The Making use of cutting-edge technology like cloud computing and machine learning is essential for producing insightful data and facilitating wise decision-making. In order to meet the increasing requirement for continuous data processing, low-latency interpersonal interaction, and resilient...

The rapid deployment of data-driven edge (DDE) systems raises significant security concerns. As cloud providers expand edge technologies, accompanying security risks grow exponentially. Unlike traditional deployments, modern systems face sophisticated attacks compromising data, workloads, and...

Real time data processing of data in intelligent analytics, decision making and AI model training and updating is an area where edge computing can be put to effective use. This chapter focuses on their deployment with machine intelligence, sensors, and networking in IIoT and smart health care...

Urban healthcare infrastructure is increasingly relying on edge computing to handle massive amounts of medical data in real time, minimizing latency and enabling timely delivery of healthcare. Cloud-based healthcare solutions are typically plagued by network congestion, computation expense, and...

The rapidly growing amount of data produced by Internet of Things (IoT) devices, gadgets, and handheld tools has made edge computing an essential resource. This chapter explores how businesses can use smart edges to access real-time data, reduce latency, and make better-informed decisions. By...

Healthcare edge computing is an emerging paradigm that puts data processing in closer proximity to where data are gathered, cutting down latency and improving real-time decision-making for healthcare systems. In this work, we examine the application of bi-stacked Artificial Neural Networks...

The framework of distributed edge computing is the core of the replacement of centralized cloud computing infrastructure regarding the digital transformation. This chapter reviews the shift of strategies to be cloud-first to edge-first and the strategic, technological and financial reasons...

Edge computing in healthcare offers significant benefits by improving medical outcomes, enhancing operational efficiency, and supporting real-time clinical decisions. This chapter explores how edge systems build resilient healthcare networks, enabling rapid patient support through data-driven...

This chapter explores the integration of AI and quantum computing in cybersecurity, focusing on their combined potential to address evolving cyber threats. The primary objective is to analyze how quantum computing enhances AI-driven security frameworks, strengthening encryption, threat...

In today's world, the use of AI and ML has gained popularity in the last few decades and since then it has been used rampantly in the fields of E-commerce and business. The use of AI and ML as integral parts of business models in the digital world can be seen how it would be imperative to have...