Over the years, Artificial Intelligence (AI) has emerged as a computational paradigm to deal with complex problems in a plethora of application domains. Researchers have realized that by leveraging the unique capabilities of human intelligence with AI, it is possible to unlock new frontiers in problem-solving and efficiency. By combining human creativity, intuition, and domain expertise with AI's data processing, analysis, and automation capabilities, one can tackle complex problems more effectively. This talk shall explore how the augmentation of human intelligence with AI can revolutionize problem-solving and pave the way for groundbreaking advancements across multiple domains for a better future.

Today most of our decision-making and problem-solving abilities are driven by ever-increasing volume of available data. By combining human judgment and intuition with AI's ability to process huge amount of data, it is possible to provide humans with actionable insights into such data, enabling them to make well-informed decisions and solve complex problems effectively.AI techniques can provide the ability to process relevant data within time constraints and extract valuable information that may not be immediately apparent to humans.

AI systems can assist in problem-solving by augmenting human cognitive abilities. It can automate routine and mundane tasks, freeing up human cognitive resources so as to focus on higher-level cognitive tasks that require creativity, critical thinking, and domain expertise. This collaboration between humans and AI can enhance productivity and efficiency. Such collaboration is particularly valuable in complex and uncertain environments, such as scientific experiments, business strategies, healthcare, finance, and logistics.

In machine learning (ML), most of the tasks are innately required to satisfy multiple criterions simultaneously. These tasks of ML are categorized as multi-objective/criterion optimization problems where more than one criterion/objective are adopted and need to be optimized simultaneously. Traditionally, however, either only one of the objectives is adopted as the objective function or multiple objectives are aggregated to a single objective function. This can be mainly attributed to the fact that most classical machine learning algorithms can only deal with a single objective optimization function. Over a past few decades, many efforts on solving machine learning problems by considering multiple objectives have gained increasing impetus, particularly due to the success of multi-objective evolutionary algorithms and other population-based stochastic search methods. It is a fact to note that in multi-objective optimization problem, in the absence of single global optimal solution, we are looking for a set of optimal solutions known as Pareto optimal solutions. It has been realized that Pareto-based multi-objective learning approaches are more useful compared to learning algorithms with a single objective function in addressing various types of machine learning, such as unsupervised learning, supervised learning, and semi-supervised learning. A common benefit of the different multi-objective learning approaches is that a deeper insight into the learning problem can be gained by analyzing the Pareto-front consist of many Pareto-optimal solutions. This talk highlights the existing research on multi-objective machine learning with a research direction for potentially interesting topics in multi-objective machine learning.

The Internet of Things (IoT) Market has seen explosive growth in recent years, driven by the proliferation of connected devices and the increasing demand for data-driven insights. The various layers of the IoT value chain cover several distinct product or service research categories. IoT is an integrated part of Future Internet including existing and evolving Internet and network developments and could be conceptually defined as a dynamic global network infrastructure with self-configuring capabilities based on standard and interoperable communication protocols where physical and virtual “things” have identities, physical attributes, and virtual personalities, use intelligent interfaces, and are seamlessly integrated into the information network. IoT plays an important role in the current and future generation of Computing, Communication and Application. Smart IoT is an exciting emerging research field that has great potential to transform both our understanding of fundamental computer science principles and our standard of living. IoT is being employed in more and more areas making “Everything Smart”, such as smart home, smart city, intelligent transportation, environment monitoring, security systems, and advanced manufacturing. The Industrial Internet of Things Platform Market is a rapidly growing market that enables the integration of physical devices and machines with advanced software and analytics. IIoT platforms enable manufacturers to collect, analyse and process data from connected machines in real-time, allowing them to optimize their operations, improve product quality, and reduce downtime. The research on future of IoT in Home and Building Automation, Trends in Sensing Applications and AI at the Edge are the focus.

The IoT Market has seen explosive growth in recent years, driven by the proliferation of connected devices and the increasing demand for data-driven insights. One of the key drivers of IoT research is the increasing adoption of IoT technologies in the industrial sector, where connected devices are being used to optimize supply chain operations, improve efficiency, and reduce costs. The IoT research also look forward to how IoT will take advantage of an IP future, a more robust cloud, and progress in Artificial Intelligence & Machine Leaning (AIML).This trend is expected to continue as more and more businesses embrace the power of IoT to transform their operations and gain a competitive edge in their respective industries.

Internet Of Everything (IoE) has been one of the trending research lately, and it’s here, IoE is the upcoming most innovative and Ubiquitous technology advancement which is going to make networked connections more relevant and valuable than ever before. Turning information into action creates new capabilities, richer experiences, and unprecedented economic opportunities for businesses, individuals, and countries. IoT Research is considered one of the next industrial revolution enablers, which is fuelled by the advancement of digital technologies. In this context the research and development challenges to create a smart world are enormous.

This Keynote will feature IoT research trends, with a review of how a solid foundation guarantees a future-proof, secure and state-of-the-art technology.