Aircraft operators are faced with increasing requirements to extend the service life of air platforms beyond their designed life cycles, resulting in heavy maintenance and inspection burdens as well as economic pressure. Structural health monitoring (SHM) based on advanced sensor technology is potentially a cost-effective approach to meet operational requirements, and to reduce maintenance costs. Fiber optic sensor technology is being developed to provide existing and future aircrafts with SHM capability due to its unique superior characteristics. This review paper covers the aerospace SHM requirements and an overview of the fiber optic sensor technologies. In particular, fiber Bragg grating (FBG) sensor technology is evaluated as the most promising tool for load monitoring and damage detection, the two critical SHM aspects of air platforms. At last, recommendations on the implementation and integration of FBG sensors into an SHM system are provided.

The rapid change of climate, population explosion, and reduction of arable lands are calling for new approaches to ensure sustainable agriculture and food supply for the future. Greenhouse agriculture is considered to be a viable alternative and sustainable solution, which can combat the future food crisis by controlling the local environment and growing crops all year round even in harsh outdoor conditions. However, greenhouse farms persist many challenges for efficient operation and management. The evolving Internet of Things (IoT) technologies, which encompass the smart sensors, devices, network topologies, big data analytics, and intelligent decision, is believed to be the solution in addressing the key challenges facing the greenhouse farming, such as greenhouse local climate control, crop growth monitoring, crop harvesting and etc. This paper reviews the current greenhouse cultivation technologies as well as the stateof-the-art of IoT technologies for smart greenhouse farms. The paper also highlights the major challenges that need to be addressed.

Lithium (Li) dendrite growth significantly deteriorates the performance and shortens the operation life of lithium metal batteries. Capturing the intricate dynamics of surface localized and rapid mass transport at the electrolyte–electrode interface of lithium metal is essential for the understanding of the dendrite growth process, and the evaluation of the solutions mitigating the dendrite growth issue. Here we demonstrate an approach based on an ultrasensitive tilted fiber Bragg grating (TFBG) sensor which is inserted close to the electrode surface in a working lithium metal battery, without disturbing its operation. Thanks to the superfine optical resonances of the TFBG, in situ and rapid monitoring of mass transport kinetics and lithium dendrite growth at the nanoscale interface of lithium anodes have been achieved. Reliable correlations between the performance of different natural/artificial solid electrolyte interphases (SEIs) and the time-resolved optical responses have been observed and quantified, enabling us to link the nanoscale ion and SEI behavior with the macroscopic battery performance. This new operando tool will provide additional capabilities for parametrization of the batteries’ electrochemistry and help identify the optimal interphases of lithium metal batteries to enhance battery performance and its safety.

Agriculture production is one of the fundamental contributors to a nation's economic development. Every year, plant diseases result in significant crop losses that threaten the global food supply chain. Early estimation of plant diseases could play an essential role in safeguarding crops and fostering economic growth. Recently, hyperspectral imaging techniques have emerged as powerful tools for early disease detection, as they have demonstrated capabilities to detect plant diseases from tissue to canopy levels. This article provides an extensive overview of the principles, types, and operating platforms of hyperspectral image sensors. Furthermore, this article delves into the specifics of these sensors' application in plant disease detection, including disease identification, classification, severity analysis, and understanding genetic resistance. In addition, this article addresses the current challenges in the field and suggests potential solutions to mitigate these pressing issues. Finally, this article outlines the promising future trends and directions of hyperspectral imaging in plant disease detection and analysis. With continuous improvement and application, these imaging techniques have great potential to revolutionize plant disease management, thereby enhancing agricultural productivity and ensuring food security.

We evaluate a wavelength interrogation technique based on an arrayed waveguide grating (AWG). Initial results show that the Bragg wavelength of fiber Bragg grating (FBG) sensors can be precisely interrogated by thermally scanning an AWG-based demultiplexer. The technique potentially offers a low-cost, compact, and high-performance solution for the interrogation of FBG distributed sensors and multisensor arrays.

In the rapidly evolving landscape of Industry 4.0, digital twins have emerged as a transformative technology across various industrial sectors. This paper presents a comprehensive, in-depth review of digital twin models in terms of the concept and evolution, fundamental components and frameworks, and existing digital twin models based on their functionalities. The paper also discusses how the existing digital twin models are used/adopted in different industries and highlights the existing challenges and potential solutions to address the current issues. This paper aims to provide researchers and industry professionals with a clear insight into the unique benefits and applications of different digital twin models. This review will help to comprehend their significance for specific industrial purposes and foster the advancement of state-of-the-art techniques in this field.