Keywords

1 Introduction

Pervasive or ubiquitous computing, which refers to computing that takes place anytime and anywhere, dates back to the 1990s when gadgets and wireless networks were not quite as advanced as they are now. Hence, it can be inferred from the above statements that technology advances at a breakneck pace. According to a recent edition of The Economist, “by 2035, the entire planet will have a trillion networked computers embedded into everything from garments to food packaging and construction industry” [1]. The IoT has swiftly become a strategic change factor for all businesses because it merges the physical and digital realms of the modern world. It offers a slew of advantages, which include a new generation of smart, linked gadgets. New value products are produced across various industries in the networked society by linking objects and imparting “acumen” to them. IoT can be described as a vast network of physical objects, such as security systems or household appliances, connected to the internet for convenient utilization. Digital components like sensors, microprocessors, software, connectivity, and data storage are extensively used in these products, besides mechanical and electrical components. As the world’s physical and digital edifices decussate, digital technologies are built into an array of consumer and industrial items; for example, motion sensors and video cameras are a part of internet-connected smart doorbells that warn a homeowner when someone approaches the door. The homeowner may monitor and converse with the guest via a smartphone application, while a video of their conversation is preserved for further protection. The demand for Internet of Things (IoT)-based linked applications and devices like smartphones, Google Glass, gadgets, etc., has accelerated immensely in recent years [2]. A tremendous amount of data is being produced rapidly due to the expansion of millions of IoT-linked devices. As a result, cloud storage becomes increasingly constrained as the amount of data produced, stored, and managed soars [3]. The cloud computing servers connect these devices in a hectic way, causing a slew of problems in optimizing important Quality of Service (QoS) characteristics, including processing, privacy, bandwidth, security, latency, response time, and storage [4, 5]. Since the cloud acts as a centralized mainframe to compute and store data and is generally located remotely from the IoT endpoints, the cloud server may take some time to respond to the data. Therefore, emerging fog computing technology relieves the strain of cloud computing services. Fog computing is a decentralized computer framework that distributes storage, intelligence control, and processing among data devices in close proximity. This framework now makes cloud computing services available at the network’s edge. Axiomatically, the network distance is reduced, and the quantity of data that has to be transferred to the cloud for processing, analysis, and storage is also reduced [6,7,8,9,10,11,12]. Wireless communication technologies have grown at an astounding rate, catapulting the way machines and humans interact. The enormous expansion of connected devices, together with the ever-increasing necessity for large bandwidth, have been the primary driving catalyst for such evolving advancements during the last decade. Though the implementation of 5G wireless communications is in its nascent stages with enmeshed characteristics that need improvement, it has become critical to consistently determine the future communication requirements and begin theoretical and practical projects on futuristic wireless system development. In general, any advancement in successive generations occurs over a 10-year period. 6G is expected to become widely available by 2030 [13]. The 6G market is expected to enable prominent advancements in imaging, location awareness, and presence technologies. With the collaboration with Artificial Intelligence (AI), the 6G computational infrastructure shall decide the ideal location for computing, including decisions concerning processing, data storage, and sharing. A significant aim of the 6G network is to facilitate communications with one-microsecond latency, which is a thousand times greater than 1-millisecond throughput (or 1/1000th of the latency). 6G is expected to deliver 1000 times the number of simultaneous wireless connections as 5G technology. Hence, the latency and capacity of 6G applications will be improved. It will also enable new and innovative wireless networking, cognitive, sensing, and imaging applications. 6G access points will be able to serve numerous clients at the same time using orthogonal frequency-division multiple accesses. The advent of smartphones increased the use of 3G services and encouraged 4G deployment requirements in the IoT business model; it is expected that some IoT businesses would support the 5G outbreak somewhere during the 5G period, hence increasing demand for upcoming 6G networks. Large IoT networks equipped with 6G networking and cognitive learning algorithms can swiftly conduct complicated calculations, transforming the user experience to real-time responsiveness [14]. Massive IoT networks will transform the healthcare, transportation, agricultural, and business sectors. Also, Smart grids with interconnected energy, water, and gas lines will make cities intelligent [15, 16]. Besides this, autonomous vehicles and wearable devices will become commonplace, making lives smoother and more convenient [17,18,19]. The complexity of a network grows in lockstep with its capacity. Heterogeneity, integration, interoperability, network capacity, network congestion, scalability, QoS provisioning, and battery lifespan are a few of the challenges that will be faced by 6G-empowered IoT [20,21,22]. IoT will be contingent on intelligent learning approaches and the extensive deployment of edge and fog computing devices in close proximity to end devices in order to overcome the challenges above [23, 24]. By performing calculations closer to end devices, edge and fog computing devices will alleviate the pressure on cloud servers, reducing computing latency [12, 25]. To boost the network efficiency even further, fog devices will smartly commingle spare resources from all accessible devices [26, 27]. The processing resources of accessible fog devices, edge devices, and other devices will be essential in living up to the expectations of highly demanding future applications (Fig. 1).

Fig. 1
An image represents the Internet of Things diagram of fog devices, edge devices, and other devices for future applications.

Expansion of IoT in different domains

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1.1 Article Organization

The remaining article is structured as shown in the following sections: Sect. 2 presents a literature review by different authors in this field. An overview of the three main subjects of discussion that are in the spotlight throughout this paper is given in Sect. 3. In Sect. 4, several applications of 6G-enabled Fog IoT networks are presented. Furthermore, Sect. 5 presents possible fog solutions for particular IoT challenges. Last but not least, the paper binds up in the next section.

2 Related Studies: Current Status

Ananya Chakraborty et al. outlined the progression of computing paradigms from the client-server model to edge computing, along with its goals and constraints. An up-to-date analysis of cloud computing and the cloud of things (CoT) is offered, covering its methods, restrictions, and research issues [28]. Jagdeep Singh et al. presented a comprehensive literature review on fog computing, discussed key features of fog computing frameworks, and pinpointed the different problems with regard to its architectural design, QoS metrics, implementation specifics, applications, and communication modalities. The article also examined the various taxonomically-based research projects and offered a classification based on the available literature for fog computing frameworks [29]. Christos L. and Stergiou et al. emphasized that 6G is a new sort of network architecture that yields all the advantages of its predecessors while simultaneously overcoming their drawbacks. Taking into consideration that telecommunications-related technologies like Cloud Computing, Edge Computing, and IoT can function on a 6G network, the author proposes a scenario that attempts to incorporate IoT functions with Cloud Computing, BigData, and Edge Computing to attain an intelligent and safe environment. Furthermore, the study presents a new and safe Cache Decision System in a wireless network that functions on a Smart Building, providing viewers with a secure and productive surrounding for surfing the internet, communicating, and maintaining big data in the fog [30].

Hazra, A., Adhikari, et al., developed a 6G-aware fog federation model for incorporating optimal fog needs and ensuring requirement-specific services all over the network while optimizing fog network operator profits and assuring the least delay in the service and cost for IoT users. A non-cooperative Stackelberg game connectivity method has been established to distribute fog and cloud resources by improving dynamic service expenditure and client requests. A resource console is activated to handle accessible fog assets, generate revenue for service suppliers, and guarantee the effortless quality of support. A comprehensive simulation study of 6G-aware performance specifications shows the advantage of the proposed model, which restricts latency to 15–20% and customer service to 20–25% when contrasted with standalone cloud and fog paradigms [31].

U.M. Malik et al. focus on reviewing the technologies that enable massive IoT and 6G. The authors also explore the energy-related complexities of fog computing in large-scale IoT enabled by 6G networks. In addition, they classified various energy-efficient fog software and services for IoT and characterized recent work in each of these segments. Subsequently, the authors analyze potential prospects and research issues in establishing energy-efficient fog technology for the upcoming 6G massive IoT networks [32]. The 6G enabled Network in Box (NIB) technology is demonstrated by Baofeng Ji et al. as a robust integrated platform capable of supporting complete network operation and management. This 6G-based NIB may be utilized as a substitute to address the demands of next-generation cellular networking by reconfiguring the network functionality deployment dynamically, giving a high level of elasticity for communication services in various scenarios. In particular, the computational intelligence (CI) technology used as part of NIB, including neural computing, evolutionary computing (EC), and fuzzy systems (FS), has implicit abilities to manage various uncertainties, offering exceptional benefits in processing the discrepancies and diversification of large datasets [33]. According to Asif Ali Laghari et al., the things in the IoT are similar to humans and computers in that they can be allocated IP (internet protocol) addresses and transmit data across networks or some other man-made thing. In this work, authors explore the use of IoT and empowering technological advancements, including cloud, fog, and 6G, in conjunction with sensors, applications, and security. Researchers discovered that sensors are critical elements of the IoT environment; if sensors fail while observing the working atmosphere, operating a vehicle, or in healthcare applications, a substantial loss will occur [34]. Mung Chiang and Tao Zhang highlighted the fog opportunities and limitations, concentrating particularly on the IoT networking aspect. This study defines fog as an emerging architecture for processing, storage, management, and networking that brings cloud-to-things services proximate to end-users. Fog as an architecture enables an increasing number of applications, such as the IoT, embedded artificial intelligence (AI), and Fifth Generation (5G) wireless systems. This article also explores why a new architecture called “Fog” is needed and how it could bridge technological shortfalls and provide new economic opportunities [35].

3 Overview of 6G Network, IoT, and Fog Computing

3.1 6G Vision

In 1926, Nikola Tesla stated: “The entire planet would be transformed into a giant brain when wireless is appropriately deployed.” Following the ideology of this visionary giant, a new vision of a 6G network has been proposed. The world is already witnessing how lifestyles and industries are progressively becoming data-driven and autonomous. This trend is anticipated to accelerate in the coming years. Various international efforts are being made by dominant countries in the wireless network industry for relevant B5G (Beyond 5G) as well as 6G initiatives and investments. Aside from that, a number of nations have started their own initiatives and given funds to conduct their studies. China, South Korea, Japan, Finland, Australia, the United States, and the United Kingdom are all in the running, and other countries are under pressure to join as well. Examples of ongoing Beyond fifth-generation (B5G) and 6G initiatives have been illustrated in Fig. 2 [36]. The next technological revolution is being driven by the merging of the digital and physical worlds, as well as automation and networked intelligence assistance. The line separating artificial intelligence, computer science, and telecommunications is blurring, allowing for a slew of new applications but also posing a challenge to future 6G networks in terms of complexity and cost to deliver additional services. The ITU (International Telecommunication Union) 2030 organization presented the first conjectural perspective on upcoming 6G services as well as use cases, emphasizing VR (virtual reality) and MR (mixed reality) services as key drivers for future 6G services.

Fig. 2
A table represents the flag of the various countries on the left and B 5 G forward slash G gambit on the right.

Global examples B5G/6G initiatives

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Fundamental Enabling Technologies

This study predicts five key technological necessities that will be required to meet the demands of the B5G/6G system and realize the paradigm transition from the IoT to the Internet of Intelligence, with the latter defined as functions that can represent information, process knowledge, and make choices [37].

  1. 1.

    Artificial Intelligence: The first paradigm transition is from a traditional 5G system and its upcoming releases, i.e., an AI-enhanced network, to an AI-native communication platform [37]. An AI-native 6G technology might provide conceptual communication functionality out of the box, mimicking how the human brain works. The widespread deployment of DNN (deep neural networks), which enables usable and comprehensible meanings to be generated from an infinite quantity of processed data, may facilitate semantic and goal-oriented communication [38]. Moreover, the design, control, and administration of next-generation wireless networks can be greatly aided through the widespread use of GTP (generative pre-trained transformer platforms) [39].

  2. 2.

    Combined Sensing and Communication: The next paradigm transition is to uplink and downlink sensing from an information-centric approach of bits and bytes (Fig. 3), with sensors infused in access points (radio heads) and devices, referred to as Neural Edges, that operate at exceptionally high frequencies lying in the spectrum of millimeter waves (mmW) and terahertz (THz) and utilizing extremely wide detachable and contiguous bandwidths (of beaucoup GHz). Sensing is a key aspect of future 6G networks and gadgets since it is the most fundamental form of intelligence. Aside from the traditional network quality indicators and wireless resource measures, it is expected to have a complete ability to detect the surroundings and aspects, similar to modern lidar or radar systems, and so retrieve a large amount of data. Sensing as a Service may be offered by blending this data with other data sources, photos, or anything else that could be acquired by any other sensors [37].

    Fig. 3
    A matrix on the left and a diagram on the right. The matrix represents the data-centric data of the bits and bytes, and the diagram represents the uplink and the downlink of the sensing.

    From data-centric to sensor-and-communication-integrated

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  3. 3.

    Connectivity in Air, Space, and Extreme Lands: The future generation of communication networks is projected to deliver ubiquitous services in previously unreachable places, such as outer space and across vast oceans. Terrestrial (land-based and marine), aerial (balloons, airplanes, pseudo satellites, drones, etc.), and space-based (LEO: Low Earth Orbiting, MEO: Medium Earth Orbiting, GEO: Geo-stationary Earth Orbiting) satellite constellation infrastructures will be combined to provide a seamlessly integrated connectivity architecture.

    NTN (Non-Terrestrial Networks) is defined as a network in which airborne (i.e., UAS (Unmanned Aerial Systems) or space-borne (LEO, MEO, GEO) and HAPS (High Altitude Platform Systems) automobiles act as base stations (BS) or relay nodes; infrastructure will be an essential component to access network of 6G services and backhaul of upcoming generation Information and Communication Systems (ICS) and will accomplish the requirements of service availability, reliability, and consistency over broad areas. The capacity of NTNs to provide wide-area coverage by offering connections across places (e.g., airplanes, rural areas, and submarines) that are exorbitant or impossible to access in terrestrial networks is its distinguishing feature. As a result, the NTN represents a terrestrial network coverage expansion in a global industry with high sales for various services continually expanding due to an escalating number of interconnected devices

  4. 4.

    Security Controls and Assurance, and Privacy Preservation: The fourth paradigm transition concerns privacy protection and cyber security generally: wireless 6G is anticipated to be secure in terms of design rather than being a security-enhanced system, as 5G is today when compared with 4G [40]. Though it is arduous to envisage preemptive security controls because wirelesses 6G has yet to be specified and agreed upon by any SDO (standards development organization), it is critical to recognize that by investigating the exposure to the risk of the projected 6G networks thoroughly, a tentative evaluation of potential attacks may be undertaken. New threats will emerge as a result of technological advancements; these must be addressed alongside any current threats that are being transferred from networks of previous generations [41]. To summarize, 6G must incorporate security into the infrastructure’s core and embed a defense-in-depth approach across the network, complemented by a Zero-Trust model [16], with the capacity to cope with various scenarios and unforeseen occurrences in harsh conditions in order to transition from a security-enhanced network to a security-by-design system (Fig. 4). In addition, new procedures for security management, security assurance, and privacy protection must be included in the 6G standardization process [37].

    Fig. 4
    Two diagrams. On the left is the digital lock and on the right is the design of the left image. The left image represents concealing, hash function, and shared secret.

    From security-enhanced networks to security-by-design infrastructures

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  5. 5.

    Prosumer Centric Systems: The final but essential paradigm change is the transition to a truly user-oriented system from an operator-centric one, which is no more than a generic stream of bits. The user is predicted to evolve into a true prosumer, meaning that they will not only be able to consume material and information but will also be able to create and distribute content, making it accessible to diverse people’s communities and cyber authorities through the usage of 6G services (Fig. 5) [37].

    Fig. 5
    Two diagrams of the prosumer-centric system. The left image represents the generic bit-pipe operator centric, and on the right is the user-centric.

    From operator-centric to prosumer-centric systems

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6G Services

6G services are expected to be available beginning in 2030 and lasting for the next 10–15 years. Several of these services will be available first with 5G technologies or their long-term progression; others would necessitate technological advancement and revolutionary network functions to fulfill their rigorous criteria as part of their typical paradigm of inexorable technological progress. In researchers’ opinion, in addition to the services now offered by 5G networks, 6G will include the following services to satisfy the multiplicity of new use cases:

  1. 1.

    Humongous Machine-Type Communication for Decentralized Intelligence (HMTCDI) service: The Machine-Type Communications (MTC) of Future 6G will expand the functionality of immense MTC envisaged in 5G to incorporate ubiquitously decentralized compute techniques that support the 6G network’s distributed intelligence, continuing the paradigm change started with 5G. This new service will be defined by its criticality, scalability, and effectiveness. Super smart cities, intelligent transportation systems, connected living, and other applications will be familiar.

  2. 2.

    Globally-Advanced BroadBand (GABB) service: This service is well-known for extending the computation-oriented communication system to accommodate rate-hungry tasks, including remote regions, such as oceans, the skies [42], and the rural areas [16], or the extended reality services, on-demand, at what time or which place.

  3. 3.

    Ultra-Reliable, Low Latency Communication, Processing, and Control (URLLCPC) service: These services are regarded to expand the capabilities of URLLCP services, which are presently 5G network supported, by incorporating compute services at the network’s edge as well as E2E (End-to-end; remote or automated) control. Latency and reliability within the particular service are components of communication and the computation side, such as accurate classification probability or learning accuracy. The service will support factory automation, networked and autonomous terrestrial, multi-sensor XR (Extended Reality) [43] and aerial vehicles, and other use cases.

  4. 4.

    Semantic Service: All applications that involve the sharing of knowledge between the parties that interact will be supported by these services. The limit is not only set for H2H (human to human) interactions, but the application will also offer M2M (machine to machine) and H2M (human to machine) communication. The intertwining and seamless connectivity of many types of intellect, both artificial and natural, will be the service’s goal. Affective computing, bi-directional and autonomous collaboration among distinct CPS (Cyber-Physical-Spaces), empathic and haptic communication, and other technologies will be enabled. This new service will be the first to offer an intelligence as a service, ushering in a profound transition that will completely transform wireless telecommunications from linked devices to linked intelligence.

6G Use Cases

6G networks entail use cases that were proclaimed throughout 5G but not yet attained, and also more sophisticated dilemmas emanating from the perspective of future generation/6G, which include haptic/tactile communications, omnipresent services (land, sea, air, space), healthcare services, national/government security, and so on. The following are some examples of related use cases, technical requirements, and associated services (shown in Table 1; where 1. MMTCCxDI, 2. GeMBB, 3. URLLCCC, 4. Semantic) [44].

Table 1 6G use cases, related technological requirements, and services
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3.2 Fog Computing

A cascade amount of data is produced as the number of IoT devices, mobile Internet, and other networked items increases [45]. According to a report by Statista, it is estimated the world will witness an upsurge in the number of IoT devices to triple by 2030, i.e., from 8.74 billion in 2020 to more than 25.4 billion (Fig. 6). As a result, conventional computing architectures, including distributed and cloud computing, appear insufficient to handle such massive data [46]. Some applications, along with smart healthcare emergency response, traffic signal infrastructures, as well as smart grids, need rapid reaction and mobility assistance [47]. To solve these difficulties, which include privacy-sensitive applications, ultra-high latency, large bandwidth, and geographic distribution, a computational architecture that facilitates cloud technology and executes the requested tasks of IoT devices with the shortest turn-around time and the lowest latency is necessary [48]. Cisco launched fog computing in 2012 to mitigate issues with IoT devices in the standard cloud technology [49]. Edge computing, i.e., a subdivision of FC, allows edge devices to execute computing and storage tasks hither to the edge. The massive IoT enabled by 6G will rely heavily on fog computing. With so many devices exchanging data and running several apps, the fog nodes’ computing and storage support for the end devices will be essential. Furthermore, these fog nodes will be heavily used in 6G communications to allow ubiquitous connection and achieve exceptionally low latency. This new fog computing-based 6 G-enabled large IoT paradigm will address several issues in terms of allocating resources; energy consumption, fairness, work offloading, reduced latency, and security.

Fig. 6
A pie chart represents the distribution of the Internet of Things worldwide from the year 2019 to 2025.

IoT devices worldwide (in billions)

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3.3 Massive IoT

The term “massive IoT” is used to describe the large-scale connectivity of a massive number of devices, sensors, and machines [16, 42]. IoT intends to link diverse items to the Internet, generating a linked world in which data collection, computing, and communication are carried out autonomously and without user intervention. It is a fundamental technique for interconnecting diver-gent electronic equipment with wireless connections. For the service of end users, IoT data may be acquired through prevalent digital assistants, including computer systems, sensor devices, mobile phones, actuators, computer systems, and radio frequency identification (RFID) [43]. The IoT is expected to grow rapidly in the upcoming years. Cisco [50] estimates that approximately 0.5 trillion IoT devices will be linked in 2030 to the World wide web, up from 26 billion in 2020. According to GlobeNewswire, the 5G-IoT market is expected to expand to 6.2855 billion dollars in 2025 [51]. The Internet of Nano-Things is similarly important for the development of future advanced IoT ecosystems in which a network of items (nano-devices and things) may detect, process, transfer, and store data using nanoscale elements (e.g., a nano controller) to support client operations like patient monitoring [52]. Interconnecting nano-networks through accessible internet and communication networks in a seamless manner necessitates the development of new network topologies and communication paradigms. In this regard, 6G will be a key facilitator towards upcoming IoT platforms and devices since it will deliver multi-dimensional wireless connectivity and consolidate all functions, such as sensory, communication, processing, intelligence, and completely autonomous operation. In reality, the upcoming generation (6G) wireless networks are projected to provide greater coverage and flexibility than the 5G networks, enabling IoT connection and service provision [53].

IoT network density is extremely high, attaining over 1 million units per square kilometer [54]. Consequently, tremendous amounts of data will need to be spread across devices, a significant number of activities will need to be completed, and massive amounts of data will need to be stored and big data evaluated. Consequently, fog computing and 6G will be critical enablers for large-scale IoT applications Several features are responsible for attaining intelligent 6 G-enabled IoT, some of which are discussed below:

  1. 1.

    Latency Reduction: Reducing latency results in the high-speed execution of jobs that enhance a service’s experience for users, which would be critical for its continuation in a fast-paced industry.

  2. 2.

    Fair Offloading: Fair offloading among gadgets while retaining adequate energy efficiency is crucial, not just for the network’s long-term viability but also for the owner’s contentment in continuing to share resources. Conversely, fairness is accomplished at the expense of extended delays. Therefore, to as-sure job completion within a given time frame, a trade-off between delay and fairness is required.

  3. 3.

    Load Balancing: It is a critical QoS (Quality of Service) element that ensures no device is overused and network operations are stabilized. In general, load balancing minimizes job queues, which reduces task execution time.

  4. 4.

    Resource Allocation: Every accessible computation node/device, as well as associated resources and data regarding their current computational jobs, must be examined by resource managers to allocate resources efficiently. These devices must balance multiple calculations, communication, and latency limitations to disperse the workload to achieve energy efficiency without overburdening the computing devices and other resources. In fog technology, IoT networks, precise system knowledge, and learning techniques aid in allocating resources.

  5. 5.

    Fault Tolerance: It refers to the system’s capacity to provide the necessary service not with-standing specific system faults. Fog nodes have built-in fault tolerance to ensure that all assigned tasks are completed. Offloaded tasks are monitored, and if a fog node exits the system due to a power outage and leaves a job incomplete, that work is offloaded to another fog node for completion.

4 Fog Enabled Intelligent IoT Applications: Trends and Challenges

FC is a viable technique for upcoming 6G networks capable of providing computational and storage capabilities. This technology will be critical in supporting 6 G’s enormous IoT applications since IoT and fog node devices have limited energy and computing solutions that necessitate intelligent energy-efficient storage. An overview of fog-based massive IoT and 6 G-enabled IoT-based applications is presented. There are numerous AI applications that make use of fog IoT networks; a few of these are discussed below [55,56,57]:

  1. 1.

    Wireless Communication Network: Fog would enable self-optimized processing, memory, management, and connectivity capabilities to move flexibly between the cloud, devices, network edge, and fog. Advanced and sophisticated gadgets like phones, laptops, and tablets are straining conventional wireless networks to their constraints. With a synergy of various Radio Access Technologies (RATs) such as 5G new radio (NR), LTE/LTE-Advanced, Internet-of-Things, Wi-Fi, 6G, and others, upcoming wireless communication infrastructures are projected to be intensively distributed and versatile in dealing with the constant traffic growth. Fog can access edge nodes and enterprise clients, which enables fog computing to take advantage of network edge processing applications, coordinated resource allocation, and distributed storage features. When a wireless system is fog-enabled, a significant portion of signal analysis and computation is dispersed, and regional information can be retained and analyzed at the network edge and user devices, facilitating programs that require deficient mobility and latency [58]. Offloading computationally complex operations to the fog node adjacent to the software platform can, for instance, significantly minimize application execution latency.

  2. 2.

    Intelligent Transportation System: As people’s reliance on transport services expands, transport systems confront various issues, including traffic jams, accident rates, and effective transport organization. Utilizing data, connectivity, control, computerization, and other contemporary advancements, an Intelligent Transportation System (ITS) is intended to build a real-time, precise, and effective system for transportation. An ITS maximizes the system’s effectiveness in terms of the flow of traffic, reliability, latency, and energy consumption by integrating data from a range of sources, such as sensors, navigation systems, and other vehicles. Fog computing is an important paradigm in modern network-connected society as it allows for low delay, high durability, and 24/7 service for applications [56]. It facilitates essential ITS operations by communicating, coordinating, and exploiting the underlying network capabilities within roads, smart cities, and highways. Fog will aid the adoption of many private and commercial autonomous vehicles by eliminating the issues associated with ITS.

  3. 3.

    Collaborative Robot System: Simultaneous localization and mapping (SLAM) is the synchronous construction of a surrounding map and assessment of the machine’s status in robotics [59]. Minimal cost, power-efficient, precise, and quick robot SLAM is essential, although such needs impose reciprocal constraints. To obtain precise mapping and positioning, a powerful computational unit is required, particularly in the optimization phase, which comprises various sophisticated analytics, and it is certainly contrary to the minimal-cost criterion. Using relatively moderate algorithms is an appropriate strategy to conserve the robot’s power requirements; moreover, this can lead to inconsistent SLAM. Furthermore, in several rescue instances, timing is crucial; as a result, the robot must act rapidly and execute quick SLAM, imposing additional strain on the inbuilt computer unit. SLAM speed can also be increased by employing low-complexity algorithms. However, there is a phase in which SLAM precision may be compromised. In a broad region with several robots, the robots need to engage in SLAM and eventually unify the maps, building a network and designating a robot as the leader in merging the SLAM and maps.

  4. 4.

    Smart Home: A smart home is just a distinct IoT system in which all digital equipment can be linked to the Internet and execute certain computer functions. Each device can be considered an IoT node and constitutes a local network.6G empowered fog provides a ray of light for smart home implementation. Fog’s multilayered structure allows the inclusion of its own fog nodes on each level or node to develop a control system with a hierarchical structure. Every fog node may be liable to perform emergency tracking and response operations, construct protection capabilities, and control the temperature and lighting of a home [56]. Also, they may offer a better storage and computation platform for citizens to guide sensors, computers, mobile phones, etc. Local sensors can transfer sensory or tracking data to nearby fog nodes first. The information will be preprocessed by fog nodes, making analysis easier.

  5. 5.

    Smart Cities: Another potential application of 6G-IoT is smart cities. Some examples of IoT applications for smart metropolitan cities include autonomous transportation, urban security, intelligent energy management systems, intelligent surveillance, water supply, and environmental monitoring. It is well known that several Smart-city strategies assert to enhance the daily life of citizens living in urban communities [57]. Smart city IoT technologies alleviate traffic congestion, minimize noise pollution, and aid in the security of metropolitan areas.

  6. 6.

    Smart Retail: In the field of Smart Retail, IoT fueled with fog and 6G would operate excellently. Retailers could interact with their clients more rapidly and conveniently with this support. The mobile phone would be the most common tool for this task. Clients might even purchase through their mobile phones using a mobile payment system, and they can track their orders.

  7. 7.

    Digital Health: IoT in healthcare has gained prominence in recent years and will continue to advance in the future. IoT in healthcare encourages individuals to use smart devices to live a healthy lifestyle. Although the notion of connected digital healthcare has enormous potential for both individuals as well as the medical and pharmaceutical sectors, it has yet to reach the vast majority of the population.

  8. 8.

    Smart Farming and Environment: The need for food is growing as the world’s population grows. In such a context, smart farming is among the most rapidly and crucially expanding fields of fog-enabled IoT. It not only assists farmers or agricultural enterprises to earn more profit but also allows consumers to acquire food at a lower cost and of higher quality. Farmers are utilizing fog-IoT-enabled devices to regulate vegetation water supply and gather intelligence on soil nutrients and moisture. Farmers in the field use sensors to evaluate natural boundaries (such as temperature and humidity), and this data could be used to increase the efficiency of production. One example is a robotized water system that responds to weather conditions. Natural boundaries are observed gradually in terms of temperature, soil nutrients, as well as moisture and forwarded to the fog servers for assessment. Obtained results can then be utilized to enhance the product’s quality and increase production. Air pollution is a problem nowadays, affecting the ecological climate and degrading air quality. IoT software powered by 6G-fog monitors vehicles that can cause an excessive level of contamination. Electrochemical toxic gasoline sensors can also be used to quantify air pollution. RFID (Radio-frequency identification) stickers make vehicles stand out. On the two roads, RFID readers are installed together with gas sensors. With this technique, it is significantly more feasible to distinguish and take action against polluted automobiles [34].

  9. 9.

    Society 5.0: Professor Harayama created the concept of “Society 5.0,” claiming that it attempts to address numerous modern societal concerns by integrating game-changing technologies, including IoT, automation, big data, and AI, into all sectors and social activities [57]. Instead of a future operated and supervised by Robotics and AI, Technologies are being utilized to establish a human-centered future where everyone will live an active and joyful life. Having tech, nature, and social systems operating in a balanced scope, one can keep a building efficient, supplying energy to a smart city and ensuring that all services provided by that city are efficient and available. This is made possible by a high level of integration between cyberspace (virtual space) and real space (physical space). In Society 5.0, a large volume of data collected through sensors in real space is collected and stored in virtual space. If society 5.0 is empowered with fog and 6G technology, it will be capable of enhancing its performance and transporting information more quickly and securely [60].

  10. 10.

    Industry 4.0: Industry 4.0 (I4.0) is intended to provide the manufacturing industry with new opportunities, such as satisfying customers’ requirements, maximizing decision-making, and adding additional application capabilities [57]. The I4.0 reformation is viewed as the amalgamation of two worlds: (1) physical (robotic and automation systems) and (2) virtual (big data and AI), to build the concept of smart factories via the IoT. This advancement has enabled several innovations, such as cooperative robotics as well as quality control through digital channels, and sensors have the potential to increase efficiency by 45–55%. Sensory technological advances have the prospect of obtaining vast volumes of data from complex applications. AI, cloud, fog, and IoT are expected to have the most significant effect, while edge computing, quantum computing, blockchain, and 3D printing are expected to have the least impact [61].

5 Fog as a Solution to IoT Challenges

Several drawbacks of present computer infrastructures that depend solely on cloud computing and end-user devices can be addressed by adopting fog. The table below (Table 2) illustrates how Fog might assist in addressing IoT challenges [35, 56, 57].

Table 2 IoT challenges and their possible solution
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6 Conclusions and Summary

IoT technology is anticipated to deliver new service models in several domains, including smart cities, smart grids, healthcare, smart transportation, rural area coverage, and more other services to facilitate faster as well as highly secure data processing for IoT users. All these IoT applications require ultra-fast connections (i.e., B5G/6G technique) as well as collaborative fog computing characteristics for their effective functioning. Fog computing with 6G communication technologies, if developed successfully, might unveil novel avenues for network administrators, cloud vendors, and diverse IoT users, allowing numerous network administrators and service providers to work together to manage the users’ demands. It facilitates excellent services to IoT customers, and they can enjoy high QoS factors, including fast data speed, uninterrupted internet connectivity, interoperability, and continuous innovation, resulting in a rise in the ratio of user satisfaction. To enhance the network performance, idle and spare resources, including all accessible devices, will be intelligently integrated through fog devices, as fog computing acts as a critical component in envisioned 6G technologies. This study summarizes the aforementioned technologies to illuminate concepts, including various fog-enabled IoT applications in B5G/6G networks, along with several challenges that IoT may encounter and provides possible fog solutions for the same. In essence, the research aimed to present a study to investigate the recent contributions to scientific studies on fog computing and IoT in the 6G-enabled contemporary age and to indicate prospective study and open challenges engulfing the merging of intelligent fog-IoT networks with 6G.