A QR Code–Enabled Digital Framework for Zoological Specimen Management Using Information Systems Approach

Due to antiquated labelling methods, data silos, and manual workflows, zoological collections in zoos, natural history museums, and research institutes continue to struggle with specimen identification, tracking, and long-term maintenance. Conventional techniques, such as handwritten labels, barcodes, or basic RFID, have drawbacks such as low data capacity, deterioration of preservation fluids, and no real-time digital connection. An Intelligent QR Code–Enabled Framework (IQRF) is proposed in this research to facilitate the digital identification and management of zoological specimens by combining high-capacity QR codes with cloud computing, mobile applications, and artificial intelligence (AI). Using Darwin Core standards, the framework creates long-lasting labels with QR codes that are connected to a centralized cloud database. Instant scanning, computer vision-based AI-driven species verification, automated metadata updates, and IoT integration for storage condition monitoring are all made possible by an intelligent mobile app. Blockchain-secured provenance improves research accessibility, reduces misidentification mistakes by 98%, and speeds up inventory procedures by 95%, according to pilot simulations. Building on the use of QR codes in biological collections, IQRF offers new AI analytics for worldwide data exchange and predictive conservation. By guaranteeing preservation, accessibility, and scientific value in the digital age, this framework transforms the management of zoological specimens.