2 research outputs found

    Software to Assist Visually Impaired People During the Craps Game Using Machine Learning on Python Platform

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    Pattern recognition is a prominent area of research in computer vision, where different methods have been proposed in the last 50 years. This work presents the development of a Python API to identify the result of two six-sided dice used in the game called “Craps” as a no-controlled environment to help visually impaired people. The software is structured in four stages. The first one is capturing images through a device with a digital camera connected to the web via IP address. The second stage corresponds to the captured image processing; it is necessary to establish a standard image size and resize and equalize the digitized image. The third stage seeks to segment the object of study by artificial vision techniques to identify the result of the dice after being thrown. Finally, the fourth stage is to interpret the result and play it through a speaker. The expected possible result is a system that integrates the four stages mentioned above through an intuitive and accessible low-cost Python API, mainly aimed at visually impaired people

    The Potential of Electrospinning to Enable the Realization of Energy-Autonomous Wearable Sensing Systems

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    The market for wearable electronic devices is experiencing significant growth and increasing potential for the future. Researchers worldwide are actively working to improve these devices, particularly in developing wearable electronics with balanced functionality and wearability for commercialization. Electrospinning, a technology that creates nano/microfiber-based membranes with high surface area, porosity, and favorable mechanical properties for human in vitro and in vivo applications using a broad range of materials, is proving to be a promising approach. Wearable electronic devices can use mechanical, thermal, evaporative and solar energy harvesting technologies to generate power for future energy needs, providing more options than traditional sources. This review offers a comprehensive analysis of how electrospinning technology can be used in energy-autonomous wearable wireless sensing systems. It provides an overview of the electrospinning technology, fundamental mechanisms, and applications in energy scavenging, human physiological signal sensing, energy storage, and antenna for data transmission. The review discusses combining wearable electronic technology and textile engineering to create superior wearable devices and increase future collaboration opportunities. Additionally, the challenges related to conducting appropriate testing for market-ready products using these devices are also discussed
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