Precision agriculture relies on timely and reliable data from the field, helping farmers better understand soil, crop and environmental conditions and make more informed decisions. However, one of the main challenges is the lack of dense and affordable measurement networks that can operate across large agricultural areas with limited infrastructure and minimal maintenance.

The project focused on the development of proof-of-concept, low-budget IoT prototypes for agricultural applications. Such devices can support distributed field monitoring by collecting data from multiple locations and creating a stronger basis for data-driven decision-making models. In this way, the project contributes to the wider use of digital technologies in agriculture, where IoT systems can help optimize resources, monitor production conditions and support more sustainable farming practices.

A key part of the project was the analysis of low-power communication technologies and hardware design choices needed for practical field deployment. Different network options, including LoRaWAN and NB-IoT, were compared in terms of energy consumption, communication performance and suitability for different use cases. The project also explored electronic circuit topologies, power supply options and generic low-power sensor designs optimized for different requirements in terms of battery life, measurement frequency and data transfer speed.