Jameson Brennan, I. Parsons, Meredith Harrison, H. Menendez
{"title":"Development of an Application Programming Interface (API) to automate downloading and processing of precision livestock data","authors":"Jameson Brennan, I. Parsons, Meredith Harrison, H. Menendez","doi":"10.1093/tas/txae092","DOIUrl":null,"url":null,"abstract":"\n Advancements in technology have ushered in a new era of sensor-based measurement and management of livestock production systems. These sensor-based technologies have the ability to automatically monitor feeding, growth, and enteric emissions for individual animals across confined and extensive production systems. One challenge with sensor-based technologies are the large amount of data generated, which can be difficult to access, process, visualize, and monitor information in real time to ensure equipment is working properly and animals are utilizing it correctly. A solution to this problem is the development of application programming interfaces (APIs) to automate downloading, visualizing, and summarizing datasets generated from precision livestock technology. For this methods paper, we develop three APIs and accompanying processes for rapid data acquisition, visualization, systems tracking, and summary statistics for three technologies (SmartScale™, SmartFeed™, and GreenFeed™) manufactured by C-Lock Inc (Rapid City, SD). Program R markdown documents and example datasets are provided to facilitate greater adoption of these techniques and to further advance precision livestock technology. The methodology presented successfully downloaded data from the cloud and generated a series of visualizations to conduct systems checks, animal usage rates, and calculate summary statistics. These tools will be essential for further adoption of precision technology. There is huge potential to further leverage APIs to incorporate a wide range of datasets such as weather data, animal locations, and sensor data to facilitate decision-making on times scales relevant to researchers and livestock managers.","PeriodicalId":23272,"journal":{"name":"Translational Animal Science","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational Animal Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/tas/txae092","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AGRICULTURE, DAIRY & ANIMAL SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Advancements in technology have ushered in a new era of sensor-based measurement and management of livestock production systems. These sensor-based technologies have the ability to automatically monitor feeding, growth, and enteric emissions for individual animals across confined and extensive production systems. One challenge with sensor-based technologies are the large amount of data generated, which can be difficult to access, process, visualize, and monitor information in real time to ensure equipment is working properly and animals are utilizing it correctly. A solution to this problem is the development of application programming interfaces (APIs) to automate downloading, visualizing, and summarizing datasets generated from precision livestock technology. For this methods paper, we develop three APIs and accompanying processes for rapid data acquisition, visualization, systems tracking, and summary statistics for three technologies (SmartScale™, SmartFeed™, and GreenFeed™) manufactured by C-Lock Inc (Rapid City, SD). Program R markdown documents and example datasets are provided to facilitate greater adoption of these techniques and to further advance precision livestock technology. The methodology presented successfully downloaded data from the cloud and generated a series of visualizations to conduct systems checks, animal usage rates, and calculate summary statistics. These tools will be essential for further adoption of precision technology. There is huge potential to further leverage APIs to incorporate a wide range of datasets such as weather data, animal locations, and sensor data to facilitate decision-making on times scales relevant to researchers and livestock managers.
技术的进步开创了以传感器为基础的畜牧生产系统测量和管理的新时代。这些基于传感器的技术能够自动监测封闭式和大规模生产系统中个体动物的采食、生长和肠道排放情况。基于传感器的技术面临的一个挑战是产生的大量数据难以实时访问、处理、可视化和监控信息,以确保设备正常工作和动物正确使用。解决这一问题的方法是开发应用编程接口 (API),以便自动下载、可视化和汇总精准畜牧技术生成的数据集。在这篇方法论文中,我们为 C-Lock 公司(Rapid City, SD)生产的三种技术(SmartScale™、SmartFeed™ 和 GreenFeed™)开发了三种应用程序接口(API)和配套流程,用于快速数据采集、可视化、系统跟踪和汇总统计。我们提供了程序 R 标记文档和示例数据集,以促进这些技术的更广泛应用,并进一步推动精准畜牧技术的发展。所介绍的方法成功地从云中下载了数据,并生成了一系列可视化数据,用于进行系统检查、动物使用率和计算汇总统计数据。这些工具对于进一步采用精准技术至关重要。进一步利用应用程序接口(API)纳入气象数据、动物位置和传感器数据等广泛的数据集,以促进研究人员和牲畜管理者在相关时间尺度上的决策,还有巨大的潜力。
期刊介绍:
Translational Animal Science (TAS) is the first open access-open review animal science journal, encompassing a broad scope of research topics in animal science. TAS focuses on translating basic science to innovation, and validation of these innovations by various segments of the allied animal industry. Readers of TAS will typically represent education, industry, and government, including research, teaching, administration, extension, management, quality assurance, product development, and technical services. Those interested in TAS typically include animal breeders, economists, embryologists, engineers, food scientists, geneticists, microbiologists, nutritionists, veterinarians, physiologists, processors, public health professionals, and others with an interest in animal production and applied aspects of animal sciences.