A Multi-collective, IoT-enabled, Adaptive Smart Farming Architecture

Abstract

Smart Farming (SF) or Precision Agriculture (PA) use precise and efficient approaches for monitoring and processing information from farms, crops, forestry, and livestock aiming at more productive and sustainable rural development. Internet of Things (IoT) is the ecosystem that can provide effective real-time information gathering and processing mechanisms, while supporting cloud access and decision-making mechanisms. Despite the notable progress in the SF field, the ability of these systems to adapt into different types of crops in order to constitute a ready-to-use tool for agricultural stakeholders remains a challenge. In this paper we present a flexible and easy-to-adopt architecture for applying modern IoT-enabled technologies in the context of SF. The proposed architecture encloses Wireless Sensor Networks (WSNs), meteorological stations and Unmanned Aerial Vehicles (UAVs) along with an information processing system that leverages machine learning and computing technologies. The innovation of the proposed architecture lies in the creation of an integrated monitoring and decision support system aiming at production increasing, efficient allocation of resources and protection of plant capital from exogenous (weather and pests) and endogenous (diseases) factors.