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The SWAMP project developed an Internet of Things (IoT) platform for smart agricultural water management. While adequate for current pilots, enhancing scalability requires component re-engineering and specific configurations.

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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.