How Can ICT Be Applied to Support Sustainable Agriculture?

The rapid growth of the global population requires producing 70% more food by 2050 than is currently available, exacerbated by challenges including reduced land and water availability, climate change, and declining soil fertility (Alfred et al., 2021). Information and Communication Technology (ICT) applications in agricultural practices, such as row crop production, include, among others, smart irrigation systems, drones, and land-based robots. These technologies present opportunities and challenges in achieving environmental, social, and economic sustainability.

Introduction

Row crop production farms face additional pressures, including demographic transitions, labour shortages and dietary shifts (McFadden et al., 2022). These obstacles have accelerated the adoption of technological innovations, particularly digital agriculture tools such as precision farming (Karunathilake et al., 2023; McFadden et al., 2022).

Precision farming collects temporal, spatial, and individual data to optimise resource efficiency, productivity, and sustainability in agriculture (Carrer et al., 2022). Since its inception in the 1990s, advances in computational power, connectivity, and technology have expanded its potential to address sustainability and productivity goals (Karunathilake et al., 2023). These advancements also align with several United Nations Sustainable Development Goals (SDGs), such as Zero Hunger (SDG 2) and Clean Water and Sanitation (SDG 6) (Priyambada et al., 2023; Vishnoi & Goel, 2024).

Smart Irrigation Systems

Smart irrigation systems use wireless and Internet of Things (IoT) technologies to optimise water usage (Boursianis et al., 2021; Ramachandran et al., 2018). At the core of these systems are IoT sensors in the form of field sensors to monitor real-time parameters such as soil moisture, temperature, and rainfall, ensuring that water is applied at the right time, place, and amount (Vallejo-Gómez et al., 2023). Resource optimisation through real-time monitoring reduces water and energy use, minimises wastage, and enhances crop yield (Ramachandran et al., 2018). Automated systems handle irrigation tasks without human intervention, reducing labour requirements and optimising efficiency (Lieder & Schröter-Schlaack, 2021). Advances in AI and cloud computing has potential to make these systems even more powerful by helping farmers make smarter, data-driven decisions (Ramachandran et al., 2018; Vallejo-Gómez et al., 2023).

Studies have shown that smart irrigation systems have the potential for substantial water savings, in certain cases up to 75% (Lieder & Schröter-Schlaack, 2021). Such systems not only conserve water but also provide environmental benefits, such as reducing greenhouse gas emissions (Lieder & Schröter-Schlaack, 2021). This is achieved by optimizing irrigation timing and quantity, which leads to a lower energy consumption in pumps and decreased nitrous oxide emissions from the soil (Lieder & Schröter-Schlaack, 2021).

Drones in Agriculture

Drones or Unmanned Aerial Vehicles (UVAs), are at a very simple level, small aerial robots (Nazarov et al., 2023; Rejeb et al., 2022; Tsouros et al., 2019). Drones are controlled and operated manually from land or are equipped with GPS programs to fly certain routes autonomously (Nazarov et al., 2023). They play a pivotal role in optimising crop management by providing reliable geolocation data and capturing ultra-high-resolution images and information about the crops or the entire field (Nazarov et al., 2023; Tsouros et al., 2019). The remote sensing technology behind drones and their ability to fly only a few centimetres above ground allows them to gather and process high spatial and temporal resolution data and images of the different field patches and plants (Tsouros et al., 2019). Their ability to scan large lands quickly without irritating the soil make them a powerful tool (Tsouros et al., 2019). Compared to their predecessors, drones are simpler to use, more flexible and more cost-effective (Tsouros et al., 2019). They perform higher-quality recordings without long waiting hours and are operational in nearly every weather even on cloudy days (Manfreda et al., 2018). The most common applications of drones in agriculture include weed mapping and management, growth monitoring and yield estimation, disease detection, precision irrigation and precise application of agricultural inputs such as fertilizers and pesticides (Tsouros et al., 2019).

Land-Based Robots

Land-based robots include autonomous systems designed for tasks such as weeding, planting, and selective harvesting (Araújo et al., 2021). These robots use advanced sensors and AI technologies (Araújo et al., 2021).

In weed management, robots equipped with precision tools, including lasers, target weeds without affecting crops, reducing herbicide reliance (ETH Zürich, 2022). For example, the “Caterra” project combines robotics, mechanical engineering, and machine learning to achieve high precision in weed removal using laser technology (ETH Zürich, 2022). In selective harvesting, robots assess crop ripeness and harvest only market-ready produce, improving efficiency and reducing waste (ETH Zürich, 2023; Kootstra et al., 2021).

Overall robotic systems can reduce labour-intensive tasks, enhance precision in field operations and support sustainability by minimising resource use and environmental impacts (Kootstra et al., 2021; ETH Zürich, 2022).

Challenges and Considerations

Despite their potential, ICT and IoT technologies face significant barriers. High initial costs can be restrictive for small-scale farmers (Mizik, 2022). The reliance on IoT sensors and battery-operated devices raises concerns about energy consumption and electronic waste (Jawad et al., 2017). Skill gaps among farmers, particularly in developing regions, hinder the adoption of advanced technologies (Torero, 2021).

Additionally, data security is another critical issue. The increased use of IoT devices introduces risks of data breaches and cyberattacks (Gupta et al., 2020). Ambiguous legal frameworks make it difficult for farmers to trust these systems (Gupta et al., 2020; Kaur et al., 2022).

Conclusion

ICT and IoT innovations in agriculture offer significant opportunities to address global food security challenges while promoting sustainability. However, overcoming barriers such as cost, energy consumption, and skill gaps is critical. Collaborative efforts between governments, technology providers, and farmers can facilitate the adoption of these technologies and ensure they contribute to a more sustainable agricultural future (McFadden et al., 2022).

The article is based on a report created as part of the “Digitalization & Sustainability” module in the Master’s program “Circular Innovation & Sustainability”.

Citations

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Cover image: https://pilotinstitute.com/drone-mapping/