Search results for: Korean smart cities

Authors: Asrat M.Belachew, Tiago Pereira, Institute of Mathematics, Computer Sciences, Avenida Trabalhador São Carlense, 400, São Carlos, 13566-590, Brazil

Abstract:

Infectious diseases are among the most prominent threats to human beings. They cause morbidity and mortality to an individual and collapse the social, economic, and political systems of the whole world collectively. Mathematical models are fundamental tools and provide a comprehensive understanding of how infectious diseases spread and designing the control strategy to mitigate infectious diseases from the host population. Modeling the spread of infectious diseases using a compartmental model of inhomogeneous populations is good in terms of complexity. However, in the real world, there is a situation that accounts for heterogeneity, such as ages, locations, and contact patterns of the population which are ignored in a homogeneous setting. In this work, we study how classical an SEIR infectious disease spreading of the compartmental model can be extended by incorporating the mobility of population between heterogeneous cities during an outbreak of infectious disease. We have formulated an SEIR multi-cities epidemic spreading model using a system of 4k ordinary differential equations to describe the disease transmission dynamics in k-cities during the day and night. We have shownthat the model is epidemiologically (i.e., variables have biological interpretation) and mathematically (i.e., a unique bounded solution exists all the time) well-posed. We constructed the next-generation matrix (NGM) for the model and calculated the basic reproduction number R0for SEIR-epidemic spreading model with cities mobility. R0of the disease depends on the spectral radius mobility operator, and it is a threshold between asymptotic stability of the disease-free equilibrium and disease persistence. Using the eigenvalue perturbation theorem, we showed that sending a fraction of the population between cities decreases the reproduction number of diseases in interconnected cities. As a result, disease transmissiondecreases in the population.

Keywords: SEIR-model, mathematical model, city mobility, epidemic spreading

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Authors: Eu Tteum Ha, Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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The smart home environment backed up by IoT (internet of things) technologies enables intelligent services based on the awareness of the situation a user is currently in. One of the convenient sensors for recognizing the situations within a home is the smart meter that can monitor the status of each electrical appliance in real time. This paper aims at learning a Bayesian network that models the causal relationship between the user situations and the status of the electrical appliances. Using such a network, we can infer the current situation based on the observed status of the appliances. However, learning the conditional probability tables (CPTs) of the network requires many training examples that cannot be obtained unless the user situations are closely monitored by any means. This paper proposes a method for learning the CPT entries of the network relying only on the user feedbacks generated occasionally. In our case study with a robot vacuum cleaner, the feedback comes in whenever the user gives an order to the robot adversely from its preprogrammed setting. Given a network with randomly initialized CPT entries, our proposed method uses this feedback information to adjust relevant CPT entries in the direction of increasing the probability of recognizing the desired situations. Simulation experiments show that our method can rapidly improve the recognition performance of the Bayesian network using a relatively small number of feedbacks.

Keywords: Bayesian network, IoT, learning, situation -awareness, smart home

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Authors: Pushplata Garg

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Mobility, is an integral part of living and sustainability of urban mobility, is essential not only for, but also for addressing global warming and climate change. However, very little is understood about the obstacles/hurdles and likely challenges in the success of plans for sustainable urban mobility in Indian cities from the public perspective. Whereas some of the problems and issues are common to all cities, others vary considerably with financial status, function, the size of cities and culture of a place. Problems and issues similar in all cities relate to availability, efficiency and safety of public transport, last mile connectivity, universal accessibility, and essential planning and design requirements of pedestrians and cyclists are same. However, certain aspects like the type of means of public transportation, priority for cycling and walking, type of roadside activities, are influenced by the size of the town, average educational and income level of public, financial status of the local authorities, and culture of a place. The extent of public awareness, civic sense, maintenance of public spaces and law enforcement vary significantly from large metropolitan cities to small and medium towns in countries like India. Besides, design requirements for shading, location of public open spaces and sitting areas, street furniture, landscaping also vary depending on the climate of the place. Last mile connectivity plays a major role in success/ effectiveness of public transport system in a city. In addition to the provision of pedestrian footpaths connecting important destinations, sitting spaces and necessary amenities/facilities along footpaths; pedestrian movement to public transit stations is encouraged by the presence of quality roadside public spaces. It is not only the visual attractiveness of streetscape or landscape or the public open spaces along pedestrian movement channels but the activities along that make a street vibrant and attractive. These along with adequate spaces to rest and relax encourage people to walk as is observed in cities with successful public transportation systems. The paper discusses problems and issues of pedestrians for last mile connectivity in the context of Delhi, Chandigarh, Gurgaon, and Roorkee- four Indian cities representing varying urban contexts, that is, of metropolitan, large and small cities.

Keywords: pedestrianisation, roadside public spaces, last mile connectivity, sustainable urban mobility

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Authors: Chitresh Kumar, Santanu Gupta

Abstract:

The research work intends to understand the process of initiation, planning and development of capital-intensive urban area level infrastructure development in East Asian Cities (specific to Indian Cities). With the onset of emphasis on sustainable urban transport, self-financed urban local bodies, it has become of utmost important to identify infrastructure and projects on a priority basis, which provide optimal utility to the urban area. Through identification of Spatial, Demographic and Socio-Economic and Political Instability Parameters and their trends for the past 60 years at the urban area and state level, the paper attempts to identify the most suitable time period when initiation of the project would become economically and demographically viable for the city.

Keywords: urban planning, regional planning, mass transit, infrastructure development, spatial planning

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Authors: Chen Xi, Liu Xuebing, Lao Xueru, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

Abstract:

To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behavior recognition models, to provide empirical data such as 'pedestrian flow data and human behavioral characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, sustainable development

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Authors: Fikiru Temesgen Gelata

Abstract:

Food security, adaptation, and climate change mitigation are all problems that can be resolved simultaneously with Climate-Smart Agriculture (CSA). This study examines determinants of climate-smart agriculture (CSA) practices among smallholder farmers, aiming to understand the factors guiding adoption decisions and evaluate the impact of CSA on smallholder farmer income in the study areas. For this study, three-stage sampling techniques were applied to select 230 smallholders randomly. Mann-Kendal test and multinomial endogenous switching regression model were used to analyze trends of decrease or increase within long-term temporal data and the impact of CSA on the smallholder farmer income, respectively. Findings revealed education level, household size, land ownership, off-farm income, climate information, and contact with extension agents found to be highly adopted CSA practices. On the contrary, erosion exerted a detrimental impact on all the agricultural practices examined within the study region. Various factors such as farming methods, the size of farms, proximity to irrigated farmlands, availability of extension services, distance to market hubs, and access to weather forecasts were recognized as key determinants influencing the adoption of CSA practices. The multinomial endogenous switching regression model (MESR) revealed that joint adoption of crop rotation and soil and water conservation practices significantly increased farm income by 1,107,245 ETB. The study recommends that counties and governments should prioritize addressing climate change in their development agendas to increase the adoption of climate-smart farming techniques.

Keywords: climate-smart practices, food security, Oincome, MERM, Ethiopia

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Authors: Mehdi Attia, Sana Ben Fadhel, Lamjed Bettaieb

Abstract:

Mobile technology has become a part of our daily lives and assist learners (despite their level and age) in their leaning process using various apparatus and mobile devices (laptop, tablets, etc.). This paper presents a new learning framework based on tablets. This solution has been developed and tested in ESPRIT “Ecole Supérieure Privée d’Igénieurie et de Technologies”, a Tunisian school of engineering. This application is named ESSF: Esprit Smart School Framework. In this work, the main features of the proposed solution are listed, particularly its impact on the learners’ evaluation process. Learner’s assessment has always been a critical component of the learning process as it measures students’ knowledge. However, traditional evaluation methods in which the learner is evaluated once or twice each year cannot reflect his real level. This is why a continuous assessment (CA) process becomes necessary. In this context we have proved that ESSF offers many important features that enhance and facilitate the implementation of the CA process.

Keywords: continuous assessment, mobile learning, tablet based learning, smart school, ESSF

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Authors: Veniamin Boiarkin, Bruno Bogaz Zarpelão, Muttukrishnan Rajarajan

Abstract:

The manufacturing sector is a vital component of most economies, which leads to a large number of cyberattacks on organisations, whereas disruption in operation may lead to significant economic consequences. Adversaries aim to disrupt the production processes of manufacturing companies, gain financial advantages, and steal intellectual property by getting unauthorised access to sensitive data. Access to sensitive data helps organisations to enhance the production and management processes. However, the majority of the existing data-sharing mechanisms are either susceptible to different cyber attacks or heavy in terms of computation overhead. In this paper, a privacy-preserving data-sharing scheme for smart utilities is proposed. First, a customer’s privacy adjustment mechanism is proposed to make sure that end-users have control over their privacy, which is required by the latest government regulations, such as the General Data Protection Regulation. Secondly, a local differential privacy-based mechanism is proposed to ensure the privacy of the end-users by hiding real data based on the end-user preferences. The proposed scheme may be applied to different industrial control systems, whereas in this study, it is validated for energy utility use cases consisting of smart, intelligent devices. The results show that the proposed scheme may guarantee the required level of privacy with an expected relative error in utility.

Keywords: data-sharing, local differential privacy, manufacturing, privacy-preserving mechanism, smart utility

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Authors: Robin Ruowei Yang

Abstract:

The Khitan-Liao dynasty (907-1125) was founded by the nomadic Khitan people and showed its peculiarities. This regime not only effectively ruled their own nomads, but also ruled the farming ethnic groups of the Han (漢) and others. It also controlled vast territories that included the northern border domains of China, East Asia, and even Central Asia. Different from the practice of other nomadic people, Khitan-Liao built settlement towns and cities on the Mongolia steppe from beginning of the dynasty, which made the politics, economy and culture of the steppe area develop significantly. In the process of cities’ construction, Khitan-Liao set up five capitals respectively. Except three of them were rebuilt or expanded based on existing cities in agricultural areas, two new capitals were built, namely up-capital (Shangjing) and middle-capital (Zhongjing) in the steppe area. This article takes the up-capital (Shangjing) as an example to investigate a special zone in the capital for settling movable tents which adapted Khitan nomads, especially its nomadic government officials to live in. By using primary Chinese historical records and newly archaeological excavations, this article examines how the special tent zone used by the Khitan rulers, discusses how the Khitan-Liao manifested its hybrid cultural characteristics in urban planning, and its implications in studying the history of Khitan-Liao. The information, discussion and argument presented in this article are also worth considering the influence of urbanization of Khitan-Liao’s urbaization on subsequent dynasties in pre-modern China and Inner Asia.

Keywords: cities on Steppe, special tent zone in cities, Khitan-Liao, hybrid culture

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Authors: Marcos Valdez Alexander Junior, Igor Aguilar-Alonso

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Malnutrition is the root of different diseases that universally affect everyone, diseases such as obesity and malnutrition. The objective of this research is to predict the calories of the food to be eaten, developing a smart mobile application to show the user if a meal is balanced. Due to the large percentage of obesity and malnutrition in Peru, the present work is carried out. The development of the intelligent application is proposed with a three-layer architecture, and for the prediction of the nutritional value of the food, the use of pre-trained models based on convolutional neural networks is proposed.

Keywords: volume estimation, calorie estimation, artificial vision, food nutrition

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Authors: Prince Dacosta Aboagye, Ayyoob Sharifi

Abstract:

Cities respond to climate concerns mainly through their climate action plans (CAPs). A comprehensive content analysis of the dynamics in existing urban CAPs is not well represented in the literature. This literature void presents a difficulty in appreciating the strengths and weaknesses of urban CAPs. Here, we perform a qualitative content analysis (QCA) on CAPs from 278 cities worldwide and use text-mining tools to map and visualize the relevant data. Our analysis showed a decline in the number of CAPs developed and published following the global COVID-19 lockdown period. Evidently, megacities are leading the deep decarbonisation agenda. We also observed a transition from developing mainly mitigation-focused CAPs pre-COP21 to both mitigation and adaptation CAPs. A lack of inclusiveness in local climate planning was common among European and North American cities. The evidence is a catalyst for understanding the trends in existing urban CAPs to shape future urban climate planning.

Keywords: urban, climate action plans, strengths, weaknesses

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Authors: Harris Niavis, Dimitra Politaki

Abstract:

The manufacturing industry was collecting vast amounts of data for monitoring product quality thanks to the advances in the ICT sector and dedicated IoT infrastructure is deployed to track and trace the production line. However, industries have not yet managed to unleash the full potential of these data due to defective data collection methods and untrusted data storage and sharing. Blockchain is gaining increasing ground as a key technology enabler for Industry 4.0 and the smart manufacturing domain, as it enables the secure storage and exchange of data between stakeholders. On the other hand, AI techniques are more and more used to detect anomalies in batch and time-series data that enable the identification of unusual behaviors. The proposed scheme is based on smart contracts to enable automation and transparency in the data exchange, coupled with anomaly detection algorithms to enable reliable data ingestion in the system. Before sensor measurements are fed to the blockchain component and the smart contracts, the anomaly detection mechanism uniquely combines artificial intelligence models to effectively detect unusual values such as outliers and extreme deviations in data coming from them. Specifically, Autoregressive integrated moving average, Long short-term memory (LSTM) and Dense-based autoencoders, as well as Generative adversarial networks (GAN) models, are used to detect both point and collective anomalies. Towards the goal of preserving the privacy of industries' information, the smart contracts employ techniques to ensure that only anonymized pointers to the actual data are stored on the ledger while sensitive information remains off-chain. In the same spirit, blockchain technology guarantees the security of the data storage through strong cryptography as well as the integrity of the data through the decentralization of the network and the execution of the smart contracts by the majority of the blockchain network actors. The blockchain component of the Data Traceability Software is based on the Hyperledger Fabric framework, which lays the ground for the deployment of smart contracts and APIs to expose the functionality to the end-users. The results of this work demonstrate that such a system can increase the quality of the end-products and the trustworthiness of the monitoring process in the smart manufacturing domain. The proposed AI-enabled data traceability software can be employed by industries to accurately trace and verify records about quality through the entire production chain and take advantage of the multitude of monitoring records in their databases.

Keywords: blockchain, data quality, industry4.0, product quality

Procedia PDF Downloads 180

Authors: Kichan Lee, Kwang-Ho Choi, Mi-Hye Hwang, Young Min Son, Bang-Hun Hyun, Byeong Yeal Jung

Abstract:

Recently, worldwide food safety authorities have been strengthening food hygiene in order to curb foodborne illness outbreaks. The hygiene status of Korean slaughterhouses has been monitored annually by Animal and Plant Quarantine Agency and provincial governments through foodborne pathogens investigation using slaughtered pig and cattle meats. This study presented the prevalence of food-borne pathogens from 2014 to 2016 in Korean slaughterhouses. Sampling, microbiological examinations, and analysis of results were performed in accordance with ‘Processing Standards and Ingredient Specifications for Livestock Products’. In total, swab samples from 337 pig carcasses (100 samples in 2014, 135 samples in 2015, 102 samples in 2016) and 319 cattle carcasses (100 samples in 2014, 119 samples in 2015, 100 samples in 2016) from twenty slaughterhouses were examined for Listeria monocytogenes, Campylobacter jejuni, Campylobacter coli, Salmonella spp., Staphylococcus aureus, Clostridium perfringens, Yersinia enterocolitica, Escherichia coli O157:H7 and non-O157 enterohemorrhagic E. coli (EHEC, serotypes O26, O45, O103, O104, O111, O121, O128 and O145) as foodborne pathogens. The samples were analyzed using cultural and PCR-based methods. Foodborne pathogens were isolated in 78 (23.1%) out of 337 pig samples. In 2014, S. aureus (n=17) was predominant, followed by Y. enterocolitica (n=7), C. perfringens (n=2) and L. monocytogenes (n=2). In 2015, C. coli (n=14) was the most prevalent, followed by L. monocytogenes (n=4), S. aureus (n=3), and C. perfringens (n=2). In 2016, S. aureus (n=16) was the most prevalent, followed by C. coli (n=13), L. monocytogenes (n=2) and C. perfringens (n=1). In case of cattle carcasses, foodborne bacteria were detected in 41 (12.9%) out of 319 samples. In 2014, S. aureus (n=16) was the most prevalent, followed by Y. enterocolitica (n=3), C. perfringens (n=3) and L. monocytogenes (n=2). In 2015, L. monocytogenes was isolated from 4 samples, S. aureus from three, C. perfringens, Y. enterocolitica and Salmonella spp. from one, respectively. In 2016, L. monocytogenes (n=6) was the most prevalent, followed by C. perfringens (n=3) C. jejuni (n=1), respectively. It was found that 10 carcass samples (4 cattle and 6 pigs) were contaminated with two bacterial pathogen tested. Interestingly, foodborne pathogens were more detected from pig carcasses than cattle carcasses. Although S. aureus was predominantly detected in this study, other foodborne pathogens were also isolated in slaughtered meats. Results of this study alerted the risk of foodborne pathogen infection for humans from slaughtered meats. Therefore, the authors insisted that it was important to enhance hygiene level of slaughterhouses according to Hazard Analysis and Critical Control Point.

Keywords: carcass, cattle, foodborne, Korea, pathogen, pig

Procedia PDF Downloads 339

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarms, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Wabinyai Fidel Raja, Gideon Lubisa

Abstract:

Air pollution is becoming a growing concern in Africa due to rapid industrialization and urbanization, leading to implications for public health and the environment. Establishing a comprehensive air quality monitoring network is crucial to combat this issue. However, conventional methods of monitoring are insufficient in African cities due to the high cost of setup and maintenance. To address this, low-cost sensors (LCS) can be deployed in various urban areas through the use of participatory air quality network siting (PAQNS). PAQNS involves stakeholders from the community, local government, and private sector working together to determine the most appropriate locations for air quality monitoring stations. This approach improves the accuracy and representativeness of air quality monitoring data, engages and empowers community members, and reflects the actual exposure of the population. Implementing PAQNS in African cities can build trust, promote accountability, and increase transparency in the air quality management process. However, challenges to implementing this approach must be addressed. Nonetheless, improving air quality is essential for protecting public health and promoting a sustainable environment. Implementing participatory and data-informed air quality monitoring can take a significant step toward achieving these important goals in African cities and beyond.

Keywords: low-cost sensors, participatory air quality network siting, air pollution, air quality management

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Authors: Sadeq Al Yaari, Muhammad Alkhunayn, Ayah Al Yaari, Ayman Al Yaari, Montaha Al Yaari, Adham Al Yaari, Sajedah Al Yaari, Fatehi Eissa

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Developmental co-ordination disorder (DCD) (also known as dyspraxia) causes a child to speak less well than expected in social conversations. We propose that the smart speaking technology could help improve sound production mechanism at both phonetic and phonological levels, which leads to better articulation of an utterance. The participants are twelve privately beginner pupils aged between 6-12 years old and diagnosed with DCD (apraxia) divided into two groups: Experimental group (n=6) and control group (called apraxic control group) (n=6). A total of fifty typically developing and achieving (TD) pupils participated as control group 2 in both groups and were preassigned into two groups (27 pupils with the treatment group and 23 with the apraxic control group). Weekly quizzes were given to all participants each week for four continuous months and results were analyzed by psychoneurolinguists and a statistician. Although being taught by the same speech-language therapist (SLT), treatment group along with TD groups were taught a full-time speaking course with sociolinguistic themes covering both phonetic and phonological properties. The course lasted for a whole semester whereby smart speaking aids have become dominant while apraxic control group and its TD group were not. Compared with apraxic control group and its TD subgroup, results show obvious changes in speaking behavioral mechanism of the DCD experimental group and its TD subgroup. Improvement could be taken from the scores where the zero marks disappeared in the fourth week (end of the first month of treatment). Good marks (5 +/10) were seen starting from the eighth week and culminating with full marks in the week number 15 of treatment where some participants scored full mark. This study concludes to support the primacy of the smart educational technology for speaking purposes and also shows that such aids can expand the range of academic performance differential categories. Further research is required to evaluate the current demonizing of smart educational aids and weighting more reasonably the relationship specificity that speaking aids can offer to other language skills, as well as their limitations.

Keywords: smart educational technology, speaking aids, pupils with SCD, apraxia

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Authors: Masoumeh Pirhadi

Abstract:

Air pollution is becoming a major health problem affecting millions. In support of this observation, the world health organization estimates that many people feel unhealthy due to pollution. This is a coupled fact that one of the main global sources of air pollution in cities is greenhouse gas emissions due heavy traffic. Green walls are developed as a sustainable strategy to reduce pollution by increasing vegetation in developed areas without occupying space in the city. This concept an offer advantageous environmental benefits and they can also be proposed for aesthetic purposes, and today they are used to preserve the urban environment. Green walls can also create environments that can promote a healthy lifestyle. Findings of multiple studies also indicate that Green infrastructure in cities is a strategy for improving air quality and increasing the sustainability of cities. Since these green solutions (green walls) act as porous materials that affect the diffusion of air pollution they can also act as a removing air vents that clean the air. Therefore, implementation of this strategy can be considered as a prominent factor in achieving a cleaner environment.

Keywords: green vegetation, air pollution, green wall, urban area

Procedia PDF Downloads 148

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: S. Murr, S. Phillips

Abstract:

One of the biggest challenges entering a market with a carsharing or any other shared mobility (SM) service is sound investment decision-making. To support this process, the authors think that a city index evaluating different criteria is necessary. The goal of such an index is to benchmark cities along a set of external measures to answer the main two challenges: financially viability and the understanding of its specific requirements. The authors have consulted several shared mobility projects and industry experts to create such a Shared Mobility City Index (SMCI). The current proposal of the SMCI consists of 11 individual index measures: general data (demographics, geography, climate and city culture), shared mobility landscape (current SM providers, public transit options, commuting patterns and driving culture) and political vision and goals (vision of the Mayor, sustainability plan, bylaws/tenders supporting SM). To evaluate the suitability of the index, 16 cities on the East Coast of North America were selected and secondary research was conducted. The main sources of this study were census data, organisational records, independent press releases and informational websites. Only non-academic sources where used because the relevant data for the chosen cities is not published in academia. Applying the index measures to the selected cities resulted in three major findings. Firstly, density (city area divided by number of inhabitants) is not an indicator for the number of SM services offered: the city with the lowest density has five bike and carsharing options. Secondly, there is a direct correlation between commuting patterns and how many shared mobility services are offered. New York, Toronto and Washington DC have the highest public transit ridership and the most shared mobility providers. Lastly, except one, all surveyed cities support shared mobility with their sustainability plan. The current version of the shared mobility index is proving a practical tool to evaluate cities, and to understand functional, political, social and environmental considerations. More cities will have to be evaluated to refine the criteria further. However, the current version of the index can be used to assess cities on their suitability for shared mobility services and will assist investors deciding which city is a financially viable market.

Keywords: carsharing, transportation, urban planning, shared mobility city index

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Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 63

Authors: Rachida Benabbou, Sang Hun Park, Hee Chung Lee

Abstract:

The world’s population is increasing with unprecedented speed, leading to fast growing urbanization pace. Cities since the Industrial revolution had evolved to fit the growing demand on infrastructure, roads, transportation, and housing. Through this evolution, cities had grown into grey, polluted, and vehicle-oriented urban areas with a significant lack of green spaces. Consequently, we ended up with low quality of life for citizens. Therefore, many cities, nowadays, are revising the way we think urbanism and try to grow into more livable and citizen-friendly, by creating change from the inside out. Thus, cities are trying to bring back nature in its crowded grey centers and regenerate many urban areas as green public spaces not only as a way to give new breath to the city, but also as a way to create change either in the environmental, social and economic levels. The city of Seoul is one of the fast growing global cities. Its population is over 12 million and it is expected to continue to grow to a point where the quality of life may seriously deteriorate. As most green areas in Seoul are located in the suburbs in form of mountains, the city’s urban areas suffer from lack of accessible green spaces in a walking distance. Understanding the gravity and consequences of this issue, Seoul city is undergoing major changes. Many of its projects are oriented to be green public spaces where citizens can enjoy the public life in healthy outdoors. The aim of this paper is to explore the results of urban conversions into green public spaces. Starting with different locations, nature, size, and scale, these conversions can lead to significant change in the surrounding areas, thus can be used as an efficient tool of regeneration for urban areas. Through a comparative analysis of three different types of urban conversions projects in the city of Seoul, we try to show the positive urban influence of the outcomes, in order to encourage cities to use green spaces as a strategic tool for urban regeneration and redevelopment.

Keywords: urban conversion, green public space, change, urban regeneration

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Authors: Jens-Phillip Petersen

Abstract:

The reduction of GHG emissions in buildings is a focus area of national energy policies in Europe, because buildings are responsible for a major share of the final energy consumption. It is at local scale where policies to increase the share of renewable energies and energy efficiency measures get implemented. Municipalities, as local authorities and responsible entity for land-use planning, have a direct influence on urban patterns and energy use, which makes them key actors in the transition towards sustainable cities. Hence, synchronizing urban planning with energy planning offers great potential to increase society’s energy-efficiency; this has a high significance to reach GHG-reduction targets. In this paper, the actual linkage of urban planning and energy planning in Denmark and Germany was assessed; substantive barriers preventing their integration and driving factors that lead to successful transitions towards a holistic urban energy planning procedures were identified.

Keywords: energy planning, urban planning, renewable energies, sustainable cities

Procedia PDF Downloads 339

Authors: Fahad Javed, Tasneem Akhter, Maria Zafar, Adnan Shafique

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Evaluation and quantification of techniques is critical element of research and development of technology. Simulations and models play an important role in providing the tools for such assessments. When we look at technologies which impact or is dependent on an average Joe consumer then modeling the socio-economic and psychological aspects of the consumer also gain an importance. For feed in tariff for home consumers which is being deployed for average consumer may force many consumers to be adapters of the technology. Understanding how consumers will adapt this technologies thus hold as much significance as evaluating how the techniques would work in consumer agnostic scenarios. In this paper we first build the case for simulators which accommodate socio-economic realities of the consumers to evaluate smart grid technologies, provide a glossary of data that can aid in this effort and present an abstract model to capture and simulate consumers' adaptation and behavioral response to smart grid technologies. We provide a case study to express the power of such simulators.

Keywords: smart grids, simulation, socio-economic parameters, feed in tariff (FiT), forecasting

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Authors: Mahmood Seyyed, Akram Salehi Heykoei, Hamidreza Safakish Kashani

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Among the remaining resource of the past, coins considered as an authentic documents among the most important documentary sources. The coins were minted in a place that called mint. The number and position of the mints in each period reflects the amount of economic power, political security and business growth, which was always fluctuated its position with changing the political and economic condition. Considering that, trade has more growth during the Safavid period than previous ones, the mint also has been in greater importance. It seems the one hand, the growth of economic in Safavid period has a direct link with the number and places of the mints at that time and in the other hand, the mints have been formed in some places because of the specific characteristic of cities and regions. Increasing the number of mints in the north of the country due to the growth of silk trade and in the west and northwest due to the political and commercial relation with Ottoman Empire, also the characteristics such as existence of mines, located in the Silk Road and communication ways, all are the results of this investigation. Accordingly, in this article researcher tries to examine the characteristics that give priority to a city for having mint. With considering that in the various historical periods, the mints were based in the most important cities in terms of political and social, at that time, this article examines the cities specific characteristics in the formation of the mints in Safavid period.

Keywords: documentary sources, coins, mint, city, Safavid

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Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: A. Karunasena, P. Bandara, J. A. T. P. Jayasuriya, P. D. Gallage, J. M. S. D. Jayasundara, L. A. P. Y. P. Nuwanjaya

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Usage of smart learning concepts has increased rapidly all over the world recently as better teaching and learning methods. Most educational institutes such as universities are experimenting those concepts with their students. Smart learning concepts are especially useful for students to learn better in large classes. In large classes, the lecture method is the most popular method of teaching. In the lecture method, the lecturer presents the content mostly using lecture slides, and the students make their own notes based on the content presented. However, some students may find difficulties with the above method due to various issues such as speed in delivery. The purpose of this research is to assist students in large classes in the following content. The research proposes a solution with four components, namely note-taker, slide matcher, reference finder, and question presenter, which are helpful for the students to obtain a summarized version of the lecture note, easily navigate to the content and find resources, and revise content using questions.

Keywords: automatic summarization, extractive text summarization, speech recognition library, sentence extraction, automatic web search, automatic question generator, sentence scoring, the term weight

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Authors: Masoud Shahmanzari

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The aim of this paper is to present a Variable Neighborhood Search (VNS) with Tabu Search (TS) conditions for the Roaming Salesman Problem (RSP). The RSP is a special case of the well-known traveling salesman problem (TSP) where a set of cities with time-dependent rewards and a set of campaign days are given. Each city can be visited on any day and a subset of cities can be visited multiple times. The goal is to determine an optimal campaign schedule consist of daily open/closed tours that visit some cities and maximizes the total net benefit while respecting daily maximum tour duration constraints and the necessity to return campaign base frequently. This problem arises in several real-life applications and particularly in election logistics where depots are not fixed. We formulate the problem as a mixed integer linear programming (MILP), in which we capture as many real-world aspects of the RSP as possible. We also present a hybrid metaheuristic algorithm based on a VNS with TS conditions. The initial feasible solution is constructed via a new matheuristc approach based on the decomposition of the original problem. Next, this solution is improved in terms of the collected rewards using the proposed local search procedure. We consider a set of 81 cities in Turkey and a campaign of 30 days as our largest instance. Computational results on real-world instances show that the developed algorithm could find near-optimal solutions effectively.

Keywords: optimization, routing, election logistics, heuristics

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Authors: Youping Huang, Yang Liu

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Mountainous cities have unique landscape relationship, topography and urban spatial pattern different from plain cities, which put forward different requirements for greenway system planning strategy. Taking the greenway planning of Chengkou County in Chongqing as an example, this paper discusses the greenway system planning strategy of mountainous cities based on urban and rural green space, urban landscape resources, human resources and other factors. Through multi-angle maintenance of landscape pattern, multi-objective integration of urban resources, multi-level construction of greenway network, and multi-interactive development control, the sustainable development of mountain city landscape resources is realized, the new urban ecology is constructed, and the quality of life of urban and rural residents is improved.

Keywords: greenway planning, mountain city, landscape pattern, cultural resources, chongqing

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Authors: Eugen Neagoe, Victor Balanica

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A Smart Building Controller (SBC) is a server software that offers secured access to a pool of building specific resources, executes monitoring tasks and performs automatic administration of a building, thus optimizing the exploitation cost and maximizing comfort. This paper brings to discussion the issues that arise with the secure exploitation of the SBC administered resources and proposes a technical solution to implement a robust secure access system based on roles, individual rights and privileges (special rights).

Keywords: smart building controller, software security, access rights, access authorization

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Authors: Y. Boulaksil, J. C. Fransoo, E.E. Blanco, S. Koubida

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In this paper, we study the small traditional retailers that are located in the neighborhoods of big cities in emerging markets. Although modern retailing has grown in the last two decades in these markets, the number of small retailers is still increasing and serving a substantial part of the daily demand for many basic products, such as bread, milk, and cooking oil. We conduct an empirical study to understand the business environment of these small traditional retailers in emerging markets by collecting data from 333 small retailers, spread over 8 large cities in Morocco. We analyze the data and describe their business environment with a focus on the informal credits they offer to their customers. We find that smaller small retailers that are funded from personal savings and managed by the owner himself offer relatively the most credits. Our study also provides interesting insights about these small retailers that will help FMCG manufacturers that are (planning to be) active in Morocco and other emerging markets. We also discuss a number opportunities to improve the efficiency of the supply chains that serve them.

Keywords: small retailers, big cities, emerging markets, empirical study, supply chain management, Morocco

Procedia PDF Downloads 569