Comparative Analysis of the IoT Architectures for Smart Agriculture: Methodological Study Using the AHP and COPRAS

Othmane Aitlmoudden, Abdellah Bakhouyi, Nisrine Safeh, Mohammed Aitdaoud, Nawal Sael

Abstract

Global population growth, coupled with the depletion of natural resources and agricultural land and the increasing unpredictability of environmental conditions, has raised significant concerns regarding food security worldwide. These challenges have prompted the adoption of smart farming practices in the agricultural sector, leveraging the internet of things (IoT) and big data solutions to enhance operational efficiency and productivity. The IoT encompasses various advanced technologies such as wireless sensor networks, self-organizing cognitive radio networks, cloud computing, big data analytics, and end-user applications. This article presents a comparative study using multi-criteria analysis to evaluate different proposed architectures for the IoT technology-based smart agriculture. To find the best architecture based on predetermined criteria, this study uses the analytic hierarchy process (AHP) and complex proportional assessment (COPRAS) techniques. By employing these decision-making methodologies, this research contributes to the selection and optimization of IoT-based solutions for smart agriculture, thereby addressing the imperative need for sustainable and efficient food production systems.

 

Keywords: smart farming, the internet of things, complex proportional assessment, analytic hierarchy process.

 

https://doi.org/10.55463/issn.1674-2974.51.5.4


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