Real-time, dynamic, and visual monitoring of underwater scenes would become an important research topic with the development of underwater wireless optical communication (UWOC), autonomous underwater vehicle, and video fusion technologies. To this end, we developed a UWOC-based 2K real-time digital video surveillance prototype named AquaF-seer. Using a light-emitting diode and an avalanche photodetector based diffused line-of-sight UWOC system, real-time video transmission with a high resolution of 1920 × 1080 pixels is achieved over various channels, i.e., 1.5-m free space channel, pure water channel, pure water channel with 1.53-mL/s bubble-induced turbulence, pure water channel with 42.40-mL/s bubble-induced turbulence, simulated pure sea water channel, and coastal ocean water channel. Moreover, 46-m and 5-m video monitoring are implemented in free space and an outdoor diving pool. It indicates the reliability of the prototype, which is the first step to realize underwater visual monitoring in future human-robot interaction applications.

Red palm weevil (RPW) is a harmful pest that destroys many date, coconut, and oil palm plantations worldwide. It is not difficult to apply curative methods to trees infested with RPW; however, the early detection of RPW remains a major challenge, especially on large farms. In a controlled environment and an outdoor farm, we report on the integration of optical fiber distributed acoustic sensing (DAS) and machine learning (ML) for the early detection of true weevil larvae less than three weeks old. Specifically, temporal and spectral data recorded with the DAS system and processed by applying a 100–800 Hz filter are used to train convolutional neural network (CNN) models, which distinguish between “infested” and “healthy” signals with a classification accuracy of ∼97%. In addition, a strict ML-based classification approach is introduced to improve the false alarm performance metric of the system by ∼20%. In a controlled environment experiment, we find that the highest infestation alarm count of infested and healthy trees to be 1131 and 22, respectively, highlighting our system’s ability to distinguish between the infested and healthy trees. On an outdoor farm, in contrast, the acoustic noise produced by wind is a major source of false alarm generation in our system. The best performance of our sensor is obtained when wind speeds are less than 9 mph. In a representative experiment, when wind speeds are less than 9 mph outdoor, the highest infestation alarm count of infested and healthy trees are recorded to be 1622 and 94, respectively.

Our Earth is a “blue planet” that 70 $\%$ of the surface is covered by the oceans, but most area of oceans remain largely unexplored. Besides supporting the Earth's ecosystem and moderating climate change, oceans are rich in economically relevant natural resources ready for harvesting, such as fishery, oil and gas, and mineral resources. Ocean observation and monitoring are therefore essential for environmental preservation and sea exploration. With the availability of advanced communication techniques, researchers began to look into distributed data acquisition and ocean interconnectivity, which engendered the concepts of intelligent ocean and the Internet-of-Underwater-Things (IoUT) framework. The framework is gaining traction since one could incorporate fiber sensing, acoustic, radio frequency, and optical wireless communication technologies to establish stable, broad-coverage, and massive ocean networks. The development of underwater internet beyond acoustic communication is still in its relative infancy, and therefore more aggregated research efforts from the related communities will be required to eventually achieve breakthroughs in comprehensive IoUT technologies. This review sheds light on the practical considerations and solutions to the challenges and robustness of the optical IoUT network in terms of channel characterization, turbulence studies, mobility, receiver optimization, and the application layer.

The CLP Publishing collects CLP journals and partnered optics and photonics journals, and provides readers an optical publishing platform with global influence. SPIE, OSA, CUP. Chinese Laser Press (CLP), established by Shanghai Institute of Optics and Fine Mechanics (SIOM), Chinese Academy of Sciences (CAS) and Chinese Optical Society (COS) in 2009, nowadays publishes eight journals and manages three online platforms.

The misalignment of mobile underwater wireless optical communication (UWOC) systems, compounded by misalignment in underwater mobility scenarios, is a practical problem that can be resolved through various means. This work describes a pulse-position modulation (PPM) based diffused-line-of-sight UWOC system that offers a solution to this issue. PPM is found to be power-efficient and, in terms of bit error ratio performances, outperforms on-off keying modulation and orthogonal frequency-division multiplexing modulation in complex dynamic underwater channels. Through indoor experiments and an outdoor deployment, herein, we validated the robustness of our PPM-based mobile UWOC system. This work is expected to shed light on practical implementation of UWOC network for relieving the strict positioning-acquisition-and-tracking requirements when underwater apparatus is transmitting or receiving signals on-the-fly.

Automatic subsea operations using real-time underwater optical wireless sensor networks are mooted as a new paradigm of underwater Internet of Things in this paper. To this end, we develop an underwater optical wireless sensor network prototype called AquaE-net, which consists of an optical hub and two sensor nodes with temperature, salinity, conductivity, and pH sensing capabilities. Clock synchronization is realized in AquaE-net, which paves the way for future underwater positioning and navigation. Moreover, real-time and bi-directional network communication with 100% packet success rates has been realized by AquaE-net in free space and turbid water in the harbor of the Red Sea at King Abdullah University of Science and Technology. This is the first step toward future effective marine environmental monitoring and marine resources exploration.