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Smart Cities, Volume 7, Issue 3 (June 2024) – 9 articles

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20 pages, 3393 KiB  
Article
Redesigning Municipal Waste Collection for Aging and Shrinking Communities
by Andante Hadi Pandyaswargo, Chaoxia Shan, Akihisa Ogawa, Ryota Tsubouchi and Hiroshi Onoda
Smart Cities 2024, 7(3), 1149-1168; https://doi.org/10.3390/smartcities7030049 - 16 May 2024
Viewed by 225
Abstract
Due to aging and depopulation, cities in Japan struggle to maintain their municipal waste collection services. These challenges were exacerbated by the pandemic. To overcome these challenges, a prototype of collective and contactless waste collection technology has been developed. However, its acceptance by [...] Read more.
Due to aging and depopulation, cities in Japan struggle to maintain their municipal waste collection services. These challenges were exacerbated by the pandemic. To overcome these challenges, a prototype of collective and contactless waste collection technology has been developed. However, its acceptance by society is unknown. In this study, we surveyed Japanese people’s preferences regarding household waste disposal. The results showed that older adults (older than 60) are willing to walk longer (more than 2 min) to carry their waste to the disposal site than younger adults. They are also less concerned about the risk of disease infection from touching other people’s garbage than younger respondents (at a 0.24 count ratio). Other significant findings are that people who live alone prefer the temporary disposal site to be placed more than one minute away from their house (at a 0.19 count ratio). People living alone also produce less plastic and packaging waste than larger households. With more Japanese older adults living alone because of the scarcity of older-adult care facilities, we proposed two waste collection strategies that can allow for the implementation of more collective and automatized contactless waste pickup technology. Each design poses different challenges, such as the need for residents’ cooperation and a higher energy supply. However, they also open new opportunities, such as encouraging active aging and using renewable energy. Full article
(This article belongs to the Special Issue Inclusive Smart Cities)
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23 pages, 1261 KiB  
Article
Enabling Alarm-Based Fault Prediction for Smart Meters in District Heating Systems: A Danish Case Study
by Henrik Alexander Nissen Søndergaard, Hamid Reza Shaker and Bo Nørregaard Jørgensen
Smart Cities 2024, 7(3), 1126-1148; https://doi.org/10.3390/smartcities7030048 - 14 May 2024
Viewed by 252
Abstract
District heating companies utilize smart meters that generate alarms that indicate faults in their sensors and installations. If these alarms are not tended to, the data cannot be trusted, and the applications that utilize them will not perform properly. Currently, smart meter data [...] Read more.
District heating companies utilize smart meters that generate alarms that indicate faults in their sensors and installations. If these alarms are not tended to, the data cannot be trusted, and the applications that utilize them will not perform properly. Currently, smart meter data are mostly used for billing, and the district heating company is obligated to ensure the data quality. Here, retrospective correction of data is possible using the alarms; however, identification of sensor problems earlier can help improve the data quality. This paper is undertaken in collaboration with a district heating company in which not all of these alarms are tended to. This is due to various barriers and misconceptions. A shift in perspective must happen, both to utilize the current alarms more efficiently and to permit the incorporation of predictive capabilities of alarms to enable smart solutions in the future and improve data quality now. This paper proposes a prediction framework for one of the alarms in the customer installation. The framework can predict sensor faults to a high degree with a precision of 88% and a true positive rate of 79% over a prediction horizon of 24 h. The framework uses a modified definition of an alarm and was tested using a selection of machine learning methods with the optimization of hyperparameters and an investigation into prediction horizons. To the best of our knowledge, this is the first instance of such a methodology. Full article
(This article belongs to the Section Smart Grids)
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17 pages, 1170 KiB  
Article
Smart Delivery Assignment through Machine Learning and the Hungarian Algorithm
by Juan Pablo Vásconez, Elias Schotborgh, Ingrid Nicole Vásconez, Viviana Moya, Andrea Pilco, Oswaldo Menéndez, Robert Guamán-Rivera and Leonardo Guevara
Smart Cities 2024, 7(3), 1109-1125; https://doi.org/10.3390/smartcities7030047 - 12 May 2024
Viewed by 370
Abstract
Intelligent transportation and advanced mobility techniques focus on helping operators to efficiently manage navigation tasks in smart cities, enhancing cost efficiency, increasing security, and reducing costs. Although this field has seen significant advances in developing large-scale monitoring of smart cities, several challenges persist [...] Read more.
Intelligent transportation and advanced mobility techniques focus on helping operators to efficiently manage navigation tasks in smart cities, enhancing cost efficiency, increasing security, and reducing costs. Although this field has seen significant advances in developing large-scale monitoring of smart cities, several challenges persist concerning the practical assignment of delivery personnel to customer orders. To address this issue, we propose an architecture to optimize the task assignment problem for delivery personnel. We propose the use of different cost functions obtained with deterministic and machine learning techniques. In particular, we compared the performance of linear and polynomial regression methods to construct different cost functions represented by matrices with orders and delivery people information. Then, we applied the Hungarian optimization algorithm to solve the assignment problem, which optimally assigns delivery personnel and orders. The results demonstrate that when used to estimate distance information, linear regression can reduce estimation errors by up to 568.52 km (1.51%) for our dataset compared to other methods. In contrast, polynomial regression proves effective in constructing a superior cost function based on time information, reducing estimation errors by up to 17,143.41 min (11.59%) compared to alternative methods. The proposed approach aims to enhance delivery personnel allocation within the delivery sector, thereby optimizing the efficiency of this process. Full article
(This article belongs to the Section Smart Transportation)
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20 pages, 12511 KiB  
Article
Integration of Smart City Technologies with Advanced Predictive Analytics for Geotechnical Investigations
by Yuxin Cong and Shinya Inazumi
Smart Cities 2024, 7(3), 1089-1108; https://doi.org/10.3390/smartcities7030046 - 6 May 2024
Viewed by 475
Abstract
This paper addresses challenges and solutions in urban development and infrastructure resilience, particularly in the context of Japan’s rapidly urbanizing landscape. It explores the integration of smart city concepts to combat land subsidence and liquefaction, phenomena highlighted by the 2011 Great East Japan [...] Read more.
This paper addresses challenges and solutions in urban development and infrastructure resilience, particularly in the context of Japan’s rapidly urbanizing landscape. It explores the integration of smart city concepts to combat land subsidence and liquefaction, phenomena highlighted by the 2011 Great East Japan Earthquake. Additionally, it examines the current situation and lack of geoinformation and communication technology in the concept of smart cities in Japan. Consequently, this study employs advanced technologies, including smart sensing and predictive analytics through kriging and ensemble learning, with the objective of enhancing the precision of geotechnical investigations and urban planning. By analyzing data in Setagaya, Tokyo, it develops predictive models to accurately determine the depth of bearing layers that are critical to urban infrastructure. The results demonstrate the superiority of ensemble learning in predicting the depth of bearing layers. Two methods have been developed to predict undetected geographic data and prepare ground reality and digital smart maps for the construction industry to build smart cities. This study is useful for real-time analysis of existing data, for the government to make new urban plans, for construction companies to conduct risk assessments before doing their jobs, and for individuals to obtain real-time geographic data and hazard warnings through mobile phones and other means in the future. To the best of our knowledge, this is the first instance of predictive analysis of geographic information being conducted through geographic information, big data technology, machine learning, integrated learning, and artificial intelligence. Full article
(This article belongs to the Section Smart Urban Infrastructures)
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29 pages, 3585 KiB  
Article
Combined Optimisation of Traffic Light Control Parameters and Autonomous Vehicle Routes
by Mariano Gallo
Smart Cities 2024, 7(3), 1060-1088; https://doi.org/10.3390/smartcities7030045 - 3 May 2024
Viewed by 476
Abstract
In the near future, fully autonomous vehicles may revolutionise mobility and contribute to the development of the smart city concept. In this work, we assume that vehicles are not only fully autonomous but also centrally controlled by a single operator, who can also [...] Read more.
In the near future, fully autonomous vehicles may revolutionise mobility and contribute to the development of the smart city concept. In this work, we assume that vehicles are not only fully autonomous but also centrally controlled by a single operator, who can also define the traffic light control parameters at intersections. With the aim of optimising the system to achieve a global optimum, the operator can define both the routes of the fleet of vehicles and the traffic light control parameters. This paper proposes a model for the joint optimisation of traffic light control parameters and autonomous vehicle routes to achieve the system optimum. The model, which is solved using a gradient algorithm, is tested on networks of different sizes. The results obtained show the validity of the proposed approach and the advantages of centralised management of vehicles and intersection control parameters. Full article
(This article belongs to the Section Smart Transportation)
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16 pages, 497 KiB  
Article
Smart Cities for All? Bridging Digital Divides for Socially Sustainable and Inclusive Cities
by Johan Colding, Caroline Nilsson and Stefan Sjöberg
Smart Cities 2024, 7(3), 1044-1059; https://doi.org/10.3390/smartcities7030044 - 3 May 2024
Viewed by 576
Abstract
This paper aims to emphasize the need for enhancing inclusivity and accessibility within smart-city societies. It represents the first attempt to apply Amartya Sen’s capability approach by exploring the implications of digital divides for promoting inclusive and climate-friendly cities that prioritize well-being, equity, [...] Read more.
This paper aims to emphasize the need for enhancing inclusivity and accessibility within smart-city societies. It represents the first attempt to apply Amartya Sen’s capability approach by exploring the implications of digital divides for promoting inclusive and climate-friendly cities that prioritize well-being, equity, and societal participation. Sen’s framework recognizes individual variations in converting resources into valuable ‘functionings’, and herein emphasizes the importance of aligning personal, social, and environmental conversion factors for individuals to fully navigate, participate in, and enjoy the benefits provided by smart cities. Adopting the capability approach and employing a cross-disciplinary analysis of the scientific literature, the primary objective is to broaden understanding of how to improve inclusivity and accessibility within smart-city societies, with a specific focus on marginalized community members facing first- and second-level digital divides. This paper underscores the importance of adopting a systemic perspective on climate-smart city navigation and stresses the importance of establishing a unified governing body responsible for monitoring, evaluating, and enhancing smart-city functionality. The paper concludes by summarizing some policy recommendations to boost social inclusion and address climate change in smart cities, such as creating capability-enhancing institutions, safeguarding redundancy in public-choice options, empowering citizens, and leveraging academic knowledge in smart-city policy formulation. Full article
(This article belongs to the Special Issue Inclusive Smart Cities)
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37 pages, 4794 KiB  
Review
Off-Grid Electrification Using Renewable Energy in the Philippines: A Comprehensive Review
by Arizeo C. Salac, Jairus Dameanne C. Somera, Michael T. Castro, Maricor F. Divinagracia-Luzadas, Louis Angelo M. Danao and Joey D. Ocon
Smart Cities 2024, 7(3), 1007-1043; https://doi.org/10.3390/smartcities7030043 - 26 Apr 2024
Viewed by 1005
Abstract
Universal access to electricity is beneficial for the socio-economic development of a country and the development of smart communities. Unfortunately, the electrification of remote off-grid areas, especially in developing countries, is rather slow due to geographic and economic barriers. In the Philippines, specifically, [...] Read more.
Universal access to electricity is beneficial for the socio-economic development of a country and the development of smart communities. Unfortunately, the electrification of remote off-grid areas, especially in developing countries, is rather slow due to geographic and economic barriers. In the Philippines, specifically, many electrified off-grid areas are underserved, with access to electricity being limited to only a few hours a day. This is mainly due to the high dependence on diesel power plants (DPPs) for electrifying these areas. To address these problems, hybrid renewable energy systems (HRESs) have been considered good electrification alternatives and have been extensively studied for their techno-economic and financial feasibility for Philippine off-grid islands. In this work, articles published from 2012 to 2023 focusing on off-grid Philippine rural electrification were reviewed and classified based on their topic. The taxonomical analysis of collected studies shows that there is a saturation of works focusing on the technical and economic aspects of off-grid electrification. Meanwhile, studies focusing on environmental and socio-political factors affecting HRES off-grid electrification are lagging. A bibliographic analysis of the reviewed articles also showed that there is still a lack of a holistic approach in studying off-grid electrification in the Philippines. There are only a few works that extend beyond the typical techno-economic study. Research works focusing on environmental and socio-political factors are also mainly isolated and do not cross over with technical papers. The gap between topic clusters should be addressed in future works on off-grid electrification. Full article
(This article belongs to the Section Smart Grids)
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16 pages, 5338 KiB  
Article
3D Point Cloud and GIS Approach to Assess Street Physical Attributes
by Patricio R. Orozco Carpio, María José Viñals and María Concepción López-González
Smart Cities 2024, 7(3), 991-1006; https://doi.org/10.3390/smartcities7030042 - 25 Apr 2024
Viewed by 342
Abstract
The present research explores an innovative approach to objectively assessing urban streets attributes using 3D point clouds and Geographic Information Systems (GIS). Urban streets are vital components of cities, playing a significant role in the lives of their residents. Usually, the evaluation of [...] Read more.
The present research explores an innovative approach to objectively assessing urban streets attributes using 3D point clouds and Geographic Information Systems (GIS). Urban streets are vital components of cities, playing a significant role in the lives of their residents. Usually, the evaluation of some of their physical attributes has been subjective, but this study leverages 3D point clouds and digital terrain models (DTM) to provide a more objective perspective. This article undertakes a micro-urban analysis of basic physical characteristics (slope, width, and human scale) of a representative street in the historic centre of Valencia (Spain), utilizing 3D laser-scanned point clouds and GIS tools. Applying the proposed methodology, thematic maps were generated, facilitating the objective identification of areas with physical attributes more conducive to suitable pedestrian dynamics. This approach provides a comprehensive understanding of urban street attributes, emphasizing the importance of addressing their assessment through advanced digital technologies. Moreover, this versatile methodology has diverse applications, contributing to social sustainability by enhancing the quality of urban streets and open spaces. Full article
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18 pages, 8995 KiB  
Article
Evaluating the Feasibility of Intelligent Blind Road Junction V2I Deployments
by Joseph Clancy, Dara Molloy, Sean Hassett, James Leahy, Enda Ward, Patrick Denny, Edward Jones, Martin Glavin and Brian Deegan
Smart Cities 2024, 7(3), 973-990; https://doi.org/10.3390/smartcities7030041 - 24 Apr 2024
Viewed by 371
Abstract
Cellular Vehicle-to-Everything (C-V2X) communications is a technology that enables intelligent vehicles to exchange information and thus coordinate with other vehicles, road users, and infrastructure. However, despite advancements in cellular technology for V2X applications, significant challenges remain regarding the ability of the system to [...] Read more.
Cellular Vehicle-to-Everything (C-V2X) communications is a technology that enables intelligent vehicles to exchange information and thus coordinate with other vehicles, road users, and infrastructure. However, despite advancements in cellular technology for V2X applications, significant challenges remain regarding the ability of the system to meet stringent Quality-of-Service (QoS) requirements when deployed at scale. Thus, smaller-scale V2X use case deployments may embody a necessary stepping stone to address these challenges. This work assesses network architectures for an Intelligent Perception System (IPS) blind road junction or blind corner scenarios. Measurements were collected using a private 5G NR network with Sub-6GHz and mmWave connectivity, evaluating the feasibility and trade-offs of IPS network configurations. The results demonstrate the feasibility of the IPS as a V2X application, with implementation considerations based on deployment and maintenance costs. If computation resources are co-located with the sensors, sufficient performance is achieved. However, if the computational burden is instead placed upon the intelligent vehicle, it is questionable as to whether an IPS is achievable or not. Much depends on image quality, latency, and system performance requirements. Full article
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