Smart Farming: Enhancing agriculture yield with IoT

Published on by Alexis Leibbrandt
Smart Farming Data

According to the BI Intelligence survey, the adoption of IoT devices in the agriculture industry is predicted to reach a market size of $15.3 billion by 2025. As per the Food and Agriculture Organization (FAO), the world needs to produce 70% more food by 2050 due to the exponential growth of the world population.

In the light of depleting natural resources such as fresh water and shrinking agricultural lands, enhancing farm yield has become more important than ever. Moreover, the shifting structure of the agricultural workforce is an impending concern in the agricultural industry. Due to the declining agricultural workforce, solutions based on IoT have been triggered to reduce the need for manual labor.

Smart Farming is focused on helping farmers close the gap between supply and demand. IoT-based agriculture comprises specialized equipment, wireless connectivity, software, and IT services. IoT technology provides an optimum application of resources to achieve high crop yields and reduce operational costs.

Smart farming enhances traditional farming equipment with sensors, wireless connectivity and cloud computing to capture data and provide actionable insights to manage all the pre-and post-harvest operations on the farm. The data on field operations is accessible, organized, and can be monitored from anywhere. Thanks to these technological advancements, plantation owners nowadays have the tools to reach an optimum application of resources and achieve high crop yields while reducing operational costs.

5 ways IoT-based smart farming can improve agriculture

Agricultural planners have started realizing that IoT-based Smart Farming is a driving force for increasing agricultural production in a sustainable manner. As the IoT adoption is still developing, there is an opportunity for solution providers in this industry to develop impactful products and services.

The IoT ecosystem already offers several applications that can improve agriculture. Let us take a look at some of the benefits.

  • Better monitoring thanks to Smart Agriculture Sensors
    A swarm of smart sensors collects data on weather conditions, soil quality, cattle's health, crop growth progress, and more. It tracks the real-time situation and suggests solutions based on these measurements. This data helps the farmer monitor its current production and, if needed, plan the modifications for the next season (e.g. favor one particular crop instead of another depending on the condition of the soil).
  • Better Control Over The Internal Processes
    Data collected by the smart sensors increase the ability to foresee the production output. That, in turn, allows farmers to plan a better product distribution. The precise knowledge of the number of crops harvested ensures the product doesn't lie around unsold. With better control over the internal processes, the production risks are reduced drastically.
  • Cost Management and Waste Reduction
    The increased control over the production can help farmers manage costs and reduce wastes. The detection of anomalies in crop growth or livestock health will mitigate the risks of losing the yield.
  • Increased Business Efficiency Through Process Automation
    Be it irrigation, pest control, fertilizing, or other multiple processes across the production cycle, all these processes can benefit from improved automation with the use of sensors and actuators. Process automation goes beyond the mere collection of the data and closes the loop by actuating based on the IoT data.
  • Enhanced Product Quality And Volumes
    Smart Farming will help farmers achieve better control over the production process. It enables them to maintain higher crop quality and adhere to growth capacity standards through automation.
Smart Farming Application

IoT-based farming cycle

To optimize the agricultural process, IoT devices and sensors installed on a field should gather and process the data in a repeated cycle that enables farmers to react to emerging issues fast. The farming cycle in this case is as follows.

  • Observation - Sensors record data from the crops, soil, livestock, or atmosphere.
  • Diagnostics - The sensor values are calibrated with specific software with predefined decision models and rules that ascertains the examined condition, needs, or anomalies.
  • Decisions - Based on the diagnostic stage, a set of improvement opportunities can be identified. In worst cases, the system might trigger specific alarms that shall be addressed in a timely manner. Typically, the software could decide whether a location-specific treatment is necessary for a particular piece of land.
  • Implementation - Finally, the treatment needs to be implemented by the farmer. In the case of a closed control loop involving smart actuators, the measures could be triggered without the intervention of the farmer.

Let’s explore the concept of the IoT-based farming cycle with a specific case.

Capturing and evaluating nutrient flows in agriculture using IoT sensor technology: a smart agriculture case from Switzerland.

Agriculture in Switzerland faces the challenge of producing more on less land (decreasing agricultural land/urban sprawl, coupled with population growth). Increasing efficiency through technological progress plays a central role in this context. However, in contrast to other countries, Swiss agriculture, rather small-scale, has been relatively little automated and digitalized.

The nutrient cycle is at the center of agricultural production, making it a core factor for Switzerland's long-term and sustainable development. In-depth knowledge of the nutrient flows within a farm significantly impacts the yield of production and the consumption of resources. So far, there is hardly any recording of the nutrient turnover on farms; the substances have to be recorded manually and evaluated in external laboratories. These procedures are not very accurate and are both inefficient and costly.

In connection with today's prevailing technology, there is, therefore, clear potential for improvement.

  • More accurate data collection benefits multiple stakeholders: Better nutrient data allows farmers, as farm managers, to use their nutrients more efficiently and optimize their planning and costs.
  • Through more accurate data, authorities gain improved insight into the nutrient distribution and its changes within the cycle across the relevant croplands. These learnings help optimize their planning bases as well as existing models.
Tractor in a field

How to record and evaluate nutrient flows in agriculture using IoT sensor technology.

Based on the akenza IoT platform and standard smart sensors, it becomes possible to digitally record the entire nutrient cycle and make it available to farmers via a web application.

A typical setup of nutrient cycle monitoring would consider the following measurement points:

  • First, the nutrient content in the slurry is measured when the tanker is filled.
  • The composition of the slurry on the farmed area is geo-referenced during distribution. Here, the system records which nutrients were applied where.
  • Plant growth is measured during the growing season, resulting in a referenced map of nutrient availability in the soil.
  • Nutrients are measured at harvest on the forage harvester. At this stage, the exact yield is shown.
  • Finally, nutrients are monitored at the time of feeding. Here, precise information about the nutrient content of the feed is displayed.
Cow cycle

Nutrient cycle in agriculture
(1 manure; 2 soil; 3 harvest; 4 feeding)

This monitoring system thus covers the entire cycle. The measured data can be made available to farms to optimize their production as well as to authorities and land planners.

Post evaluation, the cycle is repeated from the very beginning.

Technological implementation of this smart farming case.

In the depicted case, devices based on NIR sensor technology can be used for the data collection. These sensors work on the principle of near-infrared spectroscopy. It is a physical analysis technique based on spectroscopy in the range of short-wave infrared light.

The sensors are connected to the akenza IoT Platform via wireless technologies such as LoRa or cellular connectivity. The akenza IoT Platform integrates a wide range of sensors and databases. This allows for example to use weather forecasts or an animal database as additional input data sources.

Finally, the end-user can interact with the system via a web application that displays the real-time data as well as the historical data. The data is represented in customizable dashboards that relate to the farm assets.

This is just an example of a smart farming case that can be supported by the akenza platform. Based on the right combination of an IoT platform and specific sensors, one can envision many more use cases.

Speaking of IoT sensors, here are some interesting examples to consider.

Examples of sensors used in smart farming

Smart farming sensors

Left: Decentlab Soil Moisture and Temperature Profile
Middle: Decentlab Tipping Bucket Rain Gauge
Right: Dragino Soil Moisture & EC Sensor

If you are considering launching a smart farming case, our low-code IoT platform should allow you to get started in one afternoon. Simply select the appropriate sensor from our device type library, connect it via our Connectivity-as-a-Service offering and you will be ready to develop your own smart farming solution.

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