KEYWORDS: Acoustics, Single mode fibers, Signal to noise ratio, Sensors, Optical sensing, Optical amplifiers, Machine learning, Data modeling, Continuous wave operation, Signal detection
Red palm weevil (RPW) is a harmful pest that has wiped out many palm plantations worldwide. Early detection of RPW is difficult, especially on large plantations. Here, we report on combining fiber–optic distributed acoustic sensing (DAS) and machine learning to detect weevil larvae less than three weeks old, in a controlled environment. In particular, we use the temporal and spectral data provided by a fiber–optic DAS system to train a convolutional neural network (CNN), which distinguishes “healthy” and “infested” signals with a classification accuracy higher than 97%. Additionally, a rigorous machine learning classification approach is introduced to improve the false alarm performance metric by >20%.
The underwater wireless optical communication (UWOC) technology is vastly developing due to its advantages of high bandwidth, large capacity, and low latency. However, the complex underwater channel characteristics and strict requirements on pointing, acquisition, and tracking (PAT) systems hinder the performance and augmentation of UWOC. A large-area scintillating-fiber-based UWOC system is proposed to solve the PAT issue while offering high-speed, omnidirectional data detection over turbulent underwater channels. In this work, we utilized 120-cm2 coverage area scintillating fibers as a photoreceiver. The large area scintillating fibers realize omnidirectional signal detection by absorbing an incident optical radiation, re-emitting it at a longer wavelength, and then guided to the end of the fibers connected with an avalanche photodetector. The UWOC system offers a 3-dB bandwidth of 66.62 MHz, and a 250 Mbit/s data rate is achieved using non-return-to-zero on-off keying (NRZ-OOK) modulation. The system was tested over a 1.5-m underwater channel under turbulences of air bubbles, temperature, salinity, and turbidity. We generated bubbles by blowing 0.20, 0.63, and 1.98 mL/s speeds of Nitrogen gas flow. A temperature gradient of 1.33 and 2.67 Celsius/m was introduced by circulating warm and cold water at the two tank ends, respectively. Salinity concentrations at 35 and 40 ppt were introduced to emulate the salinity in the Red Sea. Lastly, different volumes of MaaloxTM were added into pure water to emulate pure sea, coastal ocean, and turbid harbor water. The fiber-based UWOC system operates under those turbulence conditions with error-free communication and 0% outage probability.
With the growing number of underwater vehicles and devices used for marine environmental monitoring, there is an urgent need for real-time and high-speed underwater wireless communication technologies to transmit huge amounts of data. This poses great challenges to conventional underwater acoustic communication technology due to its low bandwidth and high latency. Therefore, underwater wireless optical communication with high bandwidth and low latency has become a promising technology. To this end, we develop the first underwater optical wireless sensor network prototype in this work. It consists of two sensor nodes and an optical hub. There is a transceiver circuit, a pH sensor, and an integrated temperature, salinity, and conductivity sensor in the sensor nodes enabling real-time underwater environmental monitoring. There are four transceivers facing four sides in the optical hub to implement bi-directional optical wireless communication with the sensor nodes. In a laboratory testbed and a field trial conducted in an outdoor diving pool, 100% packet success rates are achieved between the optical hub and the sensor nodes at a transmission distance of 60 cm. In the field trial, one of the sensor nodes is placed 60 cm away from the optical hub for real-time underwater environmental monitoring. The other sensor node is mounted on a remotely operated vehicle to collect underwater environmental information. This prototype shows great potential in future underwater mobile sensor networks and the underwater Internet of Things.
Relaxing the alignment in underwater wireless optical communication systems is highly favorable for practical use. Employing wavelength-division-multiplexing (WDM) adds to the requirement of alignment since multiple filters are used at the receiver side to separate the incoming wavelengths. We report the use of scintillating fibers in WDM systems as signal detectors that offer valuable advantages such as large-area detection, widefield- of-view and high data rates. We demonstrate the optimal selection of wavelengths based on the fibers’ characteristics, and realise an aggregated data rate of 400-Mb/s using on-off keying modulation format with zero-forcing equalization and maximum ratio combining in an outdoor diving pool in a maximum separation distance of 10-m.
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