IoT, Business Intelligence and Blockchain technology reduces methane emissions in a cattle farm

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A Smart Farming project with Libelium’s IoT technology helps to reduce pollution and optimize the management of livestock production in Romania

Livestock contributes substantially to the global economy by providing food, employment, and financial security to billions of people around the world. However, it is in the spotlight due to its high contamination.

Agricultural pollution is released into the environment as a result of the cultivation and raising of livestock, food crops, animal feed, and biofuel crops.

reduces methane emissions in livestock
The Food and Agriculture Organization of the United Nations (FAO) estimates that livestock production is responsible for 14.5% of global greenhouse gas emissions:

  • Food production and processing accounts for 45% of contamination
  • Enteric fermentation of ruminants accounts for 39% of total emissions
  • Manure storage and processing represents 10%
  • The remaining 6% is attributable to the processing and transportation of animal products

Striking the balance between producing food for the entire planet and reducing pollutant emissions is one of the main challenges of the UN Sustainable Development Goals.

» What has been the challenge?

FAO estimates that livestock production is responsible for 14.5% of global GGE, a large part caused by the enteric fermentation of ruminants.

» Which Libelium solutions work in this IoT project?

Libelium Plug & Sense! Smart Environment PRO to monitor temperature, humidity, particulate matter and gases (NOx, COx, CH4, NH3, etc.)
 success project smart farm blockchain

Science and technology to find a solution

Faced with increasing campaigns against meat consumption to protect the planet, livestock producers have taken action. For this, they have all the scientific and technological advances at their fingertips.

In New Zealand, for example, they are researching a vaccine that works against certain gut microbes responsible for producing methane as animals digest their food.

On the other hand, Beia, distributor of Libelium in Romania, is making use of IoT technology in a project that seeks to reduce emissions from intensive cattle farming by optimizing livestock production. The project designed by a consortium of companies has a holistic approach so will monitor the animal feeding, the behavior and characteristics of the animals, and the environment of the livestock.

In this consortium named FarmSustainaBl, together with Beia, there are the following institutions:

  • Beam Innovation SRL, BEAM, Romania
  • Division of Farm Structures and Agricultural Machinery, Agricultural University of Athens, AUA, Greece
  • SDU Software Engineering, Mærsk Mc-Kinney Møller Institute, University of Southern Denmark, SDU, Denmark

methane control in farm cow

Automated animal welfare surveillance

This Smart Farming project has been developed in Milanovici Farm, located near the city of Alexandria, in south Romania, that manage around 200 head of cattle.

Two Libelium Plug & Sense! Smart Environment stations have been installed on this livestock farm to monitor various the farm environment (temperature, humidity, gas sensors (NOx, COx, CH4, NH3, etc.))

The IoT infrastructure (which includes sensors and network devices for data transmission) allows an accurate collection of all the data that can be captured on a livestock farm.

diagram how to reduce methane emission in livestock

The sensors of the Libelium Smart Environment solution send the data by dual radio (LoRaWAN and WiFi) to the FarmSustainaBl Cloud. So, the parameters monitored in the farm facilities provide structured and relevant data to support decision-making to optimize data management and farm maintenance.

The platform collects and analyzes the data on a web platform to provide recommendations to cattle stakeholders (farmers, consultants, etc.) who make management decisions to reduce greenhouse gas emissions.

Better data for more informed decisions

Then, the web platform applies Business Intelligence to generate models and simulate farm and animal performance in different scenarios. Therefore, based on simulations and modeling, the program allows the definition of optimal system configurations, to maximize the results of the farm.

This includes the development of state-of-the-art methods and tools that allow automated monitoring of animals and their health. In particular, different data analysis methods have been developed for process discovery, insight extraction, and correlation detection, as well as modeling and simulation methods to evaluate different decisions and parameter settings.

business intelligence reduces methane emission in livestock

The potential of environmental sensors connected to the Internet makes it possible to explore different data and process models, such as neural networks or data mining.

Some of the Business Intelligence methods they are exploring on the farm are:

  • Simulations based on data to understand and forecast change and explore new pathways without risk to the animal.
  • Data analysis with Bayesian models, association rule mining, support vector machines, Neural networks.
  • Optimization using probabilistic models with genetic algorithms.

Smart contracts that reward low methane emissions

Furthermore, this IoT project allows the farms to obtain finances by participating in voluntary carbon markets in agriculture.

The platform also enables the implementation of smart contracts that guarantee the best prices for agricultural products resulting from processes with low greenhouse gas emissions.

smart farming

These smart contracts are based on a blockchain transaction network. Wireless sensor devices at farm facilities upload unique information from each cow or calf to the list of records (blockchain) to establish an immutable and auditable provenance. In this way, the canon for gas emissions that customers will pay is more reliably known.

The blockchain also allows the creation of public and smart contracts to automatically offer the best prices for agricultural products with the lowest greenhouse gas emissions.

This IoT project contributes to achieve the following Sustainable Development Goals:

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