by Karina Medwenitsch, Markus Schindler, and Christoph Klikovits (Forschung Burgenland GmbH)
How can advanced data analysis reshape agriculture in Austria’s climate-stricken Seewinkel region? By combining IoT, AI, and real-time environmental analysis, researchers at Forschung Burgenland are pioneering innovative solutions to optimise water management and support the energy transition, ensuring resilience in the face of climate change.
The Green Sentry research project addresses the pressing challenges posed by climate change in the Seewinkel region of Austria, a vital agricultural area increasingly affected by extreme weather conditions. Starting in 2024, this initiative leverages advanced digital technologies and data analysis to develop sustainable solutions for water management and agricultural resilience. By combining innovative IoT sensors, real-time monitoring, and cutting-edge analytics, Green Sentry aims to enhance resource efficiency, reduce environmental impact, and strengthen the region’s adaptability to climate stressors.
The Seewinkel region located in Eastern Austria is particularly vulnerable to climate extremes such as droughts and intense heat waves, which have drastically affected agricultural productivity. Farmers have reported crop yield reductions of up to 50% for staples like maize and soybeans. Groundwater depletion, high irrigation costs due to reliance on diesel-powered systems, and occasional irrigation bans exacerbate the challenges. These issues demand innovative and sustainable solutions to ensure agricultural viability and economic stability in the region.
Previous research has shown the significant potential of IoT technologies for improving water management, particularly in agriculture. In the Civis 4.0 Patria project [L1], IoT-based solutions were employed to monitor environmental conditions and manage water resources, providing a foundation for future efforts like Green Sentry. This project demonstrated the effectiveness of IoT technologies in real-time data collection, aiding in the efficient allocation and use of water resources in various sectors. Similarly, studies have highlighted the benefits of IoT-enabled modern technologies for irrigation management, emphasising their ability to provide real-time data, optimise irrigation schedules, and reduce water consumption by dynamically adjusting irrigation needs [1] [2]. These findings contribute to the ongoing development of IoT-based systems that can monitor and manage water resources efficiently, providing the basis for Green Sentry’s approach to optimising water usage in Seewinkel.
The primary objective of Green Sentry is to address the aforementioned challenges by developing and implementing a scalable technological framework for sustainable water management and agricultural optimisation. The project aims to create precise systems for monitoring and regulating water use, particularly in large-scale irrigation systems. This involves employing advanced technologies to collect and analyse environmental data, enabling data-driven decision-making that enhances irrigation efficiency, reduces water consumption, and preserves groundwater resources. Additionally, the project fosters collaboration among local stakeholders, ensuring the solutions are practical and tailored to the region’s specific needs.
The methodology of Green Sentry integrates IoT technologies, cloud-based data processing, and advanced visualisation tools to facilitate comprehensive environmental monitoring and efficient resource management. IoT sensors deployed across wells and agricultural fields measure critical parameters, including water levels in wells, air humidity, air temperature, soil temperature, leaf temperature, light intensity, soil moisture, and leaf moisture. A Long-Range Wide Area Network (LoRaWAN) gateway installed in the Seewinkel region acts as the hub for transmitting sensor data. This data is collected in an open-source LoRaWAN Network Server (ChirpStack), where it is processed and stored in a time-series database (InfluxDB) for further analysis. To make the information accessible and actionable, the data is visualized via an open-source data visualisation and monitoring solution (Grafana), providing stakeholders with real-time insights into environmental conditions. The process of acquiring, processing and analysing the sensor data is illustrated in Figure 1. The technologies used in this project enable precise monitoring of water usage and environmental variables, allowing for the identification of inefficiencies and the optimisation of irrigation strategies. Additionally, the interoperability of these systems ensures they align with existing platforms, enhancing the utility and scalability of the solutions developed.
Figure 1: Collection, processing and analysis of the sensor data within Green Sentry.
The data analysis techniques employed by Green Sentry play a central role in the project’s success. By continuously collecting data from a variety of environmental sources, the project can generate a real-time, comprehensive understanding of water availability and environmental conditions. The data analysis helps identify patterns, predict water needs, and optimise irrigation schedules, all of which lead to reduced water consumption and more efficient use of resources. This data-driven approach can be particularly useful in areas like Seewinkel, where the risk of water scarcity is high, and resource management is critical.
While Green Sentry focuses on optimising water management in agriculture, it also opens avenues for further research. Future studies could expand real-time data analysis by incorporating environmental factors, such as the impact of weather patterns on soil and plant conditions, to refine predictive models for irrigation and automated water usage systems. Beyond agriculture, Green Sentry’s approach could be applied to sectors like water treatment, urban planning, and climate resilience in vulnerable regions for large-scale data analytics. The integration of IoT technology, data analysis, and cloud solutions opens up new opportunities for efficiently managing resources and creating innovative approaches for smart cities. Data convergence techniques could also enhance disaster response systems, supporting real-time decision-making during extreme weather events.
Through its innovative approach, Green Sentry not only supports the immediate needs of the Seewinkel region but also provides a scalable model for tackling similar challenges in other climate-vulnerable areas.
Link:
[L1] https://forschung.hochschule-burgenland.at/projekte/projekt/civis-40-patria/
References:
[1] S. Ismaili, et al., "IoT-Based Irrigation System for Smart Agriculture," 2024 XXXIII International Scientific Conference Electronics (ET), pp. 1-6, 2024, doi: 10.1109/ET63133.2024.10721573.
[2] N. Nawandar and V. Satpute, "IoT-Based Low Cost and Intelligent Module for Smart Irrigation System," Computers and Electronics in Agriculture, vol. 162, pp. 979-990, 2019, doi: 10.1016/J.COMPAG.2019.05.027.
Please contact:
Karina Medwenitsch
Forschung Burgenland GmbH, Austria
