guests’ acceptance and use after staying in smart hotels. The UTAUT identifies four key drivers of the adoption of information systems: performance expectancy, effort expectancy, social influence, and facilitating conditions. The extended UTAUT modifies the definitions of the seven constructs for consideration; the four previously cited constructs of the UTAUT model together with three new additional constructs, which including hedonic motivation, price value and habit. Thus, the seven constructs from the extended UTAUT theory could be adopted to understand their intention to revisit smart hotels. The service quality model will also be adopted and integrated into the framework to understand the guests’ intention of smart hotels. There are rare studies to examine the service quality on guests’ satisfaction and intention to revisit in smart hotels. In this study, Lodging Quality Index (LQI) will be adopted to measure the service quality in smart hotels. Using integrated UTAUT theory and service quality model because technological applications and services require using more than one model to understand the complicated situation for customers’ acceptance of new technology. Moreover, an integrated model could provide more perspective insights to explain the relationships of the constructs that could not be obtained from only one model. For this research, ten in-depth interviews are planned to recruit this study. In order to confirm the applicability of the proposed framework and gain an overview of the guest experience of smart hotels from the hospitality industry, in-depth interviews with the hotel guests and industry practitioners will be accomplished. In terms of the theoretical contribution, it predicts that the integrated models from the UTAUT theory and the service quality will provide new insights to understand factors that influence the guests’ satisfaction and intention to revisit smart hotels. After this study identifies influential factors, smart hotel practitioners could understand which factors may significantly influence smart hotel guests’ satisfaction and intention to revisit. In addition, smart hotel practitioners could also provide outstanding guests experience by improving their service quality based on the identified dimensions from the service quality measurement. Thus, it will be beneficial to the sustainability of the smart hotels business.

Keywords: intention to revisit, guest satisfaction, qualitative interviews, smart hotels

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Authors: Mohammed Alruwaili‬

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Nowadays, renewable energy resources are playing an important role in replacing traditional energy resources such as fossil fuels by integrating solar energy with conventional energy. Concerns about the environment led to an intensive search for a renewable energy source. The Rapid growth of distributed energy resources will have prompted increasing interest in the integrated distributing network in the Kingdom of Saudi Arabia next few years, especially after the adoption of new laws and regulations in this regard. Photovoltaic energy is one of the promising renewable energy sources that has grown rapidly worldwide in the past few years and can be used to produce electrical energy through the photovoltaic process. The main objective of the research is to study the impact of PV in distribution networks based on real data and details. In this research, site survey and computer simulation will be dealt with using the well-known computer program software ETAB to simulate the input of electrical distribution lines with other variable inputs such as the levels of solar radiation and the field study that represent the prevailing conditions and conditions in Diriah, Riyadh region, Saudi Arabia. In addition, the impact of adding distributed generation units (DGs) to the distribution network, including solar photovoltaic (PV), will be studied and assessed for the impact of adding different power capacities. The result has been achieved with less power loss in the loop distribution network from the current condition by more than 69% increase in network power loss. However, the studied network contains 78 buses. It is hoped from this research that the efficiency, performance, quality and reliability by having an enhancement in power loss and voltage profile of the distribution networks in Riyadh City. Simulation results prove that the applied method can illustrate the positive impact of PV in loop distribution generation.

Keywords: renewable energy, smart grid, efficiency, distribution network

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Authors: Ebrahim Fataei, Seyed Ali Hosseini, Zahra Arabi, Habib farhadi, Mehdi Aalipour Erdi, Seiied Taghi Seiied Safavian

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Solid waste production is an integral part of human life and management of waste require full scientific approach and essential planning. The allocation of most management cost to collection and transportation and also the necessity of operational efficiency in this system, by limiting time consumption, and on the other hand optimum collection system and transportation is the base of waste design and management. This study was done to optimize the exits collection and transportation system of solid waste in Meshkinshahr city. So based on the analyzed data of municipal solid waste components in seven zones of Meshkinshahr city, and GIS software, applied to design storage place based on origin recycling and a route to collect and transport. It was attempted to represent an appropriate model to store, collect and transport municipal solid waste. The result shows that GIS can be applied to locate the waste container and determine a waste collection direction in an appropriate way.

Keywords: municipal solid waste management, transportation, optimizing, GIS, Iran

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Authors: Zhang Dongqing

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Concern for students' mental health and the application of intelligent advanced technologies are driving changes in teaching models. The traditional teacher-centered classroom is beginning to transform into a student-centered smart interactive learning environment. Nowadays, smart classrooms are compatible with constructivist learning. This theory emphasizes the role of teachers in the teaching process as helpers and facilitators of knowledge construction, and students learn by interacting with them. The spatial design of classrooms is closely related to the teaching model and should also be developed in the direction of smart classroom design. The goal is to explore the impact of smart classroom layout on student-centered teaching environment and teacher-student interaction under the guidance of constructivist learning theory, by combining the design process and feedback analysis of the smart transformation project on the campus of Tongji University in Shanghai. During the research process, the theoretical basis of constructivist learning was consolidated through literature research and case analysis. The integration and visual field analysis of the traditional and transformed indoor floor plans were conducted using space syntax tools. Finally, questionnaire surveys and interviews were used to collect data. The main conclusions are as followed: flexible spatial layouts can promote students' learning effects and mental health; the interactivity of smart classroom layouts is different and needs to be combined with different teaching models; the public areas of teaching buildings can also improve the interactive learning atmosphere by adding discussion space. This article provides a data-based research basis for improving students' learning effects and mental health, and provides a reference for future smart classroom design.

Keywords: spatial layout, smart classroom, space syntax, renovation, educational environment

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Authors: Prajamitra Bhuyan

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Transport operators have a range of intervention options available to improve or enhance their networks. But often such interventions are made in the absence of sound evidence on what outcomes may result. Cycling superhighways were promoted as a sustainable and healthy travel mode which aims to cut traffic congestion. The estimation of the impacts of the cycle superhighways on congestion is complicated due to the non-random assignment of such intervention over the transport network. In this paper, we analyse the causal effect of cycle superhighways utilising pre-innervation and post-intervention information on traffic and road characteristics along with socio-economic factors. We propose a modeling framework based on the propensity score and outcome regression model. The method is also extended to doubly robust set-up. Simulation results show the superiority of the performance of the proposed method over existing competitors. The method is applied to analyse a real dataset on the London transport network, and the result would help effective decision making to improve network performance.

Keywords: average treatment effect, confounder, difference-in-difference, intelligent transportation system, potential outcome

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Authors: Christopher Meyer, Laima Gerlitz

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European Ports are about to take an important step towards their future economic development. Existing legislatives such as the European Green Deal are changing the perspective on ports as individual logistic institutions and demand a more holistic view on ports in their characteristic as ecosystem involving several different actors in an interdisciplinary and multilevel approach. A special role is taken by small and medium-sized ports facing the same political restriction and future goals - such as reducing environmental impacts with 2030 and 2050 as targets - while suffering from low financing capacity, outdated infrastructure, low innovation measures and missing political support. In contrast, they are playing a key role in regional economic development and cross-border logistics as well as facilitator for the regional hinterland. Also, in comparison to their big counterparts, small and medium-sized ports are often located within or close to city areas. This does not only bear more challenges especially when it comes to the environmental performance, but can also carry out growth potentials by putting the city as a key actor into the port ecosystem. For city development, the Smart City concept is one of the key strategies currently applied mostly on demonstration level in selected cities. Hence, the basic idea behind is par to the Smart Port concept. Thus, this paper is analysing potential synergetic effects resulting from the application of Smart City and Smart Port concepts for small and medium-sized ports' ecosystems closely located to cities with focus on innovation application, greening measurements and economic performances as well as strategic positioning of the ports in Smart City initiatives.

Keywords: port-city ecosystems, regional development, sustainability transition, innovation policy

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Authors: Manverpreet Kaur, Amarpreet Singh

Abstract:

The demand of Vehicular ad hoc networks is increasing day by day, due to offering the various applications and marvelous benefits to VANET users. Clustering in VANETs is most important to overcome the connectivity problems of VANETs. In this paper, we proposed a new clustering technique Enhanced cluster based connectivity maintenance in vehicular ad hoc network. Our objective is to form long living clusters. The proposed approach is grouping the vehicles, on the basis of the longest list of neighbors to form clusters. The cluster formation and cluster head selection process done by the RSU that may results it reduces the chances of overhead on to the network. The cluster head selection procedure is the vehicle which has closest speed to average speed will elect as a cluster Head by the RSU and if two vehicles have same speed which is closest to average speed then they will be calculate by one of the new parameter i.e. distance to their respective destination. The vehicle which has largest distance to their destination will be choosing as a cluster Head by the RSU. Our simulation outcomes show that our technique performs better than the existing technique.

Keywords: VANETs, clustering, connectivity, cluster head, intelligent transportation system (ITS)

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Authors: Tarathorn Podcharathitikull, Jirarat Teeravaraprug

Abstract:

Transportation cost is the highest cost in logistics cost of Thailand, and truck transportation is counted as about 90% of the overall transportation cost. The main problem of truck transportation is backhauling. Backhauling has become an attractive cost-saving approach in logistics. To explore such opportunities, this paper investigated the current backhauling systems in Thailand. It was found that the backhauling problem is attracted to both governmental agencies and private sector. They gave attempts to build backhauling systems. This paper investigated two systems built by governmental agencies and one by private sector. Moreover, based on the interviews with the system representatives and users, pros and cons of the systems were found. The obstacles and challenges were obtained. This paper finally proposed a conceptual model of to-be backhauling system in Thailand.

Keywords: backhauling system, backhauls, interview, Thailand

Procedia PDF Downloads 257