DigiAgriApp: a client-server application to monitor field activities
Year: 2025
Type: article
Abstract: Farming is increasingly data-driven, leveraging high-frequency and precision data from IoT devices, sensors, and remote tools. Effective data collection, organization, and management are essential to link datasets with agronomic details, forming the foundation for predictive models. These models, using AI and machine learning, optimize decision-making, forecast crop yields, predict pest outbreaks, and enhance resource use. High-quality, diverse data integration is key to building accurate tools that address agriculture's complexity, boosting productivity and resilience. We introduce DigiAgriApp, an open-source client-server application for centralized farming data management. It tracks crop details, sensor readings, irrigation, field operations, production statistics, and emissions for Life Cycle Assessment. Initially developed for the Fondazione Edmund Mach, DigiAgriApp has evolved into a versatile tool. Users can access a public server or deploy a private instance via Docker, making it ideal for institutions, farmers, and corporations alike.DigiAgriApp is available at https://digiagriapp.gitlab.io/digiagriapp-website/.
Institutions: Fondazione Edmund Mach, Loughborough University
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: hybrid
Estimated APC paid: $3,500
Award: G3406588564
OpenAlex ID: W4410487494
