Smart Water Management Platform: IoT-Based Precision Irrigation for Agriculture

Area of Science:

• Agricultural Engineering
• Environmental Science
• Computer Science

Background:

• Precision irrigation is crucial for sustainable agriculture, optimizing crop yield and resource use.
• Integrating diverse technologies for seamless smart water management remains a challenge.
• The Internet of Things (IoT) offers a promising solution for intelligent water management systems.

Purpose of the Study:

• To present the architecture, platform, and deployment of the SWAMP IoT-based smart water management system.
• To evaluate the replicability and scalability of the SWAMP platform through real-world pilots.
• To analyze the performance of FIWARE components within the SWAMP platform.

Main Methods:

• Development of an IoT-based smart water management platform (SWAMP).
• Implementation across four agricultural pilots in Brazil and Europe.
• Performance analysis of FIWARE components for scalability assessment.

Main Results:

• The SWAMP platform demonstrates replicability across diverse pilot sites.
• Adequate performance was achieved for the SWAMP pilots.
• Higher scalability with reduced computational resources necessitates component re-engineering and tailored configurations.

Conclusions:

• The SWAMP project successfully deployed an IoT platform for precision irrigation.
• The platform's performance is suitable for pilot applications but requires optimization for broader scalability.
• Future work should focus on re-engineering components for enhanced, resource-efficient scalability.