Automated Biological Analysis System: Integration of Chatbots and Edge Computing

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.