An IoT-Based Precision Agriculture Adaptation Model for Water Efficiency in Small-Scale Farming

Dewi Maharani; Eko Rohman; Fajar Iskandar

Authors

Dewi Maharani Universitas Brawijaya Author
Eko Rohman Universitas Brawijaya Author
Fajar Iskandar IPB University Author

Keywords:

Iot-Based Agriculture, Precision Agriculture, Small-Scale Farming, Smart Irrigation, Water Efficiency

Abstract

This study aims to develop an IoT-based precision agriculture adaptation model for improving water efficiency in small-scale farming. The study addresses the problem of inefficient irrigation practices among smallholder farmers who often depend on visual observation, inherited farming knowledge, and uncertain weather patterns when making water management decisions. A qualitative case study approach was used to explore farmers’ experiences, perceptions, and adaptation processes in using or responding to IoT-based irrigation tools. Data were collected through semi-structured interviews, field observation, and documentation involving small-scale farmers, farmer group leaders, agricultural extension officers, local technicians, and village-level stakeholders. The data were analyzed thematically to identify patterns related to irrigation decision-making, perceived usefulness of IoT, trust in digital data, adoption barriers, social support, and local adaptation needs. The findings show that IoT-based precision agriculture can support water efficiency when the technology is simple, affordable, easy to interpret, and aligned with farmers’ daily practices. Farmers accepted IoT tools more readily when sensor data complemented their local knowledge rather than replaced it. The study contributes to digital agriculture adoption theory by emphasizing that technology adaptation in smallholder farming is a contextual and social process. The findings imply that policymakers, extension officers, and technology developers should design farmer-friendly IoT systems supported by training, demonstration plots, and local technical assistance. Future studies should test the model across different crops and irrigation contexts.

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