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IoT Can Help Increase Cow Milk Production

2023-07-26 09:24:55
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Illustration: © IoT For All

By the year 2050, the world’s population is projected to reach 9.8 billion. Making food production as efficient as possible is not just an economic challenge; it is also a global urgency.

However, unable to escape this catch-22, cattle farming is also affected by climate change, as heat negatively impacts milk production.

To help food producers tackle future challenges, farmers will have to embrace disruptive technologies that may seem foreign to the agricultural world. The Internet of Things (IoT), artificial intelligence algorithms, machine learning, and genetic modifications are becoming increasingly relevant for professionals in the sector.

Intuition, built over years of experience, must now be supplemented with the certainty provided by data through technology.

A Real-Life Example

The Voshazhnikovo Farm in Russia has transformed into a “smart farm” to increase its milk production. The farm has a capacity of approximately 8,000 heads of cattle, including 4,500 dairy cows. Before the implementation of IoT, the farm used to produce 125 tons of milk daily, averaging nearly 28 liters per cow per day.

Libelium

The farm equipped its veterinarians with additional information about environmental conditions such as temperature, humidity, pressure, cow health, and other parameters. They discovered that the rising temperatures due to increasingly frequent heatwaves affected the cows’ appetite, resulting in increased feed and food expenses. Thus, they decided to leverage this information to feed their livestock more efficiently.

Technology partners installed environmental sensors inside the farm to collect data on temperature, pressure, humidity, and lighting conditions experienced by the cows. This information is transmitted via LoRaWAN connectivity to the farm’s ERP system, where it is added to the dataset along with external information (anemometer, temperature, humidity, precipitation), RFID tags, food purchase records, veterinarians’ Excel reports, and various external data sources.

All this data is sent to the farm’s cloud platform. Machine learning and business intelligence techniques are applied to help the staff and owners make better decisions.

Libelium

The IoT project is designed to predict herd reproduction, milk production, and animal diseases based on a combination of external and internal factors, statistical data, economic indicators, staff information, and laboratory data. This not only reduces costs associated with maintaining cow health, labor, and reproduction but also helps achieve strategic business goals, such as expanding production and opening new units.

As a result, a correlation was found between temperature, nutrition, and even the daily performance of farm workers. The owners discovered that when the temperature decreases on the farm, the cows require more feed.

The system alerts the staff to these changes, and farmers receive notifications via email or SMS. With proper feeding, milk production increases.

Award-Winning Efficiency

As a result, Voshazhnikovo’s smart farm achieved better figures: savings on feed costs for 2,000 dairy cows amounted to €340,000 over 180 days. In other words, three months after implementing the IoT system, milk production at Voshazhnikovo Farm increased to 33 liters per cow per day, an impressive 18 percent more than the previous months (28 liters per cow per day).

Libelium

Furthermore, to certify their progress, Voshazhnikovo received the “Best Innovation” award in the “Efficiency” category at the Annual Danone Forum.

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  • Agriculture
  • Automation
  • Farming
  • Sensors

  • Agriculture
  • Automation
  • Farming
  • Sensors

参考译文
物联网可帮助提高奶牛产奶量
插图:© IoT For All 到2050年,世界人口预计将达到98亿。提高粮食生产的效率不仅是一个经济挑战,也是全球迫切的需要。然而,养牛业也无法逃脱这个两难局面,因为气候变化同样影响养牛业,高温会对牛奶产量产生负面影响。为了帮助食品生产者应对未来的挑战,农民必须接受那些可能对农业界来说还很陌生的颠覆性技术。物联网(IoT)、人工智能算法、机器学习和基因改造等技术正变得越来越重要。过去,经验积累出来的直觉是主要的判断依据,但如今,这些判断必须通过技术带来的数据确定性加以补充。现实案例 位于俄罗斯的沃沙日尼科沃农场(Voshazhnikovo Farm)转型为“智能农场”,以提高奶产量。该农场拥有约8,000头牛,其中包括4,500头奶牛。在采用物联网技术之前,该农场每天的牛奶产量为125吨,平均每天每头奶牛产奶28升。Libelium 该农场为兽医提供了关于环境条件(如温度、湿度、气压、牛的健康状况等)的额外信息。他们发现,由于热浪越来越频繁,气温上升影响了奶牛的食欲,导致饲料和食品成本上升。于是,他们决定利用这些信息,更加高效地喂养牲畜。技术合作伙伴在农场内安装了环境传感器,收集奶牛所处的温度、气压、湿度和光照条件的数据。这些信息通过LoRaWAN连接传输到农场的ERP系统,并与外部信息(如风速计、温度、湿度、降水)、RFID标签、饲料采购记录、兽医的Excel报告以及其他外部数据源进行整合。所有这些数据都会被发送到农场的云平台。随后,采用机器学习和商业智能技术,帮助员工和所有者做出更佳的决策。Libelium 该物联网项目的设计目的是通过结合外部和内部因素、统计数据、经济指标、员工信息和实验室数据,来预测牛群繁殖、牛奶产量和动物疾病。这种方法不仅降低了维持奶牛健康、劳动力和繁殖的成本,还帮助农场实现战略目标,如扩大生产、开设新农场单位。结果发现,温度、营养和农场工人的日常绩效之间存在相关性。农场主发现,当农场温度下降时,奶牛需要更多的饲料。系统会向员工发出这些变化的警报,农民也会通过电子邮件或短信收到通知。通过合理喂养,牛奶产量得到了提升。获奖的效率 因此,沃沙日尼科沃智能农场取得了更好的成绩:在180天内,为2,000头奶牛节省了34万欧元的饲料成本。换句话说,在实施物联网系统三个月后,沃沙日尼科沃农场的牛奶产量达到每天每头奶牛33升,比此前的28升提高了18%,这一增长非常显著。Libelium 此外,为了证明其进步,沃沙日尼科沃获得了年度达能论坛(Danone Forum)“效率”类别中的“最佳创新奖”。TweetShareShareEmail 农业 自动化 种植 传感器 --> 农业 自动化 种植 传感器
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