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Architecture and Implementation of a Digital Platform for Precision Rangeland and Livestock Management
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/ecs2.2430openalex-snapshot
Innovation in rangeland monitoring: annual, 30 m, plant functional type percent cover maps for U.S. rangelands, 1984–2017
inferredcites →https://doi.org/10.1002/fee.2736openalex-snapshot
Fulfilling the promise of digital tools to build rangeland resilience
inferredcites →https://doi.org/10.1002/rse2.74openalex-snapshot
Terrestrial primary production for the conterminous United States derived from Landsat 30 m and MODIS 250 m
inferredcites →https://doi.org/10.1007/s10584-016-1834-7openalex-snapshot
Vulnerabilities of Southwestern U.S. Rangeland-based animal agriculture to climate change
inferredcites →https://doi.org/10.1016/j.atech.2024.100483openalex-snapshot
Enhancing precision agriculture: A comprehensive review of machine learning and AI vision applications in all-terrain vehicle for farm automation
inferredcites →https://doi.org/10.1016/j.atech.2025.101002openalex-snapshot
Integrating LoRaWAN sensor networks and machine learning models to classify beef cattle behavior on arid rangelands of the southwestern United States
inferredcites →https://doi.org/10.1016/j.comcom.2020.10.009openalex-snapshot
A study of LoRaWAN protocol performance for IoT applications in smart agriculture
inferredcites →https://doi.org/10.1016/j.comcom.2022.02.017openalex-snapshot
Discovery privacy threats via device de-anonymization in LoRaWAN
inferredcites →https://doi.org/10.1016/j.compag.2008.05.005openalex-snapshot
Is precision livestock farming an engineer's daydream or nightmare, an animal's friend or foe, and a farmer's panacea or pitfall?
inferredcites →https://doi.org/10.1016/j.iot.2023.101053openalex-snapshot
Current testing and performance evaluation methodologies of LoRa and LoRaWAN in IoT applications: Classification, issues, and future directives
inferredcites →https://doi.org/10.1016/j.rama.2021.04.003openalex-snapshot
Annual and 16-Day Rangeland Production Estimates for the Western United States
inferredcites →https://doi.org/10.1016/j.rse.2017.06.031openalex-snapshot
Google Earth Engine: Planetary-scale geospatial analysis for everyone
inferredcites →https://doi.org/10.1109/icc40277.2020.9149081openalex-snapshot
Coverage Scalability Analysis of Multi-Cell LoRa Networks
inferredcites →https://doi.org/10.1109/medcomnet52149.2021.9501247openalex-snapshot
Discovery privacy threats via device de-anonymization in LoRaWAN
inferredcites →https://doi.org/10.1109/syseng.2017.8088251openalex-snapshot
Choice of effective messaging protocols for IoT systems: MQTT, CoAP, AMQP and HTTP
inferredcites →https://doi.org/10.15232/aas.2023-02406openalex-snapshot
Deployment of a LoRa-WAN near-real-time precision ranching system on extensive desert rangelands: What we have learned*
inferredcites →https://doi.org/10.1890/140266openalex-snapshot
Climate‐change adaptation on rangelands: linking regional exposure with diverse adaptive capacity
inferredcites →https://doi.org/10.2135/cssaspecpub32.c5openalex-snapshot
Climate Forecasts: Emerging Potential to Reduce Dryland Farmers' Risks
inferredcites →https://doi.org/10.23919/eusipco.2017.8081678openalex-snapshot
Collision and packet loss analysis in a LoRaWAN network
inferredcites →https://doi.org/10.25080/majora-92bf1922-00aopenalex-snapshot
Data Structures for Statistical Computing in Python
inferredcites →https://doi.org/10.3389/fsufs.2021.611915openalex-snapshot
Opportunities to Apply Precision Livestock Management on Rangelands
inferredcites →https://doi.org/10.3390/agriculture15131434openalex-snapshot
A Two-Stage Machine Learning Approach for Calving Detection in Rangeland Cattle
inferredcites →https://doi.org/10.3390/agronomy11061227openalex-snapshot
Data-Driven Artificial Intelligence Applications for Sustainable Precision Agriculture
inferredcites →https://doi.org/10.3390/ani14091348openalex-snapshot
Stakeholder Perceptions of Animal Welfare as a Component of Sustainable Beef Programs in the United States—A Pilot Study
inferredcites →https://doi.org/10.3390/rs11121427openalex-snapshot
Rangeland Productivity Partitioned to Sub-Pixel Plant Functional Types
inferredcites →https://doi.org/10.3390/s22010273openalex-snapshot
Practical Experiences of a Smart Livestock Location Monitoring System Leveraging GNSS, LoRaWAN and Cloud Services
inferredcites →https://doi.org/10.48550/arxiv.1603.02754openalex-snapshot
XGBoost: A Scalable Tree Boosting System
inferredcites →https://doi.org/10.5555/1953048.2078195openalex-snapshot
Scikit-learn: Machine Learning in Python
What points at this work
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inferred← citeshttps://doi.org/10.3390/s26175387openalex-snapshot
Smart Animal Welfare: A Review of Sensing Technologies, Deployment Challenges, and AI-Driven Insights
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