Information System and Smart City

Smart technology: Ecosystem, impacts, challenges and the path forward

2024-02-02T15:02:41+00:00

Smart technologies have become increasingly integral to modern society, bringing many benefits and opportunities. However, they also raise important questions about their impacts on individuals, organisations, and society and how everyone can move forward smoothly in integrating and adopting technology. Therefore, this study analysed and reviewed the literature to address the questions. The study provides an overview of the potential benefits and challenges of smart technologies and applications, including artificial intelligence, machine learning, natural language processing, robotics, and the Internet of Things. The review also explores the key entities involved in a smart technology ecosystem, including governments, businesses, and international communities, and each entity’s unique role in developing and implementing smart technologies. Additionally, the review highlights the importance of ensuring a smooth transition to smart technologies, including the need for effective policies, regulations, and ethical considerations. The key takeaways from this review are the need to balance the benefits and opportunities of smart technologies with the challenges and risks they pose. Individuals, society, businesses and governments must play their respective roles in ensuring that smart technologies are developed, implemented, and used in ways that are responsible, ethical, and sustainable.

Enhancing disaster management in smart cities through MCDM-AHP analysis amid 21st century challenges

2024-02-02T15:02:41+00:00

In the era of rapid urbanization and technological progress, smart cities offer a promising solution to multifaceted global challenges, leveraging advanced technologies to optimize resources and enhance the quality of life; however, this interconnectedness also exposes them to novel vulnerabilities, particularly in the face of natural and man-made disasters, necessitating inventive strategies to ensure resilience against cyber threats and extreme weather events. This article delves into the exploration of smart cities’ diverse aspects and the categories of disasters they face, followed by an analysis of strategic mitigation approaches and their underlying criteria; it subsequently introduces the Multi-Criteria Decision-Making methodology, particularly Analytical Hierarchy Process (AHP), as a robust tool for systematic evaluation and prioritization of disaster management strategies in the increasingly complex landscape. The study’s analysis of relative weights underscores the pivotal role of Resilience Enhancement and Communication Redundancy as primary considerations in evaluating disaster management strategies for smart cities, while other criteria such as Accuracy and Timeliness, Scalability and Adaptability, Cost-effectiveness, Ethical and Privacy Considerations, and Training and Skill Requirements assume varying degrees of importance in supporting roles, providing valuable insights into the decision-making process. The assessment of alternative strategies highlights their prioritization in effective disaster management for smart cities, with notable emphasis on Citizen Engagement and Education, Early Warning Systems, and data analytics; further strategies such as Integrated Communication Systems, Resilient Infrastructure Design, Drones and Robotics, Artificial Intelligence Algorithms, and IoT-enabled Sensors and Monitoring exhibit varying degrees of significance, offering insights into their roles and potential contributions to disaster management strategies based on their weighted sums. This research has practical significance, guiding stakeholders like urban planners, policymakers, and disaster management professionals to enhance smart city resilience and prioritize strategies based on critical factors, ultimately enabling effective disaster management in smart cities amid 21st-century challenges.

Securing tomorrow’s urban frontiers: A holistic approach to cybersecurity in smart cities

2024-02-02T15:13:49+00:00

To address the intricate interplay between digital infrastructure and urban ecosystems, this study will adopt a multidisciplinary approach, combining expertise from cybersecurity, urban planning, and information technology. The research will delve into the vulnerabilities and potential threats that arise with the integration of IoT devices, interconnected systems, and the extensive data networks inherent in Smart Cities. By understanding the technological landscape, our goal is to devise adaptive and resilient cybersecurity measures that safeguard critical infrastructures while preserving the privacy and security of citizens. The methodology involves a qualitative inquiry through an open-ended questionnaire from 50 stakeholders. The anticipated outcomes of this research include the development of practical guidelines, best practices, and policy recommendations to fortify the cybersecurity posture of existing and future Smart Cities. By addressing the intricate relationship between urbanization and technology, this project aspires to contribute to the creation of secure, resilient, and sustainable urban environments that harness the full potential of Smart City innovations while mitigating cybersecurity risks.

The impact of conformity, effort and performance expectancies on SMEs information technology adoption in Nigeria

2024-03-18T07:32:45+00:00

This paper investigates the drivers of SMEs’ adoption (Small and Medium-sized Enterprises’ adoption) of information technology (IT) in Nigeria, underpinned by the performance expectancy, effort expectancy and conformity impact on IT adoption. In addition, the study examined the impact of an organizational existence on IT adoption. Confirmatory Factor Analysis was applied to establish the model goodness-of-fit, while Structural Equation Modelling was employed to test the proposed model’s hypotheses. Further, multiple regression analysis was used to test the organization years of existence effect on IT adoption. The overall arching finding indicative predominant role of performance expectancy in explaining organization adoption of IT system. Furthermore, effort expectancy (ease of IT usage) showed mixed results. While it was a predictive construct in the overall study model, it proved redundant under five years of organization existence, but was predictive of organizational existence over five years. The conformity construct (maintenance of status quo) was insignificant in the study. The research adds value to the information technology literature by establishing the factors that drive 20 SMEs IT adoption in Nigeria, especially where organization age is concerned. The unit of analysis was at organization level, there is wisdom in considering employees’ demographics, 22 such as employee’s education, IT experience, or organizational trade in future studies.

Effective approach of face mask position detection and recognition

2024-03-29T02:49:18+00:00

During recent COVID-19 pandemic across the world, face masks became necessary to stop the spread of infection. This has led to challenges with effective detection and recognition of human faces using the existing face detection systems. This paper proposes a Convolutional Neural Network (CNN) based face mask recognition system, which offers two solutions—recognition of the person wearing face mask and position of face mask i.e., whether the mask is correctly worn or not. The proposed model could play instrumental role of face recognition. In the first stage, with the help of Viola-Jones algorithm, the model detects the position of the face mask. In the second stage, we identify the person with by a modified pre-trained face mask recognition DeepMaskNet model facilitates in identifying the person. The proposed model achieves an accuracy of 94% in detecting the face mask position and 99.96% in identifying the masked person. Lastly, a comparison with the existing models is detailed, proving that the proposed model achieves the highest greater performance.

Conceptualizing sustainable smart country: Understanding the role of different sectors in building its structure

2024-04-01T08:58:12+00:00

The objective of this Article Paper is to theorize the concept of a Smart Country; for that, we will discuss the footsteps that any country in the world can follow and become a Smart Country. We will define how a Smart Country will have processes and governance structures that are fully equipped with all the necessary technological advancements. These prerequisites will not only help in laying the foundation of Smart Country. Still, they will also provide a long-term solution that will ensure the sustainability of Smart Country, which will have the capacity to not only face the challenges of the future but also synchronize with the forthcoming computational development. Through a comprehensive literature review and research analysis, we have argued in this article that a sustainable smart country is a holistic concept, so in order to make it practical, we have to consider Political, Security, Social, economic, and finally, the environmental aspects of the country, and according to each aspect, we will be providing solutions to the challenges countries are going to be facing in the near future. With these aspects mentioned, we will be explaining the three interdependent actors, which are Smart Government, Smart Citizens, and Smart Technology. These three actors will become the pillars of a Smart Country, and the collaboration between them will play a vital role in the success of this initiative. The First pillar, Smart government, will play a role in creating sustainable Smart country practices. The second pillar, a smart citizen, will play a role in adopting sustainable smart country practices. Lastly, Smart Technology will be the catalyst that will make it possible to create a sustainable, Smart Country. The research in this article will contribute by providing a framework for conceptualizing a Sustainable Smart Country, which will help policymakers and researchers develop future strategies.

NLP-reliant Neural Machine Translation techniques used in smart city applications

2024-04-02T01:28:38+00:00

For smart city applications, Neural Machine Translation (NMT) methods based on Natural Language Processing (NLP) are crucial as they facilitate information sharing and communication among diverse populations. NLP techniques are used in many domains related to smart cities, such as development and research, business, industries, media, healthcare, and residences and communities. The majority of people in India communicate using their regional languages. The majority of applications used by users in smart cities will mostly accept English as input. These people will be able to interact with these smart city devices in their native tongues more effectively with the help of effective machine translation. Just 10% of Indians use English as their primary language of communication; there are 22 official regional languages in India. So, there is requirement of better machine translation using Natural language processing (NLP). Natural language processing for Indian regional languages has a very long way to go until it surpassing the abilities of existing rich NLP applications and techniques for English language. Machine Translation is technique of Natural Language Processing (NLP) which provides better inter-lingual communication. For low resourced Indian languages effective machine translation systems became important for establishing proper communication. Machine Transliteration is a technique to convert source language into target language using machine. The developed system takes English language as input and then applies machine translation techniques to translate the source language into multiple languages using trained RNN model and multi-lingual search model which search the input word across all the datasets and generate the output into other Indian languages such as Hindi, Tamil. Our approach achieves top performance for English-Hindi language pair and comparable results for other cases.

Understanding advertising in the era of social media

2024-04-07T03:18:32+00:00

The late 1990s saw the rise of social media, which changed how people consumed and disseminated information. Youth find social networking sites to be quite appealing and popular, and they frequently spend a lot of time using the platforms’ communication affordances. Since McLuhan contended in the 20th century that technologies aid in extending human capacity, media technologies have been seen as empowering and freeing. In the media and communication sectors, technologies have made it easier for humans to manipulate mechanical and electrical processes. This study employs secondary data in this context, having researched pertinent literature, papers, and assessed them in the direction of the existing literature in order to probe the topic of inquiry. The majority of the information in the study comes from secondary sources, which provided concrete sources of insight into the analysis. These sources included pertinent texts, journals, government publications, historical documents, and the Internet. The technique was applied to assess other published works. The approach aids in verifying the validity of such results from earlier research. The paper’s analysis of the literature led to the conclusion that, despite its challenges, social media advertising can reach a wider audience than traditional media. Social media sites such as WhatsApp, Facebook, YouTube, and others allow advertisers to reach a large number of potential customers at a lower cost, 24/7. This study indicates that companies that prioritize improving their brand image will find ways to do it by having advertising explore the various online channels.

Scheduling of integrated biogas energy system for rural areas using improved differential evolutionary algorithm

2024-04-07T06:09:15+00:00

Due to lack of rational system design, an enormous amount of energy and resources are wasted or ineffectively utilized in China’s rural areas. Therefore, it is crucial to develop a practical energy system that applies to rural areas. In this paper, a Stackelberg game model is established for optimization of integrated energy system (IES) in rural areas. As a leader, new energy supplier (NES) develops price strategy for electricity and heat, the flexible users and biogas plant (BP) as followers receive price information and make energy consumption plans. Then NES adjusts equipment output based on followers’ feedback on energy loads. The objective of our Stackelberg game is to maximize the profit of NES while taking into account the costs of followers. Furthermore, our study designs an improved differential evolutionary algorithm (DEA) to achieve Stackelberg balance. The optimization scheduling result shows that the proposed model can obviously increase the profit of NES by 5.4% and effectively decrease the cost of biogas plant by 4.5%.

Enhancing traffic control systems with live video analytics: Issues, challenges, opportunities, and recent problems

2024-04-09T01:19:19+00:00

With the rapid urbanization and increasing number of vehicles on the roads, it has become imperative to develop innovative solutions that can monitor and manage traffic congestion automatically. Traffic congestion harms the economy, environment, and overall quality of life. To address these challenges, smart traffic management systems employ cutting-edge technologies such as live video analytics and sensor-based adaptive traffic control systems. These systems can predict traffic patterns, locate congestion hotspots, and uncover abnormalities contributing to road accidents in real time. However, adopting these technologies for traffic control systems raises important concerns such as robustness and sustainability across different traffic junctions, data integration from multiple sources, and computational feasibility for real time computation. Therefore, this paper aims to present an overview of the potential benefits and challenges in adapting the latest technologies including the Internet of things and machine learning for sustainable traffic management. Additionally, a case study of a smart city is presented to evaluate an adaptive traffic control system based on live camera feed analytics by leveraging computer vision techniques. The adaptive traffic control system is accurate in vehicle detection and counting. This system is very useful for smart cities where traffic signals need to be automated according to the density of vehicles.

On the issue of ensuring the safety of objects with “smart habitat”

2024-04-09T07:33:14+00:00

The problems of ensuring the security of the smart ecosystem are considered, an analysis of modern Internet of things (IoT devices) used in the control loop of the smart habitat is carried out from the point of view of the possibility of protecting and depersonalizing the information circulating in it. The article pays special attention to the issue of integrating a specialized software platform into the smart environment infrastructure, which allows for a high level of not only IT security, but also the overall security of the facility. It made an analysis of economic development and subsequent application of the integrated STB platform. Practical recommendations of the organization to improve the security of using the Internet of things in ODR are considered.

Remote Sensing applications for effective fire disaster management plans: A review

2024-02-02T15:02:41+00:00

The current context of climate change and imminent global warming is leading to changes in temperature and rainfall patterns worldwide which affect soil moisture, vegetation and soil conditions, the incidence of dry and wet events, and consequently, the occurrence, intensity, and magnitude of fires. Fires harm people’s quality of life as they can disrupt economic activities and affect public health. Additionally, fires damage the environment, accelerating water and wind erosion processes, altering air quality, and contributing to ecosystem degradation. Pampas in Argentina was selected as an example to study fires at a regional scale using Remote Sensing techniques due to its status as one of the most fertile plains in the world and the country’s most densely populated area. The fires are carefully analyzed and described considering three stages: i) pre-fires, ii) fires, and iii) post-fires. Afterwards, fire disaster management plans are described to assess these events, reduce their impacts on society and biodiversity, and minimize the ecosystems’ recovery time. In this sense, this manuscript aims to review the relationships between climate change, global warming, and the occurrence of fires. Additionally, it proposes to analyze the potential of Remote Sensing in analyzing these events at a regional scale to provide the mechanisms and tools necessary for formulating fire disaster management plans.

Quantum computing in drug discovery

2024-02-02T15:02:41+00:00

Quantum computers are recently being developed in wide varieties, but the computational results from quantum computing have been largely confined to constructing artificial assignments. The applications of quantum computers to real-world problems are still an active area of research. However, challenges arise when the limits of scale and complexity in biological problems are pushed, which has affected drug discovery. The fast-evolving quantum computing technology has transformed the computational capabilities in drug research by searching for solutions for complicated and tedious calculations. Quantum computing (QC) is exponentially more efficient in drug discovery, treatment, and therapeutics, generating profitable business for the pharmaceutical industry. In principle, it can be stated that quantum computing can solve complex problems exponentially faster than classical computing. Here it is needed to mention that QC will not be able to take on every task that classical computers perform—at least not now. It may be classical and quantum-coupled computational technologies combined with machine learning (ML) and artificial intelligence (AI) will solve each task in the future. This review is an overview of quantum computing, which may soon revolutionize the pharmaceutical industry in drug discovery.

Shaping resilient buildings and cities: Climate change impacts, metrics, and strategies for mitigation and adaptation

2024-02-02T15:02:41+00:00

In an era characterized by unprecedented urbanization and escalating concerns about climate change, the resilience of buildings and cities has emerged as a paramount global imperative. This review article embarks on a comprehensive exploration of the intricate relationship between climate change and the built environment, delving into multi-faceted dimensions that encompass climate change impacts, quantification methodologies, adaptive strategies, disaster management, eco-centric design paradigms, and assessment metrics. As the world grapples with the challenges posed by shifting climate patterns, understanding the intricate interplay between these elements becomes pivotal to fostering sustainable urban development. From the far-reaching implications of climate change on buildings and cities to the intricate tools and strategies that assess, mitigate, and adapt to these shifts, this article offers a comprehensive roadmap for creating resilient urban landscapes that thrive amidst environmental uncertainties. By amalgamating diverse insights and approaches, it envisions a future where eco-design, climate resilience, and pragmatic strategies converge to shape buildings and cities that stand as bastions of sustainability and fortitude.