Human-Centric AI Adoption and Its Influence on Worker Productivity: An Empirical Investigation

This empirical study looks at how the industrial sector is affected by the deployment of human-centric AI and finds some amazing changes in the workplace. Following implementation, employee productivity increased by 35.5%, demonstrating the significant advantages of AI in automating repetitive jobs and improving overall efficiency. Simultaneously, job satisfaction increased by a significant 20.6%, highlighting the alignment of AI with worker well-being. Employee skill development increased by 29.6% as a result of structured AI training, which is consistent with the larger goals of adopting AI that is human-centric. Significant cost reductions of up to 40% of budgets were also realized by departments, resulting in significant economic benefits. These revelations highlight the revolutionary potential of AI integration in Industry 5.0, promoting a harmonic convergence of intelligent technology and human skills for an industrial future that is more productive, happy, and financially stable

Community Engagement in Smart Cities: A Social Network Analysis and Community Engagement Test

This study, carried out in the ever-changing context of Smart Cities, reveals the complex interactions of digital social networks, digital community involvement, and the Community involvement Test (CET) framework. The examination of data obtained from certain Smart Cities indicates a thriving milieu of community engagement, characterized by a markedly elevated rate of active participation. The identification of urgent issues, particularly those related to environmental sustainability, safety, traffic management, and educational quality, is consistent with the larger urban difficulties that these creative urban centers are facing. Additionally, the CET framework's integration of SNA data and survey results produces very high ratings, indicating the engagement programs' outstanding performance in promoting resident satisfaction and active involvement. These results highlight how digital technologies can help Smart Cities foster vibrant, engaged communities. They also highlight the continued need for smart urban policies to address urgent issues and maintain residents' quality of life while adhering to the Smart City paradigm

Supply Chain Optimization in Industry 5.0: An Experimental Investigation Using Al

This experimental study examines the use of AI-driven supply chain management solutions in the framework of Industry 5.0. An analysis of fictitious data that represented product inventory, supplier details, customer orders, and transportation details showed significant cost savings in transportation logistics (10%), improvements in supplier cost efficiency (20%), and significant reductions in excess inventory (10%). In Industry 5.0, artificial intelligence (AI) emerges as a key technology that can promote effective, customer-focused, and sustainable supply chains

IoT-Enhanced Public Safety in Smart Environments: A Comparative Analysis Using the Public Safety IoT Test

The present study does a comparative analysis to evaluate the efficacy of public safety measures boosted by the Internet of Things (IoT) in various smart settings. The "Public Safety IoT Test" methodology is used in the research to evaluate costs, user happiness, and safety improvement percentages. Smart Surveillance devices showed a noteworthy 35% increase in safety in metropolitan City A, while Wearable Health devices showed a surprising 40% increase in safety in rural Village D. At a cost of $500,000 in City A and$10,000 in Village D, these results emphasize the potential of IoT technology to improve public safety and well-being. User satisfaction scores of 4 and 5, respectively, demonstrate the acceptance and efficacy of these devices. Policymakers and urban planners may benefit greatly from this study, which highlights the flexibility of IoT devices in a variety of smart settings and their important role in creating communities that are safer and more resilient

A Comparative Study of Digital City Development Using the Data-Driven Smart City Index

This research compares and contrasts the evolution of smart cities using a comparative analysis based on the Data-Driven Smart City Index. The study includes four important tables: the Digital City Development Index, which shows City D as a model smart city because of its high Infrastructure, Data Utilization, and Connectivity Scores, offers a thorough summary of the development of smart cities. The three components of the Data-Driven Smart City Index are Environmental Sustainability, Governance, and Quality of Life. City D excels in all three areas. The importance of big data analytics, IoT adoption, and open data usage—all of which City D leads—is emphasized in Data Utilization in Digital City Development. Lastly, Connectivity Infrastructure in Digital Cities emphasizes the significance of cutting-edge technology, with City D leading the way in terms of availability of public Wi-Fi, 5G network connectivity, and fiber broadband coverage. These results provide insightful information that will help stakeholders, politicians, and urban planners advance cities into the digital age and improve the quality of life for citizens

Human-Centric AI Adoption and Its Influence on Worker Productivity: An Empirical Investigation

This empirical study looks at how the industrial sector is affected by the deployment of human-centric AI and finds some amazing changes in the workplace. Following implementation, employee productivity increased by 35.5%, demonstrating the significant advantages of AI in automating repetitive jobs and improving overall efficiency. Simultaneously, job satisfaction increased by a significant 20.6%, highlighting the alignment of AI with worker well-being. Employee skill development increased by 29.6% as a result of structured AI training, which is consistent with the larger goals of adopting AI that is human-centric. Significant cost reductions of up to 40% of budgets were also realized by departments, resulting in significant economic benefits. These revelations highlight the revolutionary potential of AI integration in Industry 5.0, promoting a harmonic convergence of intelligent technology and human skills for an industrial future that is more productive, happy, and financially stable

Community Engagement in Smart Cities: A Social Network Analysis and Community Engagement Test

This study, carried out in the ever-changing context of Smart Cities, reveals the complex interactions of digital social networks, digital community involvement, and the Community involvement Test (CET) framework. The examination of data obtained from certain Smart Cities indicates a thriving milieu of community engagement, characterized by a markedly elevated rate of active participation. The identification of urgent issues, particularly those related to environmental sustainability, safety, traffic management, and educational quality, is consistent with the larger urban difficulties that these creative urban centers are facing. Additionally, the CET framework's integration of SNA data and survey results produces very high ratings, indicating the engagement programs' outstanding performance in promoting resident satisfaction and active involvement. These results highlight how digital technologies can help Smart Cities foster vibrant, engaged communities. They also highlight the continued need for smart urban policies to address urgent issues and maintain residents' quality of life while adhering to the Smart City paradigm

A Comparative Study of Digital City Development Using the Data-Driven Smart City Index

This research compares and contrasts the evolution of smart cities using a comparative analysis based on the Data-Driven Smart City Index. The study includes four important tables: the Digital City Development Index, which shows City D as a model smart city because of its high Infrastructure, Data Utilization, and Connectivity Scores, offers a thorough summary of the development of smart cities. The three components of the Data-Driven Smart City Index are Environmental Sustainability, Governance, and Quality of Life. City D excels in all three areas. The importance of big data analytics, IoT adoption, and open data usage—all of which City D leads—is emphasized in Data Utilization in Digital City Development. Lastly, Connectivity Infrastructure in Digital Cities emphasizes the significance of cutting-edge technology, with City D leading the way in terms of availability of public Wi-Fi, 5G network connectivity, and fiber broadband coverage. These results provide insightful information that will help stakeholders, politicians, and urban planners advance cities into the digital age and improve the quality of life for citizens

Low triiodothyronine predicts mortality in critically ill patients

Objective: Alteration in thyroid hormones are seen in critically ill patients admitted to intensive care units. Our objective was to study the thyroid hormone profile, prolactin and, glycosylated hemoglobin (HbA1c) at admission and analyze their correlation with mortality. Materials and Methods: In this single centre, prospective, observational study, 100 consecutive patients (52M; 48F) admitted to medical ICU irrespective of diagnosis were included. Patients with previous thyroid disorders and drugs affecting thyroid function were excluded. All participants underwent complete physical examination and a single fasting blood sample obtained at admission was analyzed for total triiodothyronine (T3), total thyroxine (T4), thyroid stimulating hormone (TSH), HbA1c, and prolactin. The patients were divided into two groups: Group 1 - survivors (discharged from the hospital) and Group 2 - nonsurvivors (patients succumbed to their illness inside the hospital). The data were analyzed by appropriate statistical methods and a P-value of <0.05 was considered significant. Results: The mean age of the participants was 58.7 ± 16.9 years and the mean duration of ICU stay was 3.3 ± 3.1 days. A total of 64 patients survived, whereas remaining 36 succumbed to their illness. The baseline demographic profile was comparable between survivors and nonsurvivors. Nonsurvivors had low T3 when compared with survivors (49.1 ± 32.7 vs. 66.2 ± 30.1, P = 0.0044). There was no significant difference observed between survivors and nonsurvivors with respect to T4, TSH, HbA1c, and prolactin. Conclusion: Our study showed that low T3 is an important marker of mortality in critically ill patients. Admission HbA1c, prolactin, T4, and TSH did not vary between survivors and nonsurvivors