Título:	Digital livestock management solution for cattle identification, traceability, and real-time monitoring, IoT-based for integrated croplivestock-forest (ICLF) systems.
Autoria:	BERNARDI, A. C. de C. GARCIA, A. R. GUIMARAES, E. da S. TONATO, F. MEDEIROS, S. R. de BARIONI JUNIOR, W. PORTUGAL, J. A. B. ALVES, T. C. CAVALCANTE, W. P. SERÃO FILHO, M. GAIOLLI JÚNIOR, C.
Afiliação:	ALBERTO CARLOS DE CAMPOS BERNARDI, CPPSE; ALEXANDRE ROSSETTO GARCIA, CPPSE; EDILSON DA SILVA GUIMARAES, CPPSE; FELIPE TONATO, CPPSE; SERGIO RAPOSO DE MEDEIROS, CPPSE; WALDOMIRO BARIONI JUNIOR, CPPSE; JOSE ALBERTO BASTOS PORTUGAL, CPPSE; TERESA CRISTINA ALVES, CPPSE; WERTER PADILHA CAVALCANTE, TAGGEN INDUSTRIES; MAURO SERÃO FILHO, TAGGEN INDUSTRIES; CLAUDINEI GAIOLLI JÚNIOR, TAGGEN INDUSTRIES.
Ano de publicação:	2026
Referência:	In: INTERNATIONAL CONFERENCE ON PRECISION AGRICULTURE, 17., CONGRESSO BRASILEIRO DE AGRICULTURA DE PRECISÃO DIGITAL, 11., 2026, Porto Alegre. Proceedings [...]. Monticello: International Society of Precision Agriculture and Brazilian Congress on Precision and Digital Agriculture., 2026.
Conteúdo:	Brazil is a global player in the beef industry with the world's largest commercial bovine herd, exceeding 230 million head, and leads the international market, accounting for approximately 25% of the global beef trade, reaching over 170 international markets. The edaphoclimatic diversity, high-performance genetics, rigorous sanitary protocols, and the adoption of a technological framework for tropical livestock, altogether, explain the decoupling of Brazilian ranching from extensive, low-productivity systems toward sustainable intensification. The increasing consumer demand for information on food quality, safety, and production conditions poses a challenge for livestock production, requiring greater control over animal production. Precision livestock farming (PLF) is a potential solution enabling continuous, real-time monitoring of animal health, welfare, and behavior. The "National Bovine Traceability Plan (PNIB)" aims to achieve animal traceability by electronic tags for an individual identification system to track history, location, and movement of the entire Brazilian herd by 2032, enhancing sanitary control and meeting international market demands. The transition toward a digitized livestock production system needs the deployment of a low-latency, cost-competitive cyber-physical architecture capable of autonomous individual identification, high-precision localization, and longitudinal behavioral monitoring. This research implements a scalable Digital Livestock Management Solution (DLMS) that utilizes a multi-layered communication protocol and was conducted at Embrapa Pecuaria Sudeste, São Carlos, SP, Brazil (21°57' S, 47°50' W, 860 m), in both beef and dairy systems. The system employs Taggen Beacon 5.1® (Taggen Industries, Campinas, SP, Brazil), a Bluetooth low energy (BLE) tag affixed to animal collars, with sensor nodes (Taggen Gateway® (Taggen Industries, Campinas, SP, Brazil)) cloud-connected via Long Term Evolution (LTE or 4G) or Wi-Fi. Data is integrated into the TG-AGRO® platform, a cloud-based management architecture for real-time access across portable devices (smartphones or tablets). The system operates as follows: the beacon module periodically broadcasts BLE advertising packets that include unique identifiers and telemetry data. The gateway performs active scanning, acquires Received Signal Strength Indicator (RSSI) metrics, and appends temporal metadata (timestamp). In beacon-equipped GNSS (Global Navigation Satellite System) configurations, the gateway correlates these packets with spatial coordinates. DLMS's multi-source power system allows autonomous operation via solar energy, grid connections, or integration with mobile agricultural equipment. For a reliable telemetry transmission over 350 m, the system uses a motion-aware RSSI smoothing algorithm (Log-Distance Path Loss Model) to mitigate multipath fading. The system is fully interoperable with legacy LF and HF-RFID protocols to ensure backward compatibility with the Brazilian Sisbov framework. Evaluation parameters included daily detection rates, report density, and message latency. Field results demonstrated a daily detection rate exceeding 98.5% of the herd, with gateways processing over 500 tags per minute in highdensity areas. The system optimizes power consumption by adapting transmission intervals (5 s to 15 min), ensuring data integrity and long-term tag durability in remote settings. The outcome demonstrates a reliable, compatible telemetry system that, despite the logistical limitations of remote settings, ensures data integrity and enables real-time decision-making. This architecture goes beyond limitations of conventional passive tracking by offering a dynamic framework for real-time spatiotemporal management across diverse livestock production systems. Additionally, information flow between on-farm operations and external regulatory or commercial stakeholders is facilitated by the incorporation of user-centric data visualization interfaces.
Thesagro:	Agricultura de Precisão Gado de Corte Identificação Rastreamento
NAL Thesaurus:	Precision agriculture Beef cattle Animal identification Traceability
Palavras-chave:	Internet of Things Internet das coisas IoT Bluetooth low energy
Notas:	ICPA 2026. ConBAP 2026.
Tipo do material:	Artigo em anais e proceedings
Acesso:	openAccess
Aparece nas coleções:	Artigo em anais de congresso (CPPSE)