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Plastic optical fibers (POF) possess the potential to occupy a distinctive role in contemporary communication systems, bridging the gap between the attributes of copper cable and glass fiber. POF stands out as a more lightweight and cost-effective alternative to glass fiber, while concurrently offering significantly enhanced communication bandwidth compared to traditional copper cables of equivalent cost or weight. However, the novelty of this technology introduces a challenge, as there is limited understanding of how POF cables may behave under specific bending conditions, particularly in the case of the latest multi-core fibers. This paper outlines a research endeavor aimed at establishing a cost-effective and reproducible testing framework for assessing the light transmission properties of plastic optical fibers during various bending conditions. The methodology involves partial automation using National Instruments LabVIEW for servo motor control, and optical power measurements were taken using the Thorlabs PM100USB. The investigation encompassed measurements across diverse bending angles and radii for five distinct types of fibers: Eska MH, Eska BH, Eska GH, a Graded Index fiber, and a Multi Core Fiber. 

This study investigates the impact of under-filled and over-filled launching configurations on the transmission properties of Plastic Optical Fiber (POF). Experimental analyses on step and graded index fibers reveal differences in spatial and frequency properties under these launching conditions. Results show that the under-filled configuration leads to narrower radial profiles and Encircled Angular Flux (EAF) compared to the over-filled configuration. Additionally, under-filled launching produces better frequency response and larger bandwidth, particularly notable in shorter fibers. Results show that the under-filled launching significantly improves transmission properties, offering potential improvements in POF applications. 

We proposed a Client Server Based Plastic Fiber Optic Network for an Elderly Support system in a smart home environment. The network will incorporate multimodal dialogue systems (MDS) and Artificial Intelligence (AI) systems. Existing AI models like GPT and Vicuna will be used and further trained to support the elderly in a smart home. The MDS systems, Whisper and Lavis, will act as intermediaries between the POF network of sensors and the AI systems. The systems will convert video and audio files into information that the AI systems can process and respond to. The POF network, consisting of sensors and a client-server architecture, will serve as the system's backbone. Its primary purpose is to gather data for the AI system and act based on its output. This research aims to enhance the safety, well-being, and independence of the elderly by leveraging advanced network technologies.