@article{4062,
  author = {Nicolás E. Caytuiro-Silva, Eveling G. Castro-Gutierrez and Jackeline M. Peña-Alejandro},
  title = {Using IoT and Computer Vision to Improve Visual  Impairment},
  journal = {Journal of Information Organization},
  year = {2024},
  volume = {14},
  number = {2},
  doi = {https://doi.org/10.6025/jio/2024/14/2/80-88},
  url = {https://www.dline.info/jio/fulltext/v14n2/jiov14n2_2.pdf},
  abstract = {The objective of this research is to address the challenges faced by individuals with visual impairments when attempting to distinguish among various banknote denominations within the city of Arequipa. It proposes the development of a device that combines computer vision and IoT technology to aid these individuals in identifying the values of different banknotes and objects in their vicinity. This study reviews the latest developments in the field of banknote recognition and object detection, both on a worldwide and local scale, highlighting recent progress in machine learning and computer vision. The research methodology is based on Design Thinking, which encompasses problem understanding (empathy), precise problem definition, idea generation, prototype creation, and effectiveness assessment. The strategy outlines the process for building a banknote image database and incorporating a real-time vision feature into the device. Although testing with the intended users has not yet been carried out, initial findings have been collected to identify areas that require improvement in banknote recognition and object detection. The ultimate aim of this study is to significantly improve the everyday lives of visually impaired individuals in Arequipa by developing a device that simplifies the task of identifying banknotes and objects, offering a ray of hope and optimism for a more inclusive future, utilizing a cost-effective solution that combines computer vision and IoT technology.
},
}