Small-scale farm digitalization using IoTs in Hungary

In the Northern Great Plain region of Hungary, close to the Ukrainian and Romanian borders, agriculture is dominated by small-scale family farms operating in one of the country’s least developed areas. Limited infrastructure, including unreliable internet connectivity in certain locations, constrains access to modern agricultural equipment. Although smartphone ownership is widespread among farmers, the adoption of digital tools for professional use remains notably low. 

At the same time, farmers in the region face a diverse and interconnected set of challenges. Their operations are increasingly shaped by climate-related risks, which have become both more frequent and more unpredictable in recent years. Recurrent frost events can damage early-stage crops and blossoms, while prolonged periods of drought significantly reduce soil moisture and limit crop development. Sudden storms and strong winds can cause physical damage to plants and infrastructure, further undermining farm productivity. Collectively, these environmental stressors place continuous strain on farmers. The local agricultural profile is characterized by a strong emphasis on arable crops and fruit production, with the Szamos region widely recognized for its processed food products and beverages. However, orchards are particularly vulnerable to pest infestations, which can result in substantial yield losses.

Despite the persistent and multifaceted nature of these risks, smallholder farmers remain under-equipped with effective mitigation tools, especially digital technologies. Key barriers include affordability and usability. Technology providers and machinery manufacturers predominantly focus on larger farms, aligning with their economic interests and the scalability of their solutions. Additionally, small farms often lack the necessary technical skills, as well as confidence and openness toward adopting new technologies, further limiting digital transformation in the sector.

Given the specific characteristics of the target group, conventional approaches to digitalization proved ineffective in this context - even the term “solution” becomes misleading, as each farm requires a tailored combination of tools, knowledge, and support. Standardized, off-the-shelf solutions failed to address the high variability among farms, where differences in scale, resources, and operational needs make a “one-size-fits-all” model impractical. For this reason, our approach was offering digital technology encapsulated inside advisory service provision. The selected technologies were chosen for their cost-effectiveness while maintaining functionality comparable to higher-end, professional-grade equipment. The software infrastructure was developed in-house (AEDIH) using open-source tools, ensuring both flexibility and affordability. Farmers received hands-on support in the introduction, customization, and practical application of digital tools, along with continuous advisory input to strengthen decision-making processes. The advisory-based approach fostered long-term collaboration between service providers and farmers, allowing for iterative improvements and broader outreach. Ultimately, the focus of the intervention extended beyond technology adoption itself. The primary objective was to enhance the overall economic performance, environmental sustainability, and social well-being of participating farms. Farmer satisfaction—and their continued engagement with the advisory service—was closely tied to the tangible improvements achieved in these areas, rather than to the mere use of digital devices. 

Main tools used:

• Affordable weather station
• Pro weather stations (to compare)
• Individual sensors
• Smart insect trap

Technical elements:

• Dragino, SenseCap leaf, soil moisture, temperature, humidity sensors 
• LoRA gateway
• 1NCE data card
• Chirpstack server
• LAMP, javascript for visualization
• Sencor SW12500
• nMETOS WS 200
• Sencrop Raincrop

For this customer we provided two different types of weather stations as part of the Test before invest service, to compare functionality, affordability and the price performance ratio. The pro weather station was a Raincrop from Sencrop, while the consumer level affordable weather station was Sencor SWS12500. Both stations were equipped with the most necessary sensors related to agricultural usage: temperature, moisture and precipitation. Interestingly, Sencor has 7 types of sensors while the Raincrop only has 3. Sencor sends data to open access platforms (WeatherCloud, WunderGround providing API, and setting up server connection was also possible), while Raincrop requires a paid subscription and data can be assessed in the Sencrop App.    

The Sencor station was set up in advance by GAK (AEDIH coordinator) and was made available for the farm throughout one entire growing season. The data was collected, stored and processed on the GAK server, and the application also provided a web-based data analysis interface (the station sends data every minute on wind speed and direction, air pressure, temperature, humidity, precipitation, light intensity and UV radiation).

Probably the most important data and benefit is related to the measurement of precipitation. Monitoring rainfall helps the farmer to decide when to travel to remote field locations, for example for soil tillage operations or pesticide spaying applications. With the climate change it became usual that even within a village’s field boundaries, the distribution and amount of rainfall may vary greatly. Temperature, humidity and precipitation data together forms the foundation for pest forecast models as well. 

Within the Test before invest service we also provided the farmer with a smart insect trap which can contribute to the weather observation with factual data regarding the spreading of pests. The main benefit of the Scoutlab trap according to the promise of the start up company is turning pest monitoring from a manual, reactive process into an automated, data-driven one using AI-powered insect traps, which can improve timing of pest control, reduce unnecessary spraying, and lower labor costs. Scoutlabs’ traps automatically photograph and identify pest insects, then send alerts when pest pressure increases. That means farmers can act before infestations spread and reduce yield loss. Instead of physically checking traps across orchards or fields, farmers can monitor pest activity remotely from a phone or web dashboard. Scoutlabs claims this removes much of the driving and trap-checking work. The company states growers can save significant scouting labor by replacing manual trap inspections with digital monitoring and reallocating skilled workers to other tasks. Scoutlabs cites up to 80% labor savings in some cases.

The farmer was also interested in testing individual sensory devices for which we provided an NB IoT leaf moisture sensor. Detection of leaf moisture bases one of the foundational data for the forecast of pests proliferation. The pest forecast models usually need this data for the correct calculations. Leaf wetness is strongly linked to fungal and bacterial diseases, when leaves stay wet too long, diseases such as mildew, rust, and blight spread more easily. Main benefits: 

• Real-time monitoring from home: the IoT system can send sensor data to a mobile app or cloud dashboard, so the farmer can monitor his fields remotely, receiving instant notification during risky conditions.
• Reduced use of pesticides, fungicides: since disease risks can be predicted based on leaf wetness duration: farmers spray only when necessary, lowering chemical costs, reducing environmental impact and chemical residue.
• Data-driven decision making: historical moisture data helps farmers understand crop patterns, compare seasons and weather impacts and make better farm management decisions.
• Labor savings: manual field checking becomes less necessary. Less time spent inspecting crop conditions.

Do’s

• Integrate the delivery of digital technologies into farm advisory services, ensuring that technology adoption is supported by continuous guidance, practical expertise, and measurable on-farm benefits. This combined approach enhances usability and long-term value for farmers.
• Prioritize the use of open-source technologies whenever possible. Beyond lowering initial investment costs, these tools enable greater flexibility, allowing solutions to be tailored to the diverse and evolving needs of smallholder farms, not only to reduce upfront costs, but also to gain more flexibility in customization according to small farmers' diverse individual needs. 
• Recognize that cost-effective technologies can, in many cases, provide comparable functionality to highly branded and heavily marketed products. When complemented with strong advisory support, these alternatives can deliver similar outcomes.
• Apply modular and adaptable sensing equipment by selecting and combining individual sensor devices as needed. In many cases, these targeted tools can offer more relevant and affordable insights than complex, full-scale systems.
• Organize training sessions and on-farm demo events close to participants’ locations, focusing on practical, hands-on learning. Also consider combining them with some social elements like cooking or discussion of actual topics of interest.
• Take into account the operational realities of small farms, particularly their limited financial capacity and human resources, and ensure that proposed solutions remain accessible and manageable within these constraints.
• Advisors and influential farmers can be engines at the local level to bring farmers together.

Don’ts

• Don’t expect that start-up technology will always work as advertised, when put under real conditions. 
• Don’t organize training events with static and theoretical content for small scale family farmers. Avoid the timing of events in the agricultural peak season(s).
• Don’t leave the farmer without continuous support.