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Nowadays, smart objects, Internet of Things (IoT) devices, and evenWireless Sensor Networks (WSN) are equipped with Ambient Intelligence (AmI), which integrates pervasive computing at the technological stack’s core. Recent studies over the last decades show an increase in smart IoT infrastructure deployments with elements of pervasive computing such as AmI, enabling business intelligence and decision-making capabilities [12]. Some of the technologies that are capable of introducing AmI to processes includes, Pervasive Computing (PC), Mobile Computing (MC) and Cyber-Physical Systems (CPS) [13]. These technologies are reliant on their hardware resources, node computing capability, critical security models, machine learning capabilities, and central processing. AmI provisioning in the technology stack requires the characterization of resources and business objectives at every layer of the technology stack. To understand the interconnectedness of billions of these devices in pervasive and genuinely ubiquitous environments, it is necessary to explore real-world implementation and application scenarios. Smart cities are a great example of IoT devices working together towards AmI. Smart parking, remote monitoring, sidewalk monitoring, and real-time air quality monitoring are just a few examples of IoT sensors integrated in our ecosystems. Similarly, applications such as smart wearables have become an integral part of future health-care systems. Industrial IoT deployments have also grown significantly over the last decade. Integrating smart sensors improves the safety and security of industrial processes. To create a user-centric Internet of Things that connects people and their gadgets in a sustainable ecosystem, we must first address the integration of diverse technologies, the establishment of trusted communications, the management of huge amounts of data and services, and user engagement. This article decouples the enabling technologies, the underlying infrastructure, and vendor-specific and vendor-neutral implementations of the IoT environment by contrasting existing tools on the Internet with the proposed IoT stack. The purposes and objectives of the present IoT implementations, as well as the need for standardisation, are described in further detail at each layer. Additionally, the role and behaviour of these devices that contribute to the creation of an ecosystem in terms of processing capability, resource availability, energy consumption, and sensing capabilities are also examined in detail. Nowadays, technological advancements are reshaping the industry toward small-formfactor, low-power gadgets that integrate a plethora of components. As a result, device cost, processing power, energy consumption, and interoperability with other systems are viewed as critical aspects in IoT applications [14–17]. Numerous studies have been conducted across multiple industry sectors on IoT devices, their technological stack, and application areas. The majority of the literature provides a high-level overview of efficacy and application in this domain. Additionally, there is a dearth of literature discussing IoT optimization and integration in the context of industryspecific deployments. However, combining this data and offering clear recommendations for IoT optimization and integration with future networks, such as edge computing, 5G networks, and beyond, remains a challenge, which served as the motivation for this study. Some of the major study contributions can be given as follows.  A comprehensive insight into IoT technology stack, adaptation and growth trends.  The detailed investigation of IoT Functional blocks at every layer (referred to as horizontal fabric), state-of-the-art research corresponding these elements, and the associated challenges.  The characterization of Middleware, enterprise platforms and integration challenges for enterprise solutions (referred to as vertical markets).  Future directions to optimize the IoT Technology Stack and its integration with enterprise systems.  Interfacing Fog/Edge network to extend coverage, convergence and deployment scope for IoT networks.  State-of-the-art research in Fog/Edge networks, open challenges and directions towards IoT interfacing, thus enhancing application of vertical markets.