Automated Biological Analysis System: Integration of Chatbots and Edge Computing - Soto-Gomez, J; Garcia-Mena, V (Institute of Electrical and Electronics Engineers Inc., 2024)
This article presents an automated system for counting and analyzing biological samples, integrating edge computing, computer vision, and Natural Language Processing (NLP) through a chatbot interface. The system processes biological samples locally using advanced image processing techniques, reducing latency and improving the accuracy of results. Additionally, the system allows for remote user interaction via a natural language interface and stores spatiotemporal data in the cloud for enhanced management. The system achieves a 6 5 % success rate in Colony-forming unit (CFU) detection and 85% in RFID/QR label recognition, with identified areas for improvement in image quality and standardization. © 2024 IEEE.