Visible Light Communication (VLC) is a short-range optical wireless communication technology that has been gaining attention due to its potential to offload heavy data traffic from the congested radio wireless spectrum. At the same time, wireless communications are becoming crucial to smart manufacturing within the scope of Industry 4.0. Industry 4.0 is a developing trend of high-speed data exchange in automation for manufacturing technologies and is referred to as the fourth industrial revolution. This trend requires fast, reliable, low-latency, and cost-effective data transmissions with fast synchronizations to ensure smooth operations for various processes. VLC is capable of providing reliable, low-latency, and secure connections that do not penetrate walls and is immune to electromagnetic interference. As such, this paper aims to show the potential of VLC for industrial wireless applications by examining the latest research work in VLC systems. This work also highlights and classifies challenges that might arise with the applicability of VLC and visible light positioning (VLP) systems in these settings. Given the previous work performed in these areas, and the major ongoing experimental projects looking into the use of VLC systems for industrial applications, the use of VLC and VLP systems for industrial applications shows promising potential.

This review paper discusses the complete evolution of free-space optical (FSO) communication, also known as unguided optical communication (UOC) technologies, all the way back to ancient man’s fire to today’s machine-learning-supported UOC systems. The principles, significance, and developments that have happened over the past several decades, as well as installation methodologies, technological limitations, and today’s challenges of UOCs are presented. All the subsets of UOC: FSO communication, underwater optical wireless communication (UOWC), and visible light communication (VLC), with their technology/system developments, potential applications, and limitations are reviewed. The state-of-the-art developments/achievements in (i) FSO channel effects and their mitigation techniques; (ii) radio-over-FSO techniques; (iii) wavelength division multiplexing and sub-carrier multiplexing techniques; (iv) FSO for worldwide interoperability for microwave access applications; (v) space optical satellite communication (SOSC); (vi) UWOC; (vii) photoacoustic communication (PAC); (viii) light-fidelity; (ix) VLC; (x) vehicular VLC (V²LC); and (xi) optical camera communication are reviewed. In addition, the current developments on emerging technologies such as artificial intelligence (to improve the performance of UOC systems), energy harvesting (for the effective utilization of UOC channels), and near-future communication network scenarios (mandatory for secured broadband digital links) are covered. Finally, in brief, to achieve the full potential of UOC systems, challenges that require immediate research attention are summarized.

Despite modern vehicles having the necessary advanced driver assistance systems (ADAS) for autonomous operation, current implementations rely solely on sensor information from the surrounding environment or data from smart infrastructure. However, shortcomings in current implementations and standards around cost-effective variable latency and data rate have prevented widespread adoption of the technology to enable autonomous operation. This paper presents a proof-of-concept (PoC) reconfigurable design and performance of a hybrid high-ultra-high bands [i.e., millimetre-Wave (mmWave)-light fidelity (Li-Fi)] fifth generation (5G) architecture for autonomous vehicular communication applications. The hybrid multiple input multiple output (MIMO) system architecture design is mathematically modelled and presented. The reported prelim PoC validation focuses on the Li-Fi experiment and results. The proposed hybrid system’s effectiveness was evaluated using the open-source “Model-based Autonomous Traffic Simulation” (MOBATSim). The simulation results of a potential Li-Fi system and a PoC prototype are presented to demonstrate the role of the Li-Fi system in the proposed hybrid mmWave-Li-Fi 5G architecture. Three models of LED/lamp and two models of photodiode were simulated at three different vehicle speeds to ascertain the potential of the system. Promising results are reported at low speeds with received power values of up to -8.39 dBm and signal to noise ratios of up to 29.39 dB. Practical prototype simulations showed auspicious results including received power of -24.6 dBm to -34.12 dBm at the vehicle speeds of 10 MPH to 30 MPH respectively. The implemented PoC Li-Fi technology component has demonstrated the ability to transmit information with a theoretical output of 333 bits per second at 1.92 m, without the use of any high-power processors, components, and modulation techniques. The proposed system yields high data rates due to reconfigurable high bandwidth channels; many simultaneous multimedia mmWave-Li-Fi connections enabled due to spatial reuse with narrow beams; and easier mmWave-Li-Fi ultra-low latency support occasioned by smaller packet sizes. This holds a great promise for the hybrid 5G/6G mmWave-Li-Fi autonomous vehicular communication use case and/or applications.

Localization in hospitals can be valuable in improving different services in medical environments. In this sense, an accurate location system in this environment requires adequately enabling communication technology. However, widely adopted technologies such as Wireless Fidelity (WiFi), Bluetooth, and Radio Frequency Identification (RFID) are considered poorly suited to enable hospital localization due to their inherent drawbacks, including high implementation costs, poor signal strength, imprecise estimates, and potential interference with medical devices. The increasing expenses associated with the implementation and maintenance of these technologies, along with their limited accuracy in dynamic hospital environments, underscore the pressing need for alternative solutions. In this context, it becomes imperative to explore and present novel approaches that not only avoid these challenges but also offer more cost effective, accurate, and interference-resistant connectivity to achieve precise localization within the complex and sensitive hospital environment. In the quest to achieve adequate localization accuracy, this article strategically focuses on leveraging Visible Light Communication (VLC) as a fundamental technology to address the specific demands of hospital environments to achieve the precise localization and tracking of life-saving equipment. The proposed system leverages existing lighting infrastructure and utilizes three transmitting LEDs with different wavelengths. The Received Signal Strength (RSS) is used at the receiver, and a trilateration algorithm is employed to determine the distances between the receiver and each LED to achieve precise localization. The accuracy of the localization is further enhanced by integrating a trilateration algorithm with the sophisticated Particle Swarm Optimization (PSO) algorithm. The proposed method improves the localization accuracy, for example, at a height of 1 m, from a 11.7 cm error without PSO to 0.5 cm with the PSO algorithm. This enhanced accuracy is very important to meet the need for precise equipment location in dynamic and challenging hospital environments to meet the demand for life-saving equipment. Furthermore, the performance of the proposed localization algorithm is compared with conventional positioning methods, which denotes improvements in terms of the localization error and position estimation.

In this paper, a novel three-dimensional (3D) indoor visible light positioning (VLP) algorithm using the Cayley–Menger determinant (CMD) with a cost function is proposed and experimentally tested to track a drone for industrial applications. The proposed algorithm uses optical received signal strength (RSS) for estimating the drone’s 3D position without prior knowledge of its height. This reduces the need for additional height sensors used in some 3D VLP systems. The performance of the proposed algorithm in terms of positioning error is also compared with a linear least squares (LLS) trilateration algorithm, with and without tilting of the receiver and with multipath reflections. The simulation results show that the proposed algorithm is more accurate and outperforms the LLS algorithm by a median improvement of 21% and is also more robust to the effect of tilting, as well as in the presence of multipath reflections. Furthermore, the proposed algorithm has been experimentally tested and compared with the LLS algorithm in a VLP test bed measuring 4 × 4 × 4.1 m ${}^3$ . The experimental results show that the median errors for LLS are 11.4 cm, while the median errors for CMD are 10.5 cm, which results in an error decrease of 8% when CMD with a cost function is used.