Smart Farming

This article is a translation of the German IOTA Beginner’s Guide by Schmucklos.

Smart Farming

Use Cases

Ayni: Aquaponics recirculating systems – Medium

Future Farm: Using the Tangle for smart agriculture – IF

iotAgrar: Digital water meter

IOTAqua: Smart water meter system

Smart Farming

Today’s farmers already have a number of digital technologies at their disposal, such as specialized software solutions for data analysis, computer-controlled machines, various sensors (soil, water, light, humidity, temperature), different communication and positioning options (mobile, LoRaWan / GPS, satellite). With these technologies, farmers can monitor their field conditions without having to enter the field itself and make strategic decisions for the whole farm or for a single area.

With the IoT, the next technology revolution is upon agriculture. IoT will become the driving force of smart agriculture in the future. For the first time there is the possibility of smart machines (robotics, drones, sensors) communicating with each other to perform data-driven processes autonomously. In a repetitive cycle, with the help of installed IoT devices, all data will be collected, processed and analyzed. This allows farmers’ new smart management systems to respond more quickly to emerging issues and changes in environmental conditions. This gives farmers better control over the process of raising livestock and growing crops, making the entire production chains more predictable, efficient and cost-effective.

General Use cases

Precision agriculture

Throughout the field, sensors collect various data and send it to the cloud. The measurements provided can be used to accurately map and analyze environmental conditions. With this data, an intelligent system with superhuman accuracy can give crops the exact treatment they need. Decisions are made per square meter or even per plant, rather than for an entire field. Plant growth and any abnormalities can be monitored individually to effectively prevent disease or infestation. By taking these precise measurements within a field, farmers can also increase the effectiveness of pesticides and fertilizers, target them or even forgo them.

Precision Farming

As with precision agriculture, smart IoT sensors allow farmers to better monitor the temperature, health, activity, nutrition, and needs of individual animals. Owners of large farms can use wireless IoT applications (ex. collar sensors) to monitor the location, well-being, and health of each animal. This information can be used to identify sick animals so they can be separated from the herd to prevent the spread of diseases.

Smart greenhouses

In current greenhouses, environmental parameters are often adjusted through manual intervention or a semi-automatic control mechanism. This often leads to energy loss, increased labor costs and production losses.

IoT-controlled smart greenhouses can use various sensors to intelligently monitor the climate and remotely control irrigation, lighting, and fertilization systems without the need for manual intervention. This allows environmental parameters to be measured and adjusted according to the specific requirements of each crop. This collected data could be stored in a cloud-based platform for further processing and analysis with minimal effort.

Agricultural drones

Both ground and aerial drones are already being used by some farmers, as drones capture multispectral, thermal and visual imagery while in flight. The collected data provides farmers with insights into a whole range of metrics. For example, plant health indices, plant counting and yield prediction, plant height measurement, plant canopy mapping, chlorophyll measurement, nitrogen content in wheat, drainage mapping, weed pressure mapping, etc. The analysis of this collected data is a real added value for any farmer. This is a great help to make a decision for the use of pesticides and fertilizers. However, with the help of IoT, many processes could be carried out autonomously or the collected knowledge could be resold.

Management system

A productivity management system typically includes all IoT devices and sensors installed on site, as well as a powerful dashboard with analytics and integrated billing / reporting capabilities. These systems also provide monitoring and remote control capabilities and allow for intervention in most operations.


Smart farming offers real potential for more productive and sustainable agricultural production based on a more precise and resource-efficient approach.

The IoT combined with a smart network of sensors, actuators, cameras, robots, drones and other connected farming devices, enables an unprecedented level of control and automated decision making. This IoT-driven agriculture is paving the way for the so-called “third green revolution,” following the revolutions in plant breeding and genetics. The “third green revolution” is now taking over agriculture.

In the future, this smart agriculture will show that the use of pesticides and fertilizers will decrease, while overall efficiency will increase. IoT technologies will enable better traceability of food, which in return will lead to increased food safety. This will also benefit the environment, for example by using water more efficiently or optimizing animal treatments.

What about IOTA?

This third green revolution relies on the IoT and the combined application of data-driven analytics technologies, M2M communication. Tamper-proof data trading is exactly what IOTA will enable in the IoT. IOTA technology offers smart machines the ability to autonomously exchange data or value with each other via the IoT, and data can also be stored in a tamper-proof manner or offered for sale on data marketplaces. Who could be a potential buyer for the collected data? This could be another farmer from the same region with similar environmental conditions or a chemical company that wants to further develop pesticides and fertilizers.

I am sure that in the future there will be one or the other IOTA project in agriculture. It will not remain only with Tangle Sheep. 🙂

Original source

Last Updated on 16. February 2021