Search Results (12)

Japan’s 8.5 million vacant homes (Akiyas) represent a paradox of scarcity amid surplus: while rural depopulation leaves properties abandoned, housing shortages and bureaucratic inefficiencies hinder their reuse. This study proposes AKI2ALL, an AI-blockchain framework designed to automate the circular repurposing of Akiyas into ten high-value community assets—guesthouses, co-working spaces, pop-up retail and logistics hubs, urban farming hubs, disaster relief housing, parking lots, elderly daycare centers, exhibition spaces, places for food and beverages, and company offices—through smart contracts and data-driven workflows. By integrating circular economy principles with decentralized technology, AKI2ALL streamlines property transitions, tax validation, and administrative processes, reducing operational costs while preserving embodied carbon in existing structures. Municipalities list properties, owners select uses, and AI optimizes assignments based on real-time demand. This work bridges gaps in digital construction governance, proving that automating trust and accountability can transform systemic inefficiencies into opportunities for community-led, low-carbon regeneration, highlighting its potential as a scalable model for global vacant property reuse. Full article

Knowledge-intensive business services (KIBSs) are key links in leading the sustainable development of cities. Studying the spatial pattern and influencing factors of urban KIBSs can help improve the utilization of KIBS resources. Taking the Wuhan metropolitan area as a case study, based on data from industrial and commercial registration enterprises, this study uses the multi-ring buffer zone analysis and kernel density estimation method to analyze the spatial pattern of KIBS, and uses a negative binomial regression model to detect the influencing factors of the spatial pattern of KIBS. The results show that: (1) KIBSs are mainly distributed in the inner suburbs, presenting a multi-center spatial pattern, exhibiting the law of agglomeration along entrepreneurial streets, headquarter bases, science and technology parks, university clusters, business centers, and industrial bases. Obvious differences exist in the spatial patterns of KIBS sub-sectors. (2) Land price, traffic conditions, office space, commercial environment, technology factors, industry diversity, incubation environment, investment environment, manufacturing foundation, agglomeration factors, and policy factors are the main factors affecting the spatial patterns of KIBSs. There are differences in the impact of influencing factors on KIBS sub-sectors. The results can provide a decision-making basis for the rational layout and planning of urban KIBSs in the post-industrial era. Full article

With limited investment costs, how to fully utilize the carbon-reduction capacity of a campus in terms of buildings, equipment, and energy is an important issue when realizing the low-carbon retrofit of office parks. To this end, this paper establishes a mathematical optimization model for the decarbonization-based retrofit of existing office parks, based on the genetic algorithm, taking into account the relationship between cost, energy-consumption, and carbon-emissions, and taking the maximum carbon reduction of the park over its whole life as the optimization goal. The validity of the model was verified in conjunction with a case study of an office park in Nanchang, China. The case study shows that, compared with current typical parks, the carbon reduction through an office park’s decarbonization retrofit has a non-linear correlation with the investment cost, and when the total investment cost of the park is above CNY 60 million, the increase in carbon reduction with the increase in the investment cost is gradually weakened, and the park achieves the maximum carbon reduction of 236,087 t when the investment cost reaches CNY 103 million. Under the current technical and economic conditions, the investment-cost–carbon-reduction benefits of different carbon-reduction technologies are different, the carbon-reduction benefit of increasing renewable energy utilization is the best, and the carbon-reduction benefit of upgrading the energy efficiency of the park’s supply-and-use system is lower than that of renewable energy utilization, but better than that of upgrading the performance of the building envelope system. In addition, the configuration of the parameters of the same low-carbon technology in different forms of buildings varies significantly, due to differences in the building form and daily use. The model established in this paper is able to give a comprehensive optimized building–equipment–energy configuration plan for existing office parks, when maximizing carbon reduction under different investment costs, which guides the park’s decarbonization retrofit. Full article

Human–wildlife conflict is a challenging issue that requires the attention of conservationists worldwide. Habitat fragmentation and encroachment reduce the abundance of prey species, and an increase in the number of predators leads to a higher risk of conflict with large cats such as leopards, jeopardizing conservation efforts. This study explored the spatio-temporal pattern of the human–leopard conflict in Bardia National Park, Nepal, from 2000 to 2020. To analyze the conflict with leopards, we used data (compensation cases filed in the park) from the buffer zone management office, the National Trust for Nature Conservation (NTNC), and the Department of National Park and Wildlife Conservation (DNPWC). Leopard attacks on livestock are increasing exponentially, with 3335 livestock killed in 2652 attacks occurring during the study period. Although livestock depredation by leopards occurred all over the park, the southern cluster has most documented livestock damage (64.01%). The eastern and northern clusters reported fluctuating and dispersed predation events, respectively. Our spatial analysis indicated no effect of topography (slope) on livestock depredation by leopards. We recorded the highest number of leopard attacks and predation during the dry winter season when the nights are longer and livestock remain in their sheds. This carnivore mostly limited its prey to small-sized livestock (95.77%) such as goats, sheep, and pigs, whereas attacks on large-sized (cow and buffalo) livestock were least frequent. Among small-sized livestock, goats are the most predated (66.92%), followed by pigs (20.30%), in all seasons. The escalating human–leopard conflict in BNP is thus a severe threat to conservation efforts as the park has already invested a substantial amount of money (approx. USD 80,000) compensating for livestock lost in leopard attacks over the last two decades. Improving habitat conditions to reduce competition inside the park, developing an insurance scheme for livestock and humans, providing support for upgraded sheds, and the development of practical and feasible strategies that focus on specific animals and clusters of the national park are needed to reduce conflicts to maintain the co-existence between wildlife and human beings. Full article

With the popularity of new energy vehicles, a large number of cities began to focus on the installation of electric vehicle charging piles. However, the existing intelligent charging piles have faced problems such as short supply, unreasonable distribution areas, and insufficient power supply. In response to these problems, this research proposes a recurrent neural network algorithm with an integrated firefly algorithm. Based on these two algorithms, a charging pile location and capacity model was established, and users’ travel habits were analyzed according to the model. In the simulation experiment, the PR curve analysis of the algorithm was carried out first. The analysis results showed that the AP value of the recurrent neural network algorithm combined with the firefly algorithm was increased from 0.9324 to 0.9972. In addition, it had higher accuracy and stability than before, which also verified the feasibility of the algorithm. Finally, through the model, the user’s travel habits were analyzed in detail. From the perspective of total demand, the charging demand of commercial centers was the highest, with a peak of about 537 kw, followed by 501 kw in office areas and then about 379 kw in parks. The kw charging demand in other areas was below 200 kw. The above results show that the recursive neural network can effectively determine the location and capacity of the charging pile, which is of great value to the development of transportation and new energy. Full article

This descriptive study reveals trends in citations and traffic-related mortality in Kuwait. Secondary data were utilized, where data on road traffic citations were obtained from the traffic police in the Ministry of Interior for the years from 2011 to 2015, and road traffic mortality data for the study period were obtained from the Ministry of Health. Objective: To describe recent trends in data related to road traffic safety in Kuwait over time, which could serve as an important indicator for the level of enforcement of existing traffic regulations. Descriptive summary statistics are presented. Results: There was a total of 24.2 million traffic violations during the study period. The number rose dramatically from 4 million citations in 2011 to nearly 6.5 million in 2015. The indirect method of citation (issued indirectly via surveillance methods) constituted a higher percentage of citations, 70.4%, compared to the direct method of citation (issued directly by the police officer), 29.6%. Furthermore, the top reason for citation was speeding, followed by parking in no parking/handicapped zones, driving with an expired license, and crossing a red light. Road traffic fatalities (RTFs) in Kuwait from 2011 to 2015 totaled 2282. About 450 people die each year in Kuwait from road traffic injuries and a slightly decreasing trend was found. Non-Kuwaitis have RTF counts that are four times higher than Kuwaitis, with 1663 and 263 deaths, respectively. Conclusions: Road traffic safety continues to be a major problem in Kuwait. Increases in citation issuance show a rise in traffic regulation enforcement, yet risky driving behaviors continue to account for most violations issued. Harsher penalties, road safety education, and implementing graduated driving licensing may be warranted to increase the safety of the roads. Full article

The purpose of the study was to investigate the impact of attracting a mega-sport facility on the development of a small town. As a case study, we took a close look at the changes occurring since Muju County attracted Taekwondowon in 2014 and its significance to urban development and city branding. Data were collected by individual interviews with five research participants engaged in the business and the regional development of Taekwondowon and the Muju County Office (MCO). As a result, the study produced the following outcomes: First, MCO has established an administrative and legal system to actively utilize Taekwondowon and spur urban development. Second, the regional ripple effects include the local economic consumption by the Taekwondo Promotion Foundation (TPF), purchasing local agricultural products by the TPF, and increasing income for local lodging and catering businesses generated by taekwondo events held at Taekwondowon. Third, and most importantly, Muju has been pursuing a transformation into a sustainable international tourism city by becoming the mecca for taekwondo. To achieve this goal, Taekwondowon has been taking some existing functions of Kukkiwon, and the MCO constructed the Taekwon Village, Taekwon Park, and Taekwon V Land throughout Muju. In addition, the social overhead capital necessary for a tourist destination, such as road expansion and a new express bus system between the international airport and Muju, has been reinforced. Furthermore, various tourism products using Taekwondowon have been provided to continue its city branding. In summary, it was found that Taekwondowon has played a pivotal role in Muju’s journey toward achieving sustainable development as the mecca for taekwondo. Full article

Despite increased renovation work for office buildings to improve energy performance, studies on the appraisal of renovated office buildings (ROB) are scarce. Thus, this study analyzed the perceptions of appraisers regarding renovation work and the effect of renovation work on the economic value of office buildings. Following a reliability evaluation, research results were derived using various methodologies, such as descriptive statistics, Chi-square analysis, analytic hierarchical process, and structural equation modeling, based on the survey results of 118 appraisers. The renovation work was found to positively increase an office building’s value, although the existing appraisal methods have low applicability considering the appraisal of ROB. On evaluating the importance of each factor considered in the ROB appraisal process, the factors related to the “location” of ROB were deemed more important than the attributes directly changed as a result of renovation work. Moreover, factors whose attributes were changed (e.g., working environment, green space, lease area, gross area of floors, number of floors, and number of parking spaces) were found to be critical factors affecting ROB value. The results of this study are expected to provide improvement directions for ROB appraisal methods and significantly aid building owners. Full article

As small obsolete buildings are exposed to high fire risks, governments are trying to evaluate their fire risks and preferentially improve fire protection performance for high risk buildings, however, the evaluation manpower and time are insufficient compared to the rapidly increasing number of obsolete buildings. Therefore, this study aimed to derive major fire risk index (FRI) evaluation items as part of developing a platform to quickly and efficiently evaluate fire risks in dense areas of small obsolete buildings utilizing spatial information convergence technology. To this end, 20 preliminary evaluation items specifically tailored to dense areas of small obsolete buildings were derived through a field survey, investigation of FRI evaluation items from existing works, and expert pre-reviews. Based on the derived 20 preliminary items, an importance survey was conducted with a total of 181 fire safety experts including fire officers, university professors, researchers, industry experts, and fire insurers. As a result, a total of 12 major evaluation items (e.g., outdoor fire extinguisher, distance to 119 Safety Center, building structure, building cladding, illegal alterations, illegal parking, and liquefied natural gas cylinder) were derived. Results can help to evaluate the fast and efficient fire risks in dense areas of small obsolete buildings. Full article

Mixed-use development is theoretically considered to enhance the residential value of an area. However, limited empirical research has focused on European and North American cities. HOPSCA is a real estate project that integrates hotels, offices, parks, shopping malls, conference centers, and apartments. As an important mixed-use development project in Chinese cities, HOPSCA is designed to improve the quality of urban life and to enhance the residential value of an area. Few studies have explicitly examined the effect of HOPSCA on residential property values, let alone linked this question to particular types of HOPSCA. To bridge this research gap, we selected Wuhan City in China as a case study to explore the effects of HOPSCA on residential property values. Specifically, we used the potential model to quantify the effects of HOPSCA and used the geographically weighted regression (GWR) method to estimate the relationship between HOPSCA variables and residential property values. The results are as follows: (1) the effects of HOPSCA on residential property values are statistically significant with positive and negative effects. The balanced-development HOPSCA generated the greatest effects, with the highest premium of 10.76% placed on residential properties. Moderate price premiums of 3.57% and 1.83% were generated under the influence of the commerce-oriented HOPSCA and housing-oriented HOPSCA, respectively. By contrast, the business-oriented HOPSCA exerted a negative effect on residential property (−2.43%). (2) Significant spatial heterogeneity exists on the effect of HOPSCA on residential property values. The results showed that the influence of different types of HOPSCA, viz. the higher the compatibility between the HOPSCA type and the socioeconomic context of Wuhan, the higher the premium captured by residential properties within the city areas. HOPSCA benefits the improvement of the quality of urban life, which promotes urban development. For policy makers and real estate developers, our findings suggest that matching the development types and the spatial layouts of HOPSCA with the regional socioeconomic contexts is critical for enhancing the value performance of such projects. Full article

Accurate indoor positioning technology provides location-based service for a variety of applications. However, most existing indoor localization approaches (e.g., Wi-Fi and Bluetooth-based methods) rely heavily on positioning infrastructure, which prevents their large-scale deployment and limits the range at which they are applicable. Here, we proposed an infrastructure-free indoor positioning and tracking approach, termed LiMag, which used ubiquitous magnetic field and ambient lights (e.g., fluorescent, incandescent, and light-emitting diodes (LEDs)) without containing modulated information. We conducted an in-depth study on both the advantages and the challenges in leveraging magnetic field and ambient light intensity for indoor localization. Based on the insights from this study, we established a hybrid observation model that took full advantage of both the magnetic field and ambient light signals. To address the low discernibility of the hybrid observation model, LiMag first generated a single-step fingerprint model by vectorizing consecutive hybrid observations within each step. In order to accurately track users, a lightweight single-step tracking algorithm based on the single-step fingerprints and the particle filter framework was designed. LiMag leveraged the walking information of users and several single-step fingerprints to generate long trajectory fingerprints that exhibited much higher location differentiation ability than the single-step fingerprint. To accelerate particle convergence and eliminate the accumulative error of single-step tracking algorithm, a long trajectory calibration scheme based on long trajectory fingerprints was also introduced. An undirected weighted graph model was constructed to decrease the computational overhead resulting from this long trajectory matching. In addition to typical indoor scenarios including offices, shopping malls and parking lots, we also conducted experiments in more challenging scenarios, including large open-plan areas as well as environments characterized by strong sunlight. Our proposed algorithm achieved a 75th percentile localization accuracy of 1.8 m and 2.2 m, respectively, in the office and shopping mall tested. In conclusion, our LiMag algorithm provided location-based service of infrastructure-free with significantly improved localization accuracy and coverage, as well as satisfactory robustness inside complex indoor environments. Full article

Nowadays, in big cities, parking management is a critical issue from both the driver’s side and the city government’s side. From the driver’s side, how to find an available parking lot in a city is a considerable concern. As a result, smart parking systems recently have received great interest, both in academia and industry. From the city government’s side, how to manage and distribute such a limited public parking resource efficiently to give every visitor a fair chance of finding an on-street parking lot is also a considerable concern. However, existing studies of smart parking management focus only on assisting the driver’s side to find available parking spaces. This study aims to raise a new perspective on such smart parking management and to propose a novel location-centric IoT-cloud-based parking violation management system. The system is designed to assist authoritative officers in finding parking violations easily and recommends the least cost path for officers so that officers can achieve their highest productivity in finding parking violations and issuing parking tickets. Experimental results show that the system not only improves the productivity of officers in finding parking violations and issuing tickets, but also helps reduce the traveling cost of officers and to reduce the average violation period of violating cars considerably. Full article