Insights in understanding critical growth drivers of innovation are essential for industrial development and economic growth for competitive advantage. This study identifies indicators from the world's major indexes and industry-level concerns. The indicators are mapped to these concerns using expert opinions and then treated mathematically using technique of order preference by similarity to an ideal solution (TOPSIS). This mapping ranks and identifies the most favorable indicators for several concerns. It, thus, identifies the critical role the indicators play for the drivers to the most effective advantage using the TOPSIS method as a comprehensive ranking of indicators effectively facilitates decision-making for estimated levels.

Smart Funding Options for Developing Smart Cities: A Proposal for India

The rapid growth of internet of things (IoT) applications, especially in wireless sensor networks (WSNs), has led to the generation of large amounts of real-time data from interconnected devices. This growth leads to challenges in securing data access and managing resources efficiently. To address these challenges, we propose a dynamic trust-based access control (DTAC) model for IoT and WSN applications. The DTAC model integrates behavioral trust evaluation and context-aware decision making to dynamically adapt access permissions to network conditions in real-time. the trust scores are calculated using fuzzy logic and machine learning techniques, which enable adaptive decision-making. To increase security, the model uses a hybrid encryption scheme that combines elliptic curve cryptography (ECC) with lightweight symmetric encryption, ensuring data confidentiality with minimal computational overhead. In addition, access control decisions are refined by contextual factors such as user roles, device locations, and data sensitivity. The model includes a collaborative re-evaluation mechanism that periodically updates trust scores and isolates malicious nodes without compromising network stability. The DTAC model is evaluated on key metrics such as security resilience, energy efficiency, and latency and demonstrates better performance than existing solutions. This model provides a scalable, energy-efficient, and secure framework for IoT and WSN applications that ensures reliable data access and privacy in diverse environments.

The increased availability of mobile devices has changed various industries and will continue to improve how information is processed in the future. Because of its improved mobile capabilities, augmented reality has become increasingly popular. The AR market is expected to grow at a rapid pace in the coming years, with some of the largest names in tech industries leading the way. Companies who want to stay ahead of the curve should at the very least think about how augmented reality could be integrated into their operations. Many smartphone applications have recently implemented Augmented Reality in different functional areas; the objective here is to investigate the various areas of Augmented Reality applications and to assess its success and potential in various fields. This paper will also provide an overview of Augmented Reality and analyze its potential and popularity in different functional areas. It will assist businesses, entrepreneurs, app developers, etc., in determining if Augmented Reality applications are appropriate for the functional area in which they are operating and might help them gain a competitive advantage.

This paper looks into the incorporation of Artificial Intelligence into cloud-native DevOps practices dealing in automation, workflow optimization, and proactive monitoring. The paper also outlines AI-based tools that support some of the main points in DevOps practice areas like CI/CD, infrastructure management, security, and observability. Additionally, it elaborates on new developments that shorten workflows in cloud environments. This study on AI-driven automation shows how these systems can help mitigate repetitive works, speed CI/CD Processes, and increase deployment efficiency. It further explains the possible AI contributions in the areas of real-time monitoring, anomaly detection, and rapid root-cause analysis. The paper also examines the existing challenges under which impeding aspects like scalability constraints, data issues, and overlook, as well as interpretability by human experts must be highlighted. Future research directions would also be mentioned at the end, intended to pave the way for practitioners and researchers to adopt artificial intelligence to develop.

The purposes of the research is to explore of the application of artificial intelligence in E-Commerce have changed the patterns in the buying behavior of customers, the different sectors using AI, the Intelligent systems and mechanisms, the benefits and threats in using AI in E-Commerce, different AI tools used to analyze the behavior and patterns of consumers. Artificial intelligence is playing an important role and creating a huge impact in every industry, business and many organizations. It is one of the main drivers of many emerging technologies which is making a huge impact in every aspect, wherever it is being implemented. Artificial Intelligence has now become one of the key components in the E-Commerce industry. Many E-Commerce businesses started implementing different artificial intelligence tools for understanding the buying behaviors of customers, visual searches, chat bots, analyzing to make strategies, retargeting etc. Artificial intelligence has optimized the potential of the E-Commerce industry and had opened many new paths in improving the customer experience, analyzing the patterns of consumer behaviors. This industry is evolving with the application of artificial intelligence unleashing its capacity to leverage the business. It totally changed the way retailers sell their products and services and also the customers who consume their products and services. Artificial Intelligence is also helping the business to increase its brand reputation by providing many a better delivery of services.