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An Agile AI and IoT-Augmented Smart Farming: A Cost-Effective Cognitive Weather Station

Author

Listed:
  • Amine Faid

    (NEST Research Group, LRI Lab, ENSEM, Hassan II University of Casablanca, Casablanca 20000, Morocco)

  • Mohamed Sadik

    (NEST Research Group, LRI Lab, ENSEM, Hassan II University of Casablanca, Casablanca 20000, Morocco)

  • Essaid Sabir

    (NEST Research Group, LRI Lab, ENSEM, Hassan II University of Casablanca, Casablanca 20000, Morocco
    Department of Computer Science, University of Quebec at Montreal (UQAM), Montreal, QC H2L 2C4, Canada)

Abstract

Internet of Things (IoT) can be seen as the electricity of 21st century. It has been reshaping human life daily during the last decade, with various applications in several critical domains such as agriculture. Smart farming is a real-world application in which Internet of Things (IoT) technologies like agro-weather stations can have a direct impact on humans by enhancing crop quality, supporting sustainable agriculture, and eventually generating steady growth. Meanwhile, most agro-weather solutions are neither customized nor affordable for small farmers within developing countries. Furthermore, due to the outdoor challenges, it is often a challenge to develop and deploy low-cost yet robust systems. Robustness, which is determined by several factors, including energy consumption, portability, interoperability, and system’s ease of use. In this paper, we present an agile AI-Powered IoT-based low-cost platform for cognitive monitoring for smart farming. The hybrid Multi-Agent and the fully containerized system continuously surveys multiple agriculture parameters such as temperature, humidity, and pressure to provide end-users with real-time environmental data and AI-based forecasts. The surveyed data is ensured through several heterogeneous nodes deployed within the base station and in the open sensing area. The collected data is transmitted to the local server for pre-processing and the cloud server for backup. The system backbone communication is based on heterogeneous protocols such as MQTT, NRF24L01, and WiFi for radio communication. We also set up a user-friendly web-based graphical user interface (GUI) to support different user profiles. The overall platform design follows an agile approach to be easy to deploy, accessible to maintain, and continuously modernized.

Suggested Citation

  • Amine Faid & Mohamed Sadik & Essaid Sabir, 2021. "An Agile AI and IoT-Augmented Smart Farming: A Cost-Effective Cognitive Weather Station," Agriculture, MDPI, vol. 12(1), pages 1-31, December.
    • Handle: RePEc:gam:jagris:v:12:y:2021:i:1:p:35-:d:713342
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    References listed on IDEAS

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    1. Aadhityaa Mohanavelu & Sujay Raghavendra Naganna & Nadhir Al-Ansari, 2021. "Irrigation Induced Salinity and Sodicity Hazards on Soil and Groundwater: An Overview of Its Causes, Impacts and Mitigation Strategies," Agriculture, MDPI, vol. 11(10), pages 1-17, October.
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