This paper illuminates the scientific footsteps of the Short-Wave Infrared (SWIR) detectors, tracing the journey of the growth and development in this critical technology area from its early days in 1969 to its swift ascent in 2023. Employing bibliometric information and VOSviewer examination, we unveil major tendencies, thematic clusters, and the dynamic swelling of the scientific publications, spotlighting the burgeoning interest and technological evolution of SWIR detectors. Our research pieces together the key stages of SWIR technology emergence, originating from the initial revelations, advances in material science and also expansion of application spheres from military surveillance to environmental monitoring and medical imaging. Thus, we shed a light on the tremendous sway of SWIR detectors on the optical engineering and also photonics, attributable to their distinct capabilities to resolve current challenges. The findings throw a lot of light on the maturation within the SWIR detector research, underlining its heightening significance in both scientific and also industrial applications. This paper is a very comprehensive overview of the SWIR detector landscape that elaborates the successes of the past and also the trajectory of the future for the researchers, practitioners, and policymakers journeying in this transformative field.
This paper investigates the integration of Kalman Filter technologies into modern agricultural practices, with a focus on advancing crop monitoring techniques. Through a comprehensive bibliometric and text mining analysis, we explore the evolution of research in this area from 1983 to 2023, highlighting the steady growth in scholarly publications and the interdisciplinary nature of the field. Our findings reveal a significant interest in leveraging Kalman Filter algorithms to enhance the precision and efficiency of agricultural operations, addressing the challenges of sustainability and food security. The study underscores the importance of data assimilation, real-time monitoring, and predictive analysis in agriculture, facilitated by the adoption of Kalman Filter and its variants. We also examine the integration of emerging technologies, such as Unmanned Aerial Vehicles (UAVs) and remote sensing, with Kalman Filter techniques to develop sophisticated agricultural monitoring systems. The paper concludes with insights into future research directions, emphasizing the need for overcoming barriers to technology adoption and fostering interdisciplinary collaborations. This work contributes to the understanding of how computational intelligence can transform agricultural practices, offering solutions for more sustainable and efficient farming.
This research plunges into the rapidly growing radar technology in the medical sector, putting emphasis on its possibility to revolutionize elderly care and health monitoring among the aging global population. Based on a systematic literature review and rigorous bibliometric analysis, we discuss radar technology application in healthcare, focusing on its potential for non-invasive, high-accuracy diagnosis and continuous patient monitoring. Our findings highlight the critical harmony between radar technology and the advances in machine learning, artificial intelligence, and data analytics, which open the door to smart healthcare solutions. These advancements will improve early disease detection, fall risk prevention, and real-time health monitoring, resulting in quick medical responses. This study endeavors to offer useful knowledge to researchers, practitioners, and policymakers who are working towards the use of technology for better health in the context of the demographic changes that the world is experiencing in terms of an ageing population by mapping the current research landscape, identifying the existing trends and gaps, and proposing the future direction of research.
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