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The aging and deterioration of engineering building structures present significant risks to both life and property. Fiber Bragg grating (FBG) sensors, acclaimed for their outstanding reusability, compact form factor, lightweight construction, heightened sensitivity, immunity to electromagnetic interference and exceptional precision, are increasingly being adopted for structural health monitoring in engineering buildings. This research paper aims to evaluate the current challenges faced by FBG sensors in the engineering building industry. It also anticipates future advancements and trends in their development within this field.

This study centers on five pivotal sectors within the field of structural engineering: bridges, tunnels, pipelines, highways and housing construction. The research delves into the challenges encountered and synthesizes the prospective advancements in each of these areas.

The exceptional performance of FBG sensors provides an ideal solution for comprehensive monitoring of potential structural damages, deformations and settlements in engineering buildings. However, FBG sensors are challenged by issues such as limited monitoring accuracy, underdeveloped packaging techniques, intricate and time-intensive embedding processes, low survival rates and an indeterminate lifespan.

This introduces an entirely novel perspective. Addressing the current limitations of FBG sensors, this paper envisions their future evolution. FBG sensors are anticipated to advance into sophisticated multi-layer fiber optic sensing networks, each layer encompassing numerous channels. Data integration technologies will consolidate the acquired information, while big data analytics will identify intricate correlations within the datasets. Concurrently, the combination of finite element modeling and neural networks will enable a comprehensive simulation of the adaptability and longevity of FBG sensors in their operational environments.

In recent years, the global focus has increasingly shifted toward the adoption of electric vehicles (EVs) due to growing concerns about environmental sustainability and the imperative of reducing greenhouse gas emissions. The transportation sector, a significant contributor to air pollution and climate change, faces increasing pressure to embrace EVs as a solution. However, the resistance exhibited by customers toward adopting new technology poses a substantial obstacle to the widespread adoption of EVs. Drawing on the link between theory of reasoned action (TRA) and self-congruity theory, this research aims to determine the factors that affect the customer intention toward EV.

The research conducts a questionnaire collecting 950 respondents from the Egyptian market. The research used primary quantitative data from online and self-administered questionnaires.

The findings indicated that green trust, price sensitivity and reliability have a positive impact on customer’s intention. However, self-image congruence was not affecting customer intention. For the moderating role of financial self-efficacy, it is affecting the relationship between price sensitivity and customer’s purchase intentions toward EV.

This research will expand the theory by conceptualizing its abstract notions through research variables and implementing them in the Egyptian market. Furthermore, it links the two distinct theories. This knowledge can be utilized by policymakers and stakeholders to expedite the adoption of EVs in the Egyptian market.

This study presents a conceptual framework for managers and policymakers about the factors that affect the customer to buy EVs, since the international organizations emphasize eco-friendly transportation systems.