A system for offline-capable, multimodal identification of farm animals and secure data management with health monitoring.

Abstract

A system for offline-capable, multimodal animal identification and secure data management, consisting of: one or more Internet of Things (IoT) collar devices configured for attachment to livestock. Each device incorporates a variety of physiological sensors and a Bluetooth Low Energy (BLE) communication interface configured to capture and transmit physiological parameters of the livestock via the Bluetooth Low Energy communication interface; a mobile computing device configured to receive multimodal livestock data from one or more IoT collar devices, the captured multimodal livestock data including images of the livestock, images of the muzzle pattern, acoustic vocalization samples, and GPS location data;an artificial intelligence processing module within the mobile computer device, configured to process the multimodal livestock data offline locally, identify breed characteristics of the livestock based on the multimodal livestock data and assess the health status of the livestock based on the multimodal livestock data and physiological parameters, generating a unique livestock identification number (ULID) for each individual animal;a blockchain-based distributed ledger within the mobile device, connected to artificial intelligence processing and configured to store the unique animal identification number, owner information and health data of each individual farm animal, and ensuring tamper-proof verification of the stored information, wherein the blockchain-based distributed ledger enables the creation of a digital twin profile for each individual farm animal, with this digital twin profile being dynamically updated based on incoming multimodal farm animal data and physiological parameters;and an analytics dashboard interface connected to the artificial intelligence module and a blockchain-based distributed ledger, configured to display predictive insights into the health, milk productivity, disease risk, and reproductive cycles of farm animals.