City Management Research Articles

Flooding Resiliency of Surigao del Sur, Caraga Region, Philippines Residences Through Rainwater Catchment and Storage System

Urbanised areas in Northeastern Mindanao have a problem of addressing flooding occurrences. This study primarily aimed to provide insights into how the rainwater catchment system of uptown communities and their cooperation could increase flood resiliency of downtown communities in the Surigao del Sur, Caraga Region, Philippines. This research employed quantitative analysis of the eleven (11) year (2010-2020) data from the Philippine Atmospheric, Geophysical, and Astronomical Services Administration - Hinatuan, Surigao del Sur station. The recommendable optimum rainwater storage capacities for a given number of household occupants, roof areas at run-off efficiency of 90%, and three (3) day rainfall characteristics at 36.9% averaged probability of exceedance were initially determined. Through scenario analysis, uptown communities emptying their rainwater storages before heavy downpour occurs could provide sufficient flood volume reduction and buffer time for downtown communities to prepare. The output of this research is vital in the environmental planning, management, and policies of cities and regions.

Interaction between formal and informal actors in the shadow of policymaking: Case studies of community-based urban pluvial flood risk management in Pearl River Delta cities

Policymakers increasingly integrate urban pluvial flood risk management into multiple strategies, acknowledging that local contexts and the actors involved are crucial. However, the literature on the decision-making processes of community-based pluvial flood risk management sheds little light on how local formal and informal actors relate to each other. This paper contributes to filling this research gap by exploring the interdependency between local authorities and community residents from a multilevel governance perspective. Two cases, based in Pearl River Delta Cities, are analysed to explore actors' interactions locally in the Chinese Sponge City Program, a national programme for urban pluvial flood risk management. The comparative study of the two cases leads to four conclusions. First, the Sponge City Program at the local level can be viewed as multilevel governance. Second, triggered by the goal set by the national government and the local contexts, local authorities see the benefit of locally integrating the Sponge City Program into an integrated and area-specific plan, emphasizing the importance of institutional assertiveness. Third, tensions and synergies exist in the interaction process between local authorities and residents that will have to be recognized and embraced and, where necessary, converted from constraining to enabling factors. Fourth, institutional barriers still dominate locally in the Sponge City Program because of a lack of support for cross-boundary cooperation and public participation. To span these boundaries, policymakers should be more open to changing the perspective from ‘planning for people’ to ‘planning with people’.

WATER SECURITY THROUGH CORPORATE SOCIAL RESPONSIBILITY: A CASE STUDY OF RO WATER PLANTS BY TATA POWER DDL

Water security is one of the most pressing issues in urban India especially for the poor. The purpose of this research is to examine the CSR approach to water security focusing on Tata Power DDL’s RO Water Plants in North and North-West Delhi. In this research, I follow the ethnographic method to analyze the effects of Tata Power DDL’s CSR program on JJ colonies’ access to clean drinking water for the targeted beneficiaries. Questionnaires, interviews, and observation were used to measure the social, economic and environmental impacts of the initiative. According to the result, there were changes in health, hygiene, and satisfactions of the community because of safe drinking water source. However, the following was noted as comprising the challenges that CfPTs face: technological barriers; and difficulty in engaging with the community. The study also underlines the significance of public private partnership in water security and provides an insight into how such other CSR programs could be expanded. The study offers important information about the role of CSR in supporting sustainable development and water management in large cities.

PSYCHOLOGICAL SKILL ASSISTANCE FOR MARRIED COUPLES WHO ARE ALUMNI OF PRE-MARITAL COURSES AT BP4 - PARIAMAN CITY

This paper aims to see how far BP4 Pariaman City has a role in strengthening human psycho-social in the field of social welfare; services for alumni of post-marriage couples need to be followed up with a balanced program. The lack of psycho-social understanding of pre-marital post-marriage course graduates will have great potential to add to the long line of early marriage ages in Pariaman City. The fundamental problem that is most troubling is their ignorance of the responsibilities, rights and obligations of husband and wife in the household. To overcome this solution, the service team identified the problem of spaciousness. It mapped the problem to be treated (treatment) for the subject of service through two stages: family psychology guidance and Islamic family counseling. The first stage is pre-activity in the form of a Focus Discussion Group (FGD) presenting lecturers as participants to provide input for the mentoring action plan to be carried out. The second stage is action activities, including psychological skill assistance in family psychology and group counseling. This activity has generally received appreciation from stakeholders (BP4 Pariaman City management, pre-marital course alumni) because this program has offered various alternatives for their self-development in elaborating their knowledge to be applied in household life. The results of the reflection and evaluation of the program offered by the service conclude that they understand that a sakinah mawaddah wa rahmah household life is not achieved by material wealth but by the ability to accept oneself and have a correct understanding of an Islamic household. They understand that household problems cannot be measured only by logic. However, it includes religious and spiritual matters the human mind cannot reach. Therefore, they understand that household responsibilities are worldly matters and matters of the afterlife, which are related to God.

The indicators included in ISO 37120 and performance measurement in smart cities

Purpose: Local government units are undergoing a shift in management practices driven by the implementation of the New Public Management (NPM) doctrine. One element of NPM is the measurement of performance in local government. As cities grow, the new concept of ‘smart cities’ is rapidly developing. However, it is difficult to determine how to measure the level of ‘smartness’. This paper focuses on measuring the performance of smart cities using the indicators included in ISO 37120. Methodology/approach: In the theoretical part, we overview the aims of performance measurement within NPM and the idea of smart cities. Meanwhile, the empirical part includes statistical data to analyse performance measurement using the indicators included in ISO 37120. Findings: Performance measurement is possible using the indicators included in ISO 37120. The indicators make it possible to compare the results of cities in various countries. Thus, standardising the indicators is the key to the development of smart city performance measurement. Originality/value: Our findings will be of value for future research about using ISO standards for the performance management of smart cities. Our research is also important for implementing NPM in local government. Research limitations: Due to a lack of data, the observation period is too short to make a more in-depth analysis.

A novel framework for waste management in smart city transformation with industry 4.0 technologies

Most of the developed and developing nations focus on the transformation of city livelihood through the development of smart cities. Waste management in smart cities is a critical concern for policymakers and smart city administration. The fourth industrial transformation (hereafter Industry 4.0) helps to improve waste management practices in smart cities to improve the sustainability of the city. This paper tries to develop a roadmap for industry 4.0 technologies relevant to managing waste in smart cities. This paper proposes a novel framework for analyzing the deployment enablers of Industry 4.0 technologies, implementation barriers, current best practices, and opportunities for digital technologies (EBPO) for smart city transformation. The proposed EBPO conceptual framework is analyzed in the context of studies conducted in developed and developing countries. The EBPO presents the unique linkages among the technological advancements for managing waste in smart cities. The present research is an early attempt to explore the relevance of industry 4.0 technologies in the smart waste management context for improving environmental sustainability. The keyword and theme mapping analysis proposes three major waste management clusters in smart cities. This paper provides insight for improving EBPO elements for smart cities’ waste management. The policy and theoretical implications are presented for smart city stakeholders. The paper also highlights the different dimensions of the EBPO framework.

Pandemic Governance: Responses for COVID-19 Management of Zamboanga City

The challenges brought by pandemic governance include the efficient management of socioeconomic, political, and health issues. In today's sociodemographic and globalized environment, a rational and scientific approach to pandemic governance and public health policy formulation necessitates a combination of science, culture, and people. Effective pandemic governance requires an approach that is adaptive, and lesson based. In instances when faith in governmental institutions and political leadership are crucial, knowledge of the public health system, epidemiology, and socio-political issues is also important. Effective pandemic governance can impact COVID-19 management outcomes. This study looks into the Zamboanga City's COVID-19 management responses. It examines the effectiveness of the measures implemented by Zamboanga City in the critical areas specified for the management of the COVID-19 epidemic. This study employs a descriptive-qualitative method using secondary data analysis and interview guide. This study demonstrates that Zamboanga City's approaches to the management of the COVID-19 pandemic are effective in thirteen (13) assessment categories. This study also reveals flaws in the application of countermeasures against the spread of the COVID-19 virus. Thus, there is a need to improve responses on the part of political leaders by designing, integrating, and implementing sound governance strategies in the fight against COVID-19 pandemic.

Impact of urban tree arrangement on pedestrian exposure to the size-fractional particulate matter in a city boulevard

Trees act as natural filters that mitigate roadside air pollution. However, the filtration impact of different tree arrangements on traffic pollutants with different particle diameters has rarely been analysed in real street canyon environments. To quantify how roadside tree arrangements impact pedestrian exposure to particle number concentrations (PNCs) of different diameters (0.25–32 μm), in situ field measurements were carried out in a boulevard-type street canyon in the city of Xi'an, China. This study analysed the experimental data of PNCs collected along segments of a pedestrian lane under four typical tree arrangements: open space without trees, a sparse-spaced tree arrangement, a medium-spaced tree arrangement, and a dense-spaced tree arrangement in a street canyon. Our results reveal that the effect of tree arrangement on PNCs depended on the particle diameter. In general, trees can significantly reduce coarse PNC (particles with diameters >2.5 μm) but not the fine PNC. Quantitative analysis showed that a medium-spaced tree arrangement, in which tree crowns are adjacent to each other but do not overlap, is the most capable of reducing PNC, followed by a sparse-spaced tree arrangement, while a the dense-spaced tree arrangement has the least impact. The attenuation effect of trees on the PNCs increased with increasing particle diameter. Moreover, the presence of trees altered the local microclimate, which also affected how exposure to PNCs changed. Our empirical findings further highlight the complexity of how trees affect particulate pollutants in street canyons and provide timely insights for enhancing tree-planning management in cities from the perspective of air quality improvement.

Analysis of Indonesian Public Sentiment towards the Cities of Jakarta, Surabaya and Medan Using the Naïve Bayes Algorithm

The theory of sentiment analysis is interesting to research, this theory aims to group the polarity of a text in a sentence, feature/aspect, or document and then determine whether the opinion contained in the sentence, feature/aspect, or document has positive or negative sentiment. . Sentiment analysis helps in understanding how people respond to certain issues related to these cities (Jakarta, Surabaya, Medan). This research uses the Naïve Bayes algorithm by conducting sentiment analysis on cities such as Jakarta, Surabaya and Medan, we can gain valuable insights to support better decision making in various aspects of city development and management. The results of this research provide an accuracy value of 77% for the city of Jakarta, 76% for the city of Surabaya, 75% for the city of Medan. These results also show that the Naïve Bayes model has quite good performance in carrying out sentiment analysis. Keywords: Indonesia, Sentimen, Naïve Bayes, Twitter

Knowledge Level and Practice of Primary School Teachers Regarding Traumatic Dental Injuries and Their Emergency Management in Twin Cities

Background: Childhood dental trauma frequently occurs at school, with primary school teachers often being the first responders. The immediate response and management by teachers can help mitigate the adverse physical, psychological, and social impacts of dental trauma on children. Despite the significance, there is limited data on the knowledge and practices of primary school teachers regarding the emergency management of dental injuries. Objective: The objective of this study was to evaluate the knowledge level and practices of primary school teachers concerning dental trauma and its emergency management. Methods: This descriptive cross-sectional study was conducted in primary schools of Rawalpindi and Islamabad. A sample of 335 primary school teachers was selected using simple random sampling. Data was collected using a structured questionnaire adapted from Ivanda et al. (10), which included three sections: demographic information, background and satisfaction with current knowledge, and specific knowledge of dental trauma management. The questionnaire consisted of 14 multiple-choice questions, and knowledge was scored out of 14 points. Scores were categorized as good (11.2-14 points), moderate (8.4-11.1 points), or poor (<8.3 points) based on Bloom's cut-off points. Statistical analyses were conducted using Fisher’s exact test, chi-square test, and independent t-test with a significance threshold of p≤0.05. Results: All participants reported they had not received training for traumatic dental injuries (TDIs). The majority (97.9%) demonstrated poor knowledge, with only 2.1% showing moderate knowledge and none achieving a good knowledge level. There was a statistically significant difference in knowledge between private and public sector teachers (p=0.04), but no significant correlations were found between knowledge scores and age, education level, or teaching experience. Conclusion: Traumatic dental injuries occur frequently in schools, and teachers should be well-equipped to handle such emergencies. The study highlights the insufficient knowledge among primary school teachers regarding dental trauma management. Comprehensive training programs are recommended to improve teachers' preparedness, potentially reducing the physical and psychological impacts of dental trauma on children.

Inventorying and proposing solutions for street tree management in Thu Duc city, Ho Chi Minh City

Tree inventory plays an essential role in the urban landscape master plan. It serves as the foundation for data acquisition that supports the planning strategy and decisions relating to the community’s interests, particularly in recently established cities like Thu Duc city. This research was carried out from October 2021 to December 2022 in this city and aimed to inventory to gather qualified information for managing the city’s street trees. The study used an inventory form of street trees including criteria such as name, family, diameter at breast height (DBH), total height, and indicators of vitality and distance from trees to infrastructure. By this form, 287 streets were surveyed. The total number of investigated trees was 31.023 trees belonging to 65 species and 24 flora families, of which the species with a high percentage (from 10% or more) were Dipterocarpus alatus, Hopea odorata, Peltophorum pterocarpum, and Lagerstroemia speciosa. The most numerous plant family was Fabaceae. These trees typically had a height of less than 10 m, with a DBH of less than 20 cm. Many streets did not guarantee the distance between trees and infrastructure, particularly the distance to the electrical systems. The survey also showed that the majority of trees were healthy and grow healthily. From the current situation of Thu Duc city street trees, three solutions must be prioritized in order to improve street trees in this city.

A Review of IoT-Based Smart City Development and Management

Smart city initiatives aim to enhance urban domains such as healthcare, transportation, energy, education, environment, and logistics by leveraging advanced information and communication technologies, particularly the Internet of Things (IoT). While IoT integration offers significant benefits, it also introduces unique challenges. This paper provides a comprehensive review of IoT-based management in smart cities. It includes a discussion of a generalized architecture for IoT in smart cities, evaluates various metrics to assess the success of smart city projects, explores standards pertinent to these initiatives, and delves into the challenges encountered in implementing smart cities. Furthermore, the paper examines real-world applications of IoT in urban management, highlighting their advantages, practical impacts, and associated challenges. The research methodology involves addressing six key questions to explore IoT architecture, impacts on efficiency and sustainability, insights from global examples, critical standards, success metrics, and major deployment challenges. These findings offer valuable guidance for practitioners and policymakers in developing effective and sustainable smart city initiatives. The study significantly contributes to academia by enhancing knowledge, offering practical insights, and highlighting the importance of interdisciplinary research for urban innovation and sustainability, guiding future initiatives towards more effective smart city solutions.

A Water Demand Forecasting Model Based on Generative Adversarial Networks and Multivariate Feature Fusion

Accurate long-term water demand forecasting is beneficial to the sustainable development and management of cities. However, the randomness and nonlinear nature of water demand bring great challenges to accurate long-term water demand forecasting. For accurate long-term water demand forecasting, the models currently in use demand the input of extensive datasets, leading to increased costs for data gathering and higher barriers to entry for predictive projects. This situation underscores the pressing need for an effective forecasting method that can operate with a smaller dataset, making long-term water demand predictions more feasible and economically sensible. This study proposes a framework to delineate and analyze long-term water demand patterns. A forecasting model based on generative adversarial networks and multivariate feature fusion (the water demand forecast-mixer, WDF-mixer) is designed to generate synthetic data, and a gradient constraint is introduced to overcome the problem of overfitting. A multi-feature fusion method based on temporal and channel features is then derived, where a multi-layer perceptron is used to capture temporal dependencies and non-negative matrix decomposition is applied to obtain channel dependencies. After that, an attention layer receives all those features associated with the water demand forecasting, guiding the model to focus on important features and representing correlations across them. Finally, a fully connected network is constructed to improve the modeling efficiency and output the forecasting results. This approach was applied to real-world datasets. Our experimental results on four water demand datasets show that the proposed WDF-mixer model can achieve high forecasting accuracy and robustness. In comparison to the suboptimal models, the method introduced in this study demonstrated a notable enhancement, with a 62.61% reduction in the MSE, a 46.85% decrease in the MAE, and a 69.15% improve in the R2 score. This research could support decision makers in reducing uncertainty and increasing the quality of water resource planning and management.

Distance- and Angle-Based Hybrid Localization Integrated in the IEEE 802.15.4 TSCH Communication Protocol

Accurate localization of devices within Internet of Things (IoT) networks is driven by the emergence of novel applications that require context awareness to improve operational efficiency, resource management, automation, and safety in industry and smart cities. With the Integrated Localization and Communication (ILAC) functionality, IoT devices can simultaneously exchange data and determine their position in space, resulting in maximized resource utilization with reduced deployment and operational costs. Localization capability in challenging scenarios, including harsh environments with complex geometry and obstacles, can be provided with robust, reliable, and energy-efficient communication protocols able to combat impairments caused by interference and multipath, such as the IEEE 802.15.4 Time-Slotted Channel Hopping (TSCH) protocol. This paper presents an enhancement of the TSCH protocol that integrates localization functionality along with communication, improving the protocol’s operational capabilities and setting a baseline for monitoring, automation, and interaction within IoT setups in physical environments. A novel approach is proposed to incorporate a hybrid localization by integrating Direction of Arrival (DoA) estimation and Multi-Carrier Phase Difference (MCPD) ranging methods for providing DoA and distance estimates with each transmitted packet. With the proposed enhancement, a single node can determine the location of its neighboring nodes without significantly affecting the reliability of communication and the efficiency of the network. The feasibility and effectiveness of the proposed approach are validated in a real scenario in an office building using low-cost proprietary devices, and the software incorporating the solution is provided. The experimental evaluation results show that a node positioned in the center of the room successfully estimates both the DoA and the distance to each neighboring node. The proposed hybrid localization algorithm demonstrates an accuracy of a few tens of centimeters in a two-dimensional space.

Knowledge-based Bi-correction model for achieving effective lag-free characteristic on daily urban water demand forecasting

Accurate demand forecasting is crucial for the efficient management of smart cities. However, the non-stationary and nonlinear characteristics of daily water demand series present significant challenges, leading to the lag forecasting problem and unreliable predictions. To address these challenges, this paper introduces a novel bi-correction model based on knowledge extraction, named the knowledge-based bi-correction model (KbBcM). The KbBcM leverages prior and posterior knowledge to achieve effective lag-free forecasting. The prior knowledge, in the form of sequence and feature information, is extracted using an autoregressive long short-term memory (AR-LSTM) network and a newly proposed lag penalty attention (LPA) module. Furthermore, a hybrid stacked LSTM network is employed to obtain primary forecasting results, which are then corrected with a masked weighted Markov chain (MWMC) based on posterior knowledge. Addressing the limitations of current metrics focused on absolute error, we also introduce the novel mean prediction trend effectiveness (MPTE) to comprehensively evaluate the effectiveness of lag-free forecasting performance. Comparation experiments performed on the urban water demand dataset of a megacity demonstrate the superiority of the KbBcM over baseline models. Additionally, ablation studies are performed to examine the effectiveness of the proposed sub-modules, further validating the robustness and reliability of the KbBcM in addressing the complexities of urban water demand forecasting.

Based on 5G Internet of Things Technology (Iot), the Integrity of Agricultural Products and the Sustainability of the origin's Ecological Environment

The rise in population worldwide necessitates a change towards smart agricultural methods. This, along with decreasing natural resources, restricted agricultural land availability, and a rise in inclement weather, has led to making the food and essential safety as the critical element for most of the countries around the world. Therefore, it can be regarded that, the internet of things (IoT) is mainly focused in enhancing the overall performance of food production and enable in creating sustainable living. The application of wireless sensors has enabled as the critical aspect in implement the smart agriculture which will provide the ways in using the IoT in an effective manner. The different technologies like cloud computing, RFID (radio frequency) related tools has enabled in enhancing the overall IoT. Several advantages of IoT have been mentioned in this study. It has been stated that the implementation of new generation of cellular networks and IoT told are likely to become widely available in the coming decades. On a practical basis, this is potentially good from the standpoint of IoT, as many “mainstream” IoT applications will assist in creating sustainable city management, better building efficiencies and campuses. The primary impetus support in creating better mobile connectivity, support in using the critical technologies to enhance the overall productivity and output. To allow 5G cellular technology to accommodate large data rates, the millimeter wave spectrum must be used. Millimeter wave systems, on the other hand, necessitate the use of tiny cells. In overall, a facilitator enables in applying the technologies based on the needs and requirements of the organization to attain the stated purpose.

The evolving roles of actors in sustainability experiments: Evidence from community waste management in a Chinese city

Engaging and coordinating interconnected actors is critical to the success of sustainability experiments. However, a notable gap remains in understanding how multiple actors shape and influence the design and outcome of sustainability experiments in China. This article illustrates how a community waste management experiment emerges and develops from a fluid network of activities carried out by diverse actors in Qingdao city, China. We find that NGOs, the city government, industries, and various alliances across them play a critical role in accumulating resources, enhancing networks through fulfilling actors' interests, sustaining coordination, and creating strong long-term linkages, albeit with evolving roles and changing relative importance. While effective solutions need to be context specific, taking into account the geographical, cultural, policy and regulatory environment, our study epitomizes a possible pathway for transforming community waste management in Chinese cities facing common challenges in the backdrop of largely top-down governance and minimal public participation.

Study of the correspondences distribution of vehicle traffic on the road network of cities

The problems of traffic management in large cities are complicated as the increase in traffic volume far exceeds the road network capacity. It leads to saturation of the road network, which negatively affects its functioning. This article analyzes the state of the art of improving the quality of road traffic by predicting the size of traffic after the implementation of traffic management measures. While the issue of modeling traffic flow parameters based on technological factors has been sufficiently studied, the problems of considering the human factor need to be clarified. The object of study is traffic flow on the city's road network. The criteria used by drivers to compare the characteristics of alternative traffic routes were identified based on the field study results. Based on the data obtained, the parameters of alternative routes that drivers choose when driving on the road network are formed. According to the survey results, the most significant factor is the minimum mileage along the route. Deviations from the shortest route were determined to determine the patterns of distribution of correspondence of non-route vehicles along alternative routes. It made it possible to define the distribution of transport correspondence along alternative routes. Since the process under consideration is probabilistic, the law of distribution of a random variable was determined. After having determined the law of distribution of a random variable for the data obtained, the calculations showed that the change in the random variable is well described by the gamma distribution. It was determined that the share of transport correspondence that will be carried on them decreases as the length of the route deviates from the shortest one. The obtained results make it possible to predict road network congestion by modeling the distribution of traffic flows. In further research, it would be advisable to analyze the distribution of transport correspondence by other criteria.

A Tree-Prone Community: Residential and Street Tree Planting and Care in the Neotropical City of Xalapa, Mexico

Abstract Background Urban trees are the most conspicuous elements of greenery in cities, providing goods and services that contribute to people’s well-being. However, proper tree care and management are necessary for their survival, particularly for street and residential trees. Methods Through a survey, our objectives were to identify and quantify the presence of residential and street trees and the contribution of residents in tree planting and care in the city of Xalapa, Mexico. We assessed the dwelling characteristics that facilitate the presence, planting, and care of residential and street trees in the city (socioeconomic level, homeownership, time of inhabitance, and location of dwellings) via Generalized Linear Models. Results In Xalapa, the presence of residential trees was higher than that of street trees; people contributed significantly to the planting and care of both residential and street trees; the socioeconomic level and time of inhabitance were positively associated with the presence and planting of street trees; and homeownership was positively associated with residential trees. However, tree care was largely independent of tree planting and dwelling characteristics. Conclusions People’s contributions and commitment to planting and care for residential and street trees are high, with the dwelling characteristics showing as important factors for tree presence and planting, but not for tree care. Recognizing people’s actions and participation in tree planting and care and orienting them towards a positive impact through city planning and management can help to keep Xalapa as a green, functional city that provides quality benefits and services to the urban dwellers.

Enhancing the smart parking assignment system through constraints optimization

Traffic in big cities has become a black spot for drivers. One of the major concerns is the parking problem that hindering urban mobility particularly in the big city and other congested areas; Drivers lose a significant amount of time looking for looking for a parking spot. This leads to an increase in accidents, a big consumption of fuel and a spectacular augmentation of pollution. We present a parking assignment system based on constraint programming in this paper, to meet the need for effective parking management in smart cities, for a group of drivers booking in the same time and area. In this work, we suggest two formulations of the Parking Assignment Problem, The first was established by using Constraint Satisfaction Problems (CSP) and the second is based on Mixed Integer Linear Programing (MILP). An implementation of the model taking advantage of Choco solver dedicate to the constraint programming and the evaluation of its scalability compared to the Mixed Integer Linear Programing solvers. The experiments conducted with Choco and MILP solvers on a real case study in the city of Casablanca showed that the two methods generates promising solutions in terms of scalability and response time.