Achieving ultra-low latency in Vehicle-to-Everything (V2X) communication is essential for ensuring the safety and effectiveness of autonomous vehicles (AVs). However, existing systems often struggle to meet the stringent latency demands, particularly in complex and rapidly changing urban environments. This study introduces an innovative framework that utilizes artificial intelligence (AI) for dynamic resource allocation in V2X networks. By integrating real-time data analysis, edge computing, and 5G capabilities, the proposed approach effectively minimizes latency. Simulation results indicate up to a 35% reduction in latency compared to conventional models, underscoring the potential of AI in enhancing the responsiveness and reliability of V2X systems. These findings offer a significant step toward making autonomous vehicle deployments more viable in smart cities.

The rapid advancement of digital technologies, particularly Artificial Intelligence (AI) and Machine Learning (ML), is ushering in a transformative era for civil engineering and disaster management. This paper outlines a multidisciplinary approach that harnesses the power of digital transformation to augment disaster preparedness, response mechanisms, and sustainable urban development. By integrating AI and ML innovations, Information and Communication Technology (ICT) advancements, and emerging technologies like quantum computing and blockchain, this study explores innovative digital solutions aimed at addressing critical challenges within the sector. Key focal points include the application of AI for early prediction and management of natural disasters, the strategic use of ICT in enhancing urban resilience, and the adoption of virtual simulation tools in education to bridge the theoretical-practical gap. Through an in-depth analysis of case studies—ranging from AI-powered mobile applications in smart city ecosystems to advanced materials engineering—this research highlights the potential of digital technologies to build resilient infrastructures, improve public health outcomes, and promote sustainable urban planning. This paper contributes to the ongoing discourse on the role of digital innovation in civil engineering, providing insights into the benefits and challenges of integrating technology into traditional practices, with the ultimate goal of achieving a more sustainable and resilient future.

The Integrated Control and Command Centre (ICCC) is instrumental in enhancing global cities' efficiency, resilience, and sustainability as the central hub for urban management. By integrating diverse technological solutions and data sources, the ICCC enables real-time monitoring, analysis, and control of urban systems, aiding informed decision-making in city planning. Urban planners leverage the ICCC to assimilate data from various sectors such as traffic management, public safety, utilities, and environmental monitoring, fostering a holistic understanding of urban dynamics. This data-driven approach empowers planners to anticipate challenges, identify trends, and devise effective strategies for sustainable development, including optimizing traffic flow and implementing targeted interventions for environmental sustainability. Moreover, the ICCC serves as a centralized platform for emergency response and fosters citizen engagement through smart governance tools, enabling residents to access real-time information and provide feedback. However, challenges like lack of infrastructure, governance, funding, and skills hinder its holistic implementation. As technology continues to advance, the role of the ICCC will evolve, presenting new opportunities for innovation and sustainable urban development. Proposed in all Smart Cities of India under the Smart Cities Mission, Integrated Control and Command Centres (ICCCs) are operational in 100 cities, with Agartala, Indore, and Vadodara highlighted for sustainable business models. Yet, challenges persist in creating comprehensive ICCC models. Therefore, the main objective of this paper is to investigate and strategize the implementation of ICCCs in Indian cities for improved governance and urban resilience.

INTRODUCTION: Commercial buses serve as the predominant mode of public transportation in Tanzania, with 90% of travellers opting for them, especially for inter-regional and urban-rural journeys. Despite their widespread use, the affordability of this mode has led to a rise in road safety issues, resulting in an alarming surge in accidents, injuries, and fatalities. This paper explores the potential of eLearning as an alternative approach to enhance road safety in Tanzania's commercial bus sector. OBJECTIVES: The primary aim of this study is to assess bus drivers' perceptions of eLearning deployment and develop a tailored course to improve road safety practices. The overarching goal is to contribute to existing knowledge by creating a training course addressing identified gaps in the context of changing driver behaviours in Tanzania. METHODS: Employing a quantitative approach, data for this study were collected through an online survey on Qualtrics and semi-structured interviews over three weeks. Participants included individuals from the National Institute of Transport (NIT), Vocational Education Training Authority (VETA), road safety NGOs, and bus drivers in Dar es Salaam, in collaboration with the Land Transport Regulatory Authority (LATRA). The study involved the development of an eLearning package tailored for professional bus drivers, utilizing social network analysis techniques. RESULTS: The survey, comprising 153 participants, provided insights into bus drivers' preferences for a 35-hour theory and practical training program. Findings indicated a high willingness among drivers to adopt eLearning, with smartphones being the preferred device. The study also proposed a comprehensive eLearning package, incorporating six modules derived from research findings, to enhance road safety awareness among professional bus drivers. CONCLUSION: This research advocates for developing and implementing eLearning as a viable strategy to enhance road safety awareness and skills among commercial bus drivers in Tanzania. The proposed eLearning modules and the learning management system (LMS) aim to address the limitations of traditional in-person training, providing a flexible and accessible alternative. Future efforts should involve stakeholders, policy discussions, and integration with GPS tracking for targeted feedback and continuous improvement in driving behaviours. Overall, the introduction of eLearning has the potential to impact safety cultures within companies positively and contribute to reducing road traffic accidents.

The integration of automation into urban planning introduces a complex dynamic where efficiency often clashes with equity, especially for marginalized communities. This necessitates a delicate balance between these two aspects. This article investigates the ethical principles and equity considerations in urban planning decisions, revealing a historical and contemporary bias towards efficiency, marginalizing certain groups. Automation, while beneficial in sectors like transportation, land use, and infrastructure, can perpetuate existing inequities and pose ethical challenges such as algorithmic bias and data privacy concerns. The article explores the impacts of automation on plan execution and monitoring, highlighting the need for current best practices to address these challenges. It provides an overview of automation in urban planning and calls for continuous research, collaboration, and improvement to ensure efficiency and equity are mutually reinforced.

Effective crop production and harvesting decisions rely on proper farm monitoring and management. Each region has distinct needs for farm oversight, but the primary focus remains on collecting and evaluating environmental data such as temperature, soil moisture, air humidity, all of which are vital to plant growth. Gathering this data on a large scale requires significant effort and is often based on intuition or simple measurement tools. This paper proposes a novel solution for farming data collection using an IoT platform integrated Long-Range Wide Area Networks (LoRaWAN) network application with Augmented Reality (AR) technology and Machine Learning (ML) algorithms to predict key environmental daily indexes. In a pilot study in Quang Tho, Vietnam, the system accurately predicted environmental conditions, reduced the risk of crop failure, and improved farm management efficiency. This approach enhances real-time data interaction and offers predictive analytics, supporting sustainable agriculture.

INTRODUCTION: With the development of the Internet, users tend to express their opinions and emotions through text, visual and/or audio content. This has increased the interest in multimodal analysis methods. OBJECTIVES: This study addresses multimodal sentiment analysis on tweets related to natural disasters by combining textual and visual embeddings.METHODS: The use of textual representations together with the emotional expressions of the visual content provides a more comprehensive analysis. To investigate the impact of high-level visual and texual features, a three-layer neural network is used in the study, where the first two layers collect features from different modalities and the third layer is used to analyze sentiments. RESULTS: According to experimental tests on our dataset, the highest performance values (77% Accuracy, 71% F1-score) are achieved by using the CLIP model in the image and the RoBERTa model in the text. CONCLUSION: Such analyzes can be used in different application areas such as agencies, advertising, social/digital media content producers, humanitarian aid organizations and can provide important information in terms of social awareness.

As cities worldwide transform into smart, interconnected urban environments, the management of municipal waste emerges as a pressing challenge. This paper, titled "Development of a Smart Waste Management System with Automatic Bin Lid Control," offers a sophisticated solution that integrates seamlessly within the concept of smart cities. This system harnesses the power of the Internet of Things (IoT) to optimize waste collection and enhance urban cleanliness. The primary aim of this project is to create a smart waste management system that extends beyond traditional waste bins. It introduces a network of intelligent waste containers equipped with automatic lid control mechanisms that operate based on real-time waste level data. When approaching these bins, the lid control mechanism automatically opens the bin only if the waste level is not full, thereby facilitating convenient waste disposal. In the context of smart cities, this innovative approach presents several advantages. It optimizes waste collection efficiency by prioritizing bins in need of immediate attention and ensures that waste containers are not prematurely emptied, reducing unnecessary waste disposal trips. Moreover, the system enables city authorities to gain insights into waste level trends, fostering data-driven and proactive waste management strategies for a cleaner, more sustainable urban environment.

In modern society, people are increasingly using cameras at home, in shops, and on the streets. Traffic systems have also invested in building more surveillance camera systems. The data collected by cameras contains valuable information for traffic regulation and recording traffic violations. The challenge is how to effectively use this data. In this article, we will discuss the use of real-time data from surveillance cameras on some roads in Da Nang City for vehicle counting using background subtraction methods. Additionally, we also tested the detection of red light violations to contribute to the development of a smart traffic system. So, the use of background subtraction in analyzing real-time data from surveillance cameras can greatly improve traffic management

This study delves into the potential of Electronic Voting Systems (EVS) in Ghana, to enhance transparent and trustworthy electoral processes. We presented a comprehensive framework highlighting trust, diaspora engagement, and human factors in voting. The study proposes a robust EVS framework for Ghana, emphasizing trust and accountability, preventing electoral fraud, and encouraging African governments to invest in IT and collaborate with experts in e-government and e-voting systems. We commence with a detailed systems analysis, identifying specific electoral challenges in Ghana. An artifact is designed and developed, and the artifact's effectiveness is demonstrated through Design Science Research Methodology (DSRM). We evaluated its alignment with the desired solution for Ghana's electoral issues. We emphasize the potential of EVS to address electoral challenges in Ghana and underscore the importance of proactive government policies, IT investments, and collaboration with IT experts. User acceptance testing achieved a remarkable 98% approval rate, showcasing the feasibility of implementing EVS at the national level. This research underlines the pivotal role of EVS in Ghana and advocates for visionary government policies and investments in IT. These measures can modernize electoral systems, align them with international standards, and promote democratic progress while preventing electoral fraud in Ghana and other African nations to avoid condemnation and punishment of unconstitutional transfers of power that are being challenged by meticulously planned takeovers.