key: cord-1029950-t34mew31 authors: Pattnaik, Sushant Kumar; Samal, Soumya Ranjan; Bandopadhaya, Shuvabrata; Swain, Kaliprasanna; Choudhury, Subhashree; Das, Jitendra Kumar; Mihovska, Albena; Poulkov, Vladimir title: Future Wireless Communication Technology towards 6G IoT: An Application-Based Analysis of IoT in Real-Time Location Monitoring of Employees Inside Underground Mines by Using BLE date: 2022-04-30 journal: Sensors (Basel) DOI: 10.3390/s22093438 sha: f678253e4f8b079b36692f360c1604081fc33cc5 doc_id: 1029950 cord_uid: t34mew31 In recent years, the IoT has emerged as the most promising technology in the key evolution of industry 4.0/industry 5.0, smart home automation (SHA), smart cities, energy savings and many other areas of wireless communication. There is a massively growing number of static and mobile IoT devices with a diversified range of speed and bandwidth, along with a growing demand for high data rates, which makes the network denser and more complicated. In this context, the next-generation communication technology, i.e., sixth generation (6G), is trying to build up the base to meet the imperative need of future network deployment. This article adopts the vision for 6G IoT systems and proposes an IoT-based real-time location monitoring system using Bluetooth Low Energy (BLE) for underground communication applications. An application-based analysis of industrial positioning systems is also presented. In recent years, wireless technology has been one of the fastest-growing technologies in the area of communication. Today, wireless technology is becoming one of the largest carriers of digital data around the globe. According to the Cisco Visual Networking Index (VNI) Global Mobile Data Traffic for 2016 to 2022, worldwide mobile data traffic increased about 10-fold over these 6 years, reaching 77 exabytes (approx.) per month by 2022 (Figure 1a [1] ). According to [1] , the device mix is becoming smarter (advanced computing and multimedia competencies with at least 3G connectivity) with an increasing number of smart devices with high computing capabilities and better network connectivity, which creates a growing demand for smarter and more intelligent networks. The share of smart devices and connections as a percentage of the total will increase from 46 percent in 2016 to 85 percent by 2022, a more than two-fold increase during the figure time frame Figure 1b [1] . It is expected that 75 billion devices will be connected by the end of 2025 [2] . devices and connections as a percentage of the total will increase from 46 percent in 2016 to 85 percent by 2022, a more than two-fold increase during the figure time frame Figure 1b [1] . It is expected that 75 billion devices will be connected by the end of 2025 [2] . Service providers around the globe are busy rolling out 5G networks to meet the growing demand of the end consumer for greater bandwidth, higher safety and quicker connectivity on the move. Many vendors have additionally begun area trials for 6G and are getting closer to rolling out 5G deployments in the direction of the end of the forecast length. Moreover, the heterogeneous nature of the next-generation communication networks in terms of the application, communication technology used and involvement of diversified devices brings a large variety of requirements and expectations. Today's world is focusing more on the IoT due to its wide range of applications from human-centric to industry 4.0/industry 5.0. Nevertheless, device-to-device (D2D), machine-to-machine (M2M) and vehicle-to-vehicle (V2V)/V2X communication technologies constitute the real applications showing the widespread advantages of the IoT [3] [4] [5] [6] [7] [8] [9] . Furthermore, reliable data transmission with low latency is another key challenge for successful IoT applications [10] . The emergence of the Internet of Everything (IoE), which offers remarkable solutions for massive data transmission to the edge network, and the integration of Industrial Control Systems (ICSs) with the IoE recast it as the Industrial Internet of Everything (IIoE) [5] . Again, with the evolution of different emerging technologies such as artificial intelligence (AI), machine learning (ML), cloud computing, cognitive computing, edge computing, fog computing, blockchain technology, etc., various challenges are being addressed in different IoT industrial applications. Such complex IoT networks provide substantial technological prospects that facilitate the realization of good quality of service (QoS) and quality of experience (QoE). For example, the Internet of SpaceThings (IoST) for high speed, reduced latency and umbrella Internet coverage; the Social Internet of Things (SIoT) for an interface between human and social networks; the Internet of NanoThings (IoNT) for telemedicine; and the Internet of UnderwaterThings (IoUT) for improving ocean water quality, cyclonic/tsunami disaster management, etc. [11] . In view of this, the IoE introduces essential protection challenges due to the wide variety of functionality and demanding situations. There is always a dependency of the IoT on cellular networks since long-term evolution (LTE) was introduced, which is enhanced as 5G/6G in some specific scenarios. The demand for high throughput, high energy efficiency and better connectivity with reduced latency time can be attained beyond 5G/6G networks [12] . The 6G system will offer a better enrollment of the IoT devices as the 5G IoT has provided a solid foundation. The future 6G network is envisioned to be service-oriented, where software-defined networks (SDN) and network function virtualization (NFV) will play a vital role in the end-to-end architecture [13] . These technologies are capable of providing better coverage with high throughput, improved spectrum Moreover, the heterogeneous nature of the next-generation communication networks in terms of the application, communication technology used and involvement of diversified devices brings a large variety of requirements and expectations. Today's world is focusing more on the IoT due to its wide range of applications from human-centric to industry 4.0/industry 5.0. Nevertheless, device-to-device (D2D), machine-to-machine (M2M) and vehicle-to-vehicle (V2V)/V2X communication technologies constitute the real applications showing the widespread advantages of the IoT [3] [4] [5] [6] [7] [8] [9] . Furthermore, reliable data transmission with low latency is another key challenge for successful IoT applications [10] . The emergence of the Internet of Everything (IoE), which offers remarkable solutions for massive data transmission to the edge network, and the integration of Industrial Control Systems (ICSs) with the IoE recast it as the Industrial Internet of Everything (IIoE) [5] . Again, with the evolution of different emerging technologies such as artificial intelligence (AI), machine learning (ML), cloud computing, cognitive computing, edge computing, fog computing, blockchain technology, etc., various challenges are being addressed in different IoT industrial applications. Such complex IoT networks provide substantial technological prospects that facilitate the realization of good quality of service (QoS) and quality of experience (QoE). For example, the Internet of SpaceThings (IoST) for high speed, reduced latency and umbrella Internet coverage; the Social Internet of Things (SIoT) for an interface between human and social networks; the Internet of NanoThings (IoNT) for telemedicine; and the Internet of UnderwaterThings (IoUT) for improving ocean water quality, cyclonic/tsunami disaster management, etc. [11] . In view of this, the IoE introduces essential protection challenges due to the wide variety of functionality and demanding situations. There is always a dependency of the IoT on cellular networks since long-term evolution (LTE) was introduced, which is enhanced as 5G/6G in some specific scenarios. The demand for high throughput, high energy efficiency and better connectivity with reduced latency time can be attained beyond 5G/6G networks [12] . The 6G system will offer a better enrollment of the IoT devices as the 5G IoT has provided a solid foundation. The future 6G network is envisioned to be serviceoriented, where software-defined networks (SDN) and network function virtualization (NFV) will play a vital role in the end-to-end architecture [13] . These technologies are capable of providing better coverage with high throughput, improved spectrum efficiency, greater bandwidth and ultra-low latency. The 6G IoT system is sustainable for highaccuracy localization and sensing, which are necessary for most of the envisioned highly computationally intensive applications. A growing number of research works focus on current advances in wireless and IoT technology, including in-depth analysis of the advanced technology concepts, methodology and techniques. Specifically, [14] provides a comprehensive survey on key enabling technology for 6G, where the emphasis is on a discussion of the operation of the individual technology with useful statistics for industries and academic researchers on the potential for investigating new research directions. The authors of [15] discussed the requirements of 6G and recent research trends to enable 6G capabilities and design dimensions by employing disruptive technologies such as artificial intelligence (AI) and driving the emergence of new use cases and applications manifested by stringent performance requirements. A review of 6G in terms of use cases, technical requirements, usage and key performance indicators (KPI) is presented in [16] . Here, the authors presented a preliminary definition roadmap, specifications, standardization and regulation for 6G. A survey on wireless evolution toward 6G networks is presented in [17] , discussing the capabilities of network slicing technology with AI to enable a multitude of services with different quality of service (QoS) requirements for 6G networks. A comprehensive survey on the existing trends, applications, network structure and technologies of 6G is presented in [18] , with a focus on industrial markets and use cases of 6G that take advantage of a better on-device processing and sensing, high data rates, ultra-low latencies and advanced AI. In [19] , the authors presented an overview of 6G describing the complete evolution path from 1G networks to date and focusing on several key technologies such as terahertz communications, optical wireless communications (OWC) and quantum communications for improving the data rates. A comprehensive survey on the convergence of the IoT and 6G is presented in [20, 21] with a focus on edge intelligence, reconfigurable intelligent surfaces, space-air-groundunderwater communications, terahertz communications, massive ultra-reliable and lowlatency communications and blockchain as the technologies that empower future IoT networks. A comprehensive study on 6G-enabled massive IoT is presented in [22] , where ML and blockchain technologies are discussed as the primary security and privacy enablers. In [23] , the potential of the IoT and 6G for various use cases in healthcare, smart grid, transport and Industry 4.0 have been elaborated jointly with the challenges during their practical implementations. Several shortcomings of 5G and features of 6G related to social, economic, technological and operational aspects such as the weakness of short packet and sensing-based URLLC, which may limit the dependability of low-latency services with high data rates or the lack of support of advanced IoT technologies are discussed in [24] . Current research activities, therefore, should focus on innovative techniques such as advanced time-stamp stream filtering combined with intelligent network slicing to support multi-party (source) data stream synchronization in very low latency environments coupled with distributed control (at the edge). In [25] , the author mainly focuses on the integration of blockchain technology into 6G, the IoTand IIoT networks. Blockchain technology has a strong potential to fulfill the requirements for massive 6G-based IoT for the integrity of personal data protection, data privacy and security and scalability. Furthermore, a sustainable ecosystem-focused business model, driven by blockchain-empowered 6G networks is thoroughly analyzed to deal with the cutting-edge worldwide economic disaster. Envisioning the green 6G-IoT network, a novel joint design technique using intelligent reflective surface (IRS) and ambient backscatter communication (ABC) is proposed in [26] . This method is primarily based on the joint design of an iterative beamforming vector, an IRS phase shift and reflection coefficients to decrease the AP's transmit power without affecting the QoS. The author in [27] addressed the three fundamental components, i.e., artificial intelligence (AI), mobile ultra-high speed and the (IoT) for the future 6G network. The authors focused on the recent approaches, research issues and key challenges of IoT network topology and terahertz (Tz) frequency. A comprehensive survey of existing 6G and IoT-related works is summarized in Table 1 . We present a comparative analysis between 5G and 6G. We present the vision and key features of 6G with its different aspects. We present a brief review of several challenges of 6G. We propose a BLE-based real-time location monitoring system by using the IoT The remainder of this article is organized as follows. Section 2 presents the vision, applications and challenges of the IoT, including the connectivity standards and a com- parative analysis of their capabilities. In Section 3, a comparative analysis of 5G and 6G with the vision key features and the challenges of 6G is presented. Section 4 proposes and discusses a BLE-based real-time location monitoring system by using the IoT. Finally, we draw conclusions in Section 5. Related abbreviations are listed in the Appendix. A schematic representation of the structure of the paper is shown in Figure 2 . In the last few decades, the IoT has become the most promising and thriving area of research in academia and industry. The IoT extends the existence of communication by converging clients, businesses and industries by connecting intelligent things with each other through the cloud. These smart connections encompass different network applications, communication technologies and smart devices along with physical and virtual things. The IoT paradigm is a transformation from a centralized computer-based network to a completely distributed network of smart devices. To take the potential benefits of the IoT and to compete globally, the IoT European Research Cluster (IERC) has focused mainly on establishing a cooperation platform between companies and organizations for developing more research activities on the IoT at the European level. The primary objective of IERC is to facilitate making the research activities more ambitious and neoteric. The International Telecom Union (ITU) was the first international agency to produce a report on the IoT in 2005 [28] . Thereafter a new standard of the IoT was approved by the ITU in 2012 [29] . However, the term IoT was first used by the Massachusetts Institute of Technology's (MIT's) Kevin Ashton in 1999 [30] . In the last few decades, the IoT has become the most promising and thriving area of research in academia and industry. The IoT extends the existence of communication by converging clients, businesses and industries by connecting intelligent things with each other through the cloud. These smart connections encompass different network applications, communication technologies and smart devices along with physical and virtual things. The IoT paradigm is a transformation from a centralized computer-based network to a completely distributed network of smart devices. To take the potential benefits of the IoT and to compete globally, the IoT European Research Cluster (IERC) has focused mainly on establishing a cooperation platform between companies and organizations for developing more research activities on the IoT at the European level. The primary objective of IERC is to facilitate making the research activities more ambitious and neoteric. The International Telecom Union (ITU) was the first international agency to produce a report on the IoT in 2005 [28] . Thereafter a new standard of the IoT was approved by the ITU in 2012 [29] . However, the term IoT was first used by the Massachusetts Institute of Technology's (MIT's) Kevin Ashton in 1999 [30] . The vision of the IoT has different perspectives based on the data generated by the connected objects and the technology used. During the early stages of IoT implementation, the vision was to identify the physical objects by using radio frequency identification (RFID) tags. However, due to recent technological advances, the vision of the IoT has been reformed by encapsulating varying technologies and smart sensors. The IoT leads the way in unfolding the new generations of different compelling applications and services in the field of Industrial IoT (IIoT), Industry 4.0 and Society 5.0. Figure 3 , illustrates the key technologies that impact the IoT. In the last few decades, IoT has become the most promising and thriving area of research in academia and industry. The IoT extends the existence of communication by converging Clients, Businesses, and Industries by connecting intelligent things with each other through the cloud. These smart connections encompass different network applications, communication technologies, and smart devices along with physical and virtual things. The IoT paradigm is a transformation from a centralized computer-based network to a completely distributed network of smart devices. In order to take the potential benefits of IoT and to compete globally, the IoT European Research Cluster (IERC) has mainly focused on establishing a cooperation platform between companies and organizations for developing more research activities on IoT at the European level. The primary objective of IERC is to facilitate the research activities to be more ambitious and neoteric. International Telecom Union (ITU) is the first international agency to produce a report on IoT in the year of 2005 [28] , thereafter a new standard of IoT is approved by ITU in the year of 2012 [29] . However, the term IoT was first brought into focus by Massachute Institute of Technology's (MIT's) Kevin Ashton in the year of 1999 [30] . IoT applications in various sectors have been assessed based on their impacts on society and the economy along with their technology readiness level (TRL). The applications of the IoT are diversified based on their use in different fields such as intelligent homes, healthcare, agriculture, transportation, the environment, education, retail and logistics, industries and many more [31] [32] [33] [34] . Consequently, the IoT has also had an impact during the pandemic era of COVID-19 in many aspects, e.g., contact tracing, virus detection by temperature scanning, remote health monitoring, quarantine e-tracking, virus spread control, etc., and also in tackling the post-COVID-19 situation [35] [36] [37] [38] . AI-integrated IoT technology for the early detection of COVID-19 is discussed in [37] . This research mainly focuses on analyzing the extracted features of cough, shortness of breath and speech difficulties by using long short-term memory (LSTM) with recurrent neural network (RNN). In [38] , an IoT-based real-time learning system is developed to control the spread of COVID-19 infection in the context of smart healthcare for residents. The system is used to monitor and analyze user activities and environmental parameters which helps predict critical cases, so alerts can be sent to the caretakers. A few applications of the IoT are briefly presented in Table 2 . With an increase in the number of smart devices and real-time applications, the complexity of IoT networks has increased in terms of their densities and architecture. These complexities scale down the performance competencies of the current IoT network. There are several IoT challenges, namely, universal standardization, connectivity, cloud computing, energy efficiency, IoT protocol and architecture in addition to security and privacy. The IoT is still in its developing stage; so many more challenges have to be addressed with the revolution of technologies in the future research domains of the IoT. A few challenges of the IoT are briefly presented in Table 3 . As per the IoT analytics report, there are mainly 21 IoT connectivity standards that can be broadly classified in two ways: as cellular IoT and non-cellular IoT connectivity standards. The cellular IoT standards are operated at a licensed spectrum, whereas the noncellular IoT is operated at a non-licensed spectrum. Different IoT connectivity standards are depicted in Figure 4 [135] [Source: IoT Analytics Report 2021]. A comparative analysis of different IoT connectivity standards is presented in Table 4 . vironment As per the IoT analytics report, there are mainly 21 IoT connectivity standards that can be broadly classified in two ways: as cellular IoT and non-cellular IoT connectivity standards. The cellular IoT standards are operated at a licensed spectrum, whereas the non-cellular IoT is operated at a non-licensed spectrum. Different IoT connectivity standards are depicted in Figure 4 [135] [Source: IoT Analytics Report 2021]. A comparative analysis of different IoT connectivity standards is presented in Table 4 . Proprietary [140] , ITU G.9959 [142] FSK, GFSK [136, 137, 140] FHSS [89] , CSMA/CA [138] AES-128 [138, 140] IoT Connectivity Standards With the standardization of 5G about to complete and its commenced global deployment, several latent limitations to meet the necessary requirements of IoT systems still remain. These impediments mainly relate to the high computation, security, wireless brain-computer interface (WBCI) intelligent communication in terms of more autonomous human-to-machine (H2M) communication, holographic communication (augmented reality/virtual reality) and AI. These data-hungry applications require more spectrum bandwidth (e.g., mm-wave) and high spectral efficiency which can be realized at the subterahertz (sub-THz) and THz bands [154] . Furthermore, due to the incorporation of a wide variety of mobile applications, there are some more challenges (beyond uRLLC, coverage, localization, privacy, power consumption, better quality-of-service, etc.) that need to be addressed in the future B5G wireless communication standards. In this context, the 6G is attracting more researchers from academia and industries towards itself. A comparative analysis between 5G and 6G is presented in Table 5 . Despite the dramatic revolution of IoT-5G application in today's wireless networks, 6G is anticipated to excel 5G in many ways, not only in daily life, but also in Society 5.0. Even though 6G is not a talking point of global harmony so far, some additional features with more potential and capabilities are being discussed. In this section, a comprehensive vision of a 6G network is presented from multiple perspectives as shown in Figure 5 . As 6G is envisioned as a fully automated and smart network, the incorporation of AI, MLand quantum machine learning (QML) makes the future wireless networks more intelligent and predictive by limiting human efforts [176, 187] . AI and ML are the transforming technologies and data analytics tools in the modern era of wireless communication that bring new research challenges in the field of 6G IoT [186] . By using big data and ML, a more precise performance prediction model can be implemented in a 6G IoT network to make smart decisions for security, optimization, resource allocation, network management, self-organization, etc., [155] [156] [157] [158] [159] [160] [161] [162] [163] [164] [165] 188] . Due to the high veracity/volume data and complex 6G IoT network structure, it is necessary to instigate more futuristic learning/training frameworks for high-dimension neural networks (HDNN) [165] . Integrity AI [154] • Operational Intelligence (OI) • Environmental intelligence (EI) • Service intelligence (SI) Quantum Machine Learning (QML) [176] Terahertz (THz) Communication [156, [177] [178] [179] [180] • Support High Data Rate (Terabit/s) [181] • Secure Communication [181] • Small Attenuation with Large Penetration [181] Visible Light Communication (VLC) (430-790THz) [164, 169] Holographic Communications [156] Mind-Machine Interface (WMMI) [22] Haptic Communication [22] Human-Centric Communication [182] • Disease Diagnosis/Emotion Detection • Collection of Biological Features Society 5.0 (SDGs) [183] [184] [185] • Smart Food Due to the emergence of multi-access edge computing (MEC) in the 5G network, there are several limitations in the centralized network, e.g., privacy, security, trust, incompatibility of the existing protocol to the dynamic connectivity and distributed and ubiquitous computing [166] . Thus, it is necessary to prepare a blueprint of decentralized architecture to support such a dynamic and autonomous network. In this regard, blockchain is a promising technology for the future 6G network and is capable of dealing with these challenges. Blockchain technology can provide a decentralized network management framework that can be used for resource management, data sharing/storage, spectrum sharing and other challenges [172] [173] [174] [175] 189 ]. The 6G network is expected to meet the essential requirements for energy-efficient wireless communication globally. The green 6G network enables minimum energy utilization and helps achieve a peak data rate (THz) during signal transmission. A significant improvement in the energy efficiency of a network can be greatly experienced by incorporating different energy-harvesting techniques [154, 190] . This also helps facilitate green communication by reducing CO 2 emission. In addition, several communication techniques, e.g., D2D communication, massive multiuser multiple-input-multiple-output (MIMO), heterogeneous network (HetNet), green IoT, non-orthogonal multiple access, energy-harvesting communications, etc., may be adopted to facilitate green communication for future wireless networks [191] [192] [193] . With reference to the data analysis shown in Figure 1 , the ever-increasing demand for high data rate and seamless connectivity to such ultra-dense networks can be provided by integrating terahertz (THz) (ranges from 0.1-10 THz) communication in 6G networks [168, 177, 178] . A vast amount of unused radio spectra which can be efficiently used to increase network capacity is available in the THz band. THz is additionally reasonable for high data rate transmission and short-range communication by empowering the ultra-high bandwidth and uLLC paradigms. An extensive review of THz communication with its future scope and challenges is presented in [194] . It is believed that human-centric communication is a key feature of the 6G network. With the help of this technology, sharing and/or accessing different physical features can be possible by humans. To accelerate human-centric communication rather than technology/machine-centric communication, the principal means of human perception must be incorporated into the communication system module [195] . A human-centric communication framework needs two fundamental aspects-technology and user experience (UE). The latter includes human behavior as well as psychological and socioeconomic contexts and needs to be considered during the modeling and analysis of the communication system [183, 184, 195] . In 2016, Society 5.0 was initiated by the Japanese cabinet in its Fifth Science and Technology with a vision to build a "Super Smart Society" [196] . Later, the vision was revised and presented by the Keidanren Business Federation with the prime focus of delivering sustainable development goals (SDGs) through the creation of Society 5.0 [183, 184, 197] . Society 5.0 is designed to solve different social issues by taking advantage of technological advancements. Considering different aspects of economic growth, social and environmental conditions, 17 primary objectives and 167 goals are listed in the Agenda 2030 by the United Nations to address several global challenges [198, 199] . Even though several advanced features have been added to 6G networks to enhance the performance matrices in comparison with 5G networks, there are still some key challenges that must be addressed further. These challenges are broadly classified into two categories: (i) technological challenges that include high throughput, EE, connectivity flexibility, more intelligent optimization techniques, etc., and (ii) non-technological challenges including industry barriers, spectrum allocation, regulatory policies and standardization, etc. [200] . A few key challenges of the future 6G networks are summarized in Figure 6 . Even though several advanced features have been added to 6G networks to enhance the performance matrices in comparison with 5G networks, still there are some key challenges that must be addressed further. These challenges are broadly classified into two categories; (i) technological challenges which include high throughput, EE, connectivity flexibility, more intelligent optimization techniques, etc., and (ii) non-technological challenges including industry barriers, spectrum allocation, regulatory policies, and standardization, etc. [200] . A few key challenges of the future 6G networks are summarized in Figure 6 . Selfaggregating communications fabric [200] Policies and regulations [200] Figure 6 . Challenges of 6G [5, 154, 156, [200] [201] [202] [203] . In addition, due to the integration of the IoE, terrestrial and non-terrestrial communication networks in 6G, their different heterogeneous highlights must be considered to productively coordinate them. Heterogeneity is likewise present in the protocol that those communication networks will comply with. Thus, 6G is taking on the massive task of integrating a number of heterogeneous aspects [203] . Furthermore, due to the inclusion of mm-Wave and THz communication, 6G networks are facing several more open challenges, e.g., more sensitive low-power transmitter, new model architecture, advanced propagation techniques for better coverage and directional communication. The networks must also deal with system noise, channel fading and fluctuations [169, [203] [204] [205] . Several more challenges such as computational and processing resources due to the application of AI [206] , a few ML application-related challenges [207] , training issues and interoperability challenges [208] , challenges in estimating the channel information by using reconfigurable intelligent surfaces (RIS) [209, 210] and computational and trade-off challenges due to the application of artificial neural networks (ANN) in the IoT [211] have been recognized for the future 6G networks. Mining is one of the most speculative businesses around the globe. Most of the mines all over the world are lagging in different safety measures causing many casualties and deaths. The basic causes of death in underground mines are gas accidents, rock falling, ventilator accidents, fire, explosions, etc. Considering the safety issues of the employees/workers inside the mines, real-time location tracing of those employees becomes a major concern. Effective underground communication is necessary to collect more information about the mines or workers. However, there are various constraints while collecting the real-time data inside the mines such as restricted transmitting power, large attenuation of the transmitted signal from the rock wall and low penetration of the electromagnetic signal. In this regard, it is always beneficial to take the potential advantages of low-power and short-range communication technologies such as, RFID, Zigbee, Bluetooth, Bluetooth low energy (BLE), etc. In this section, a scenario for a Bluetooth low energy (BLE) beacon-based real-time location monitoring of employees/workers by using the IoT is presented. A BLE beacon and microcontroller are used to design this asset-tracking product and have been implemented in the IoT here by connecting this device to the cloud. Underground communication inside mines is a major factor for the safety and security concerns of the mineworkers. The advent of IoT technology and its usefulness can be beneficial for the mining industry. It is believed that a robust communication infrastructure using IoT technology inside the mines may enhance the safety of the workers and is also capable of providing real-time information resulting in quick action to avoid lethal situations. Several researchers have proposed various frameworks and ideas for efficient communication inside the mines based on IoT technology, which includes low-power and short-range communication. The authors of [212, 213] proposed a wireless sensor network (WSN)-based monitoring system for underground mines. In this proposed technique, various sensors are placed at different locations to collect activities and positions of the employees, and the collected data are transferred to the end user or the central server via BS. Nageswari et al. [214] , proposed an IoT-based smart mine monitoring system that uses radio frequency (RF) technology for communication purposes inside the mines. With this proposed technique the real-time location and real-time sensing of the dynamically varying environment can be achieved by using RF technology and WSN network, respectively. The major drawback of this proposed model is that large-signal transmission loss occurs through the walls of underground mines. An IoT-based mine safety system using WSN was proposed in [215, 216] . In these proposed techniques, the authors used a Zigbee module for information collection from the cloud and measured the surrounding parameters of underground mines with the help of various sensors. A mine safety system using WSN was proposed in [217] , where the authors constructed a prototype by using Zigbee and WSN to monitor safety issues and to measure the ambient properties, e.g., temperature, humidity, airflow, etc., inside the underground mines. A Zigbee compliant RFID-based safety system for underground coal mines was proposed in [218] , where a unified wireless mesh-network infrastructure was used to monitor and locate the workers and measure the different environmental parameters inside the coal mines. Similarly, an IoT-based system for underground coal mines that uses a microcontroller, a node MCU and various sensors to measure the environmental conditions and safety measures of workers was proposed in [219] . A LoRaWAN-based coal safety and health monitoring system was proposed in [220] . In this proposed methodology, LoRaWAN uses low-power RF with a wide communication range and IoT technology for monitoring the workers' health and observing the status of the circumstances in the coal mines. There are several existing technologies used for communication purposes in underground mines. The most common approaches are RFID, Zigbee, Bluetooth, GPS, etc. Table 6 presents a comparative analysis of some existing technologies in terms of their pros and cons [214] [215] [216] [217] [218] [219] [220] [221] . To overcome these issues, our proposed technique uses BLE, which is a low-power and low-cost technology. This proposed methodology reduces the deployment cost and complexities by using the BSs of the existing cellular network infrastructure for the communication process. The system architecture of BLE-based real-time location monitoring in mines by using the IoT is shown in Figure 7 . In this scenario, two base stations (BS) are deployed to provide necessary services (uplink/downlink) to the BLE devices through the central office server as shown in Figure 7a , and the complete workflow is shown in Figure 7b . and low-cost technology. This proposed methodology reduces the deployment cost and complexities by using the BSs of the existing cellular network infrastructure for the communication process. The system architecture of BLE-based real-time location monitoring in mines by using the IoT is shown in Figure 7 . In this scenario, two base stations (BS) are deployed to provide necessary services (uplink/downlink) to the BLE devices through the central office server as shown in Figure 7a , and the complete workflow is shown in Figure 7b . Figure 7a shows the coverage area of BLE and cell towers based on their transmitted power. The blue and green colored portion shows the energy region of BLE devices and cell towers, respectively. As can be seen, cell tower 0 transmits more power compared to cell tower 1. All the BLE devices are wearable or are attached to the employee working inside the mines. In this proposed method, beacons are considered because they can be easily identified by single board computers (SBC) as shown in Figure 8 . Different beacons are accessed by the nearest SBC based on their coverage area. The blue-colored region indicates the transmitted energy by the beacon signal as shown in Figure 8a . The system contains beacons that are small and inexpensive, which emit signals in the same fashion as BLE. The used beacons have a short-range and can triangulate position in the same way that a phone uses cell towers with an assisted global positioning system (AGPS). These transmitters are deployed at known points inside the mines, and they permit the device to obtain area fixes. This data can be utilized to make new client encounters, for example, turn-by-divert headings for indoor situating from gateways/applications that read the guide signals. Figure 7a shows the coverage area of BLE and cell towers based on their transmitted power. The blue and green colored portion shows the energy region of BLE devices and cell towers, respectively. As can be seen, cell tower 0 transmits more power compared to cell tower 1. All the BLE devices are wearable or are attached to the employee working inside the mines. In this proposed method, beacons are considered because they can be easily identified by single board computers (SBC) as shown in Figure 8 . Different beacons are accessed by the nearest SBC based on their coverage area. The blue-colored region indicates the transmitted energy by the beacon signal as shown in Figure 8a . The system contains beacons that are small and inexpensive, which emit signals in the same fashion as BLE. The used beacons have a short-range and can triangulate position in the same way that a phone uses cell towers with an assisted global positioning system (AGPS). These transmitters are deployed at known points inside the mines, and they permit the device to obtain area fixes. This data can be utilized to make new client encounters, for example, turn-by-divert headings for indoor situating from gateways/applications that read the guide signals. The scenario presented in Figure 8a ,b shows the position of the SBC (fixed position) and a random distribution of BLE devices, as the position of BLE device (wearable) depends on the position of the employee working inside the mine. The BLE receivers/gateway receives the universally unique identifier (UUID) transmitted by the beacons in a repetitive manner as shown in Figure 8a ,b. These signals can be utilized to differentiate between subgroups and individual ones in the subgroups. It is modified to check the accessible BLE signals "on the air" and the received signals contain the accompanying snippets of data in a bundle size of 60 bits, with 10 bits specifying major and minor values. The received signal strength indicator (RSSI) values can be utilized to decide the distance of the receiver to every one of the reference points. As those region statistics are stored inside the database, navigation of the receiver also can be tracked, and alerts can be generated if certain rules are violated. All the beacon data are stored in a local server through the gateway and then transferred to the central office server through cell towers as shown in Figure 8a ,b. The central office server is continuously updated based on the real-time information sent by the BLE beacon through the gateway. This information can be used to find the real-time location of the employees/workers inside the mines. The scenario presented in Figure 8a ,b shows the position of the SBC (fixed position) and a random distribution of BLE devices, as the position of BLE device (wearable) depends on the position of the employee working inside the mine. The BLE receivers/gateway receives the universally unique identifier (UUID) transmitted by the beacons in a repetitive manner as shown in Figure 8a ,b. These signals can be utilized to differentiate between subgroups and individual ones in the subgroups. It is modified to check the accessible BLE signals "on the air" and the received signals contain the accompanying snippets of data in a bundle size of 60 bits, with 10 bits specifying major and minor values. The received signal strength indicator (RSSI) values can be utilized to decide the distance of the receiver to every one of the reference points. As those region statistics are stored inside the database, navigation of the receiver also can be tracked, and alerts can be generated if certain rules are violated. All the beacon data are stored in a local server through the gateway and then transferred to the central office server through cell towers as shown in Figure 8a ,b. The central office server is continuously updated based on the real-time information sent by the BLE beacon through the gateway. This information can be used to find the real-time location of the employees/workers inside the mines. The simulation result in Figure 9 shows the discovery time of the BLE devices. It can be seen that the visibility time of the BLE device is constant, and the delay time is also very small. Hence, it helps to find the real-time location of the employees/workers inside the mines within a short time. Due to the small visibility time, the rescue process can be improved for the employees/workers (real-time locations) inside the underground mines during any hazardous situation. The simulation result in Figure 9 shows the discovery time of the BLE devices. It can be seen that the visibility time of the BLE device is constant, and the delay time is also very small. Hence, it helps to find the real-time location of the employees/workers inside the mines within a short time. Due to the small visibility time, the rescue process can be improved for the employees/workers (real-time locations) inside the underground mines during any hazardous situation. This paper summarizes and relates the future direction of IoT applications to current 6G trends, development sand challenges. The study looked at the vision and different technologies impacting the IoT as outcomes of international research. The paper considered the applications in various sectors and provided a summary of the different IoT technologies. The various IoT connectivity standards and a few challenges remaining open for IoT integration with cellular systems were outlined. The IoT is a basic building block for next-generation industrial standard 4.0/5.0 smart applications in home, city, agriculture, healthcare and many more uses, but this requires a major upgrade of the physical and network layers of upcoming cellular wireless networks. In this paper, a brief comparison between 5G and 6G was presented in terms of the technical features. The vision and key features of 6G along with the implementation challenges were discussed. This paper also includes a case study related to the real-time application of the IoT to locate the employees in underground mines using BLE technology. The system architecture and workflow for the given application were presented. This article might assist the researcher apprehend various challenges with their applications of the IoT and 6G to the real world. Author Contributions: S.K.P.: concept and setup preparation, design of system model; S.R.S.: concept, methodology creation, model selection, analysis and simulations supervision, text editing; S.B.: text and plot preparation, design of system model supervision, simulations and review; K.S. and S.C.: setup preparation, design of system model supervision, data preparation and text editing; J.K.D. and A.M.: methodology validation, model validation, setup preparation and data preparation, V.P.: overview of model validation, final model preparation, data preparation supervision, text editing and review. All authors have read and agreed to the published version of the manuscript. This paper summarizes and relates the future direction of IoT applications to current 6G trends, development sand challenges. The study looked at the vision and different technologies impacting the IoT as outcomes of international research. The paper considered the applications in various sectors and provided a summary of the different IoT technologies. The various IoT connectivity standards and a few challenges remaining open for IoT integration with cellular systems were outlined. The IoT is a basic building block for next-generation industrial standard 4.0/5.0 smart applications in home, city, agriculture, healthcare and many more uses, but this requires a major upgrade of the physical and network layers of upcoming cellular wireless networks. In this paper, a brief comparison between 5G and 6G was presented in terms of the technical features. The vision and key features of 6G along with the implementation challenges were discussed. This paper also includes a case study related to the real-time application of the IoT to locate the employees in underground mines using BLE technology. The system architecture and workflow for the given application were presented. This article might assist the researcher apprehend various challenges with their applications of the IoT and 6G to the real world. Author Contributions: S.K.P.: concept and setup preparation, design of system model; S.R.S.: concept, methodology creation, model selection, analysis and simulations supervision, text editing; S.B.: text and plot preparation, design of system model supervision, simulations and review; K.S. and S.C.: setup preparation, design of system model supervision, data preparation and text editing; J.K.D. and A.M.: methodology validation, model validation, setup preparation and data preparation, V.P.: overview of model validation, final model preparation, data preparation supervision, text editing and review. All authors have read and agreed to the published version of the manuscript. 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The authors declare no conflict of interest.Sensors 2022, 22, 3438