| Summary: | Aims: Discuss a new strategies and technologies to increase the number of blood donors; use artificial intelligence and robotic process automation to reduce the number of hours spent on repetitive activities within blood donation; discuss the Fundação Hemominas case study. Materials and methods: The Fundação Hemominas donor co-capturing robot project aims to increase donor engagement, optimize resource management, and ultimately save lives by improving blood donation rates and ensuring a stable supply. The robot makes active contacts through robocall and chatbots, monitors blood stocks and it is capable of providing information on blood donation. Blood stocks are monitored, and based on demand needs, targets for attracting blood donors by the robot are calculated. This paper presents a case study conducted with an exploratory approach to investigate the impact of the donor captor robot, an innovative technology implemented in blood donation centers. The study employed participant observation as a primary data collection tool, complemented by documental analysis to gain insights into the robot's functionality, effectiveness, and overall impact on blood donation rates and resource management. The project's technological tools are: robotic process automation (RPA), deep learning (DL), voicebots and chatbots, robocalls, MGAPP app, website, and others. Discussion: Down here are the expected impact. Improving blood donation rates: the robot may effectively capture and engage potential donors. Through its automated capabilities, it can reach out to a larger audience, provide information, answer queries, and encourage individuals to schedule donation appointments. Efficient resource management: the robot is designed to optimize the allocation of resources within blood donation centers capabilities. By analyzing data on blood stocks, demand, and donor availability, it can strategically schedule appointments to match supply with demand. This ensures a more efficient use of resources, reduces wastage, and minimizes the risk of blood shortages. Technological advancement: the implementation of a donor captor robot represents a significant technological advancement to nonprofit blood banks. It combines artificial intelligence (AI), natural language processing (NLP), and automation to create a sophisticated and user-friendly robot. The integration of chatbots and voicebots allows for personalized interactions, efficient communication, and streamlined donor management. Data-driven decision making: the robot captures and analyzes a wealth of data related to donor behavior, appointment scheduling, and blood inventory. By harnessing this data, blood banks can gain valuable insights into donor preferences, trends, and challenges. This information can guide future strategies, enabling targeted campaigns, enhancing donor experiences, and fostering long-term donor engagement. The robot's data-driven approach empowers scientific research, decision-making in the field of blood transfusion and insights. Public awareness and engagement: the robot may contribute to raising public awareness about the importance of blood donation. Through its proactive outreach, it educates individuals about the impact of blood donation on saving lives and addresses common misconceptions. Conclusion: In summary, the robot may help the blood donation process, save lives, and inspire further advancements in AI and automation for the betterment of society.
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