Development of an IoT-Based Adaptive Precision Agriculture System for Small-Scale Farmers

Maya Hidayat; Nadia Saputra; Rizki Wijaya

Authors

Maya Hidayat Universitas Brawijaya Author
Nadia Saputra Universitas Brawijaya Author
Rizki Wijaya IPB University Author

Keywords:

Adaptive Precision Agriculture, Internet Of Things, Small-Scale Farmers, Socio-Technical System

Abstract

This study aims to explore the development of an IoT-based adaptive precision agriculture system for small-scale farmers in response to irrigation uncertainty, limited digital access, and the need for practical farm decision support. This research used a qualitative case study approach in Sumberjo Village, Dlanggu District, Mojokerto Regency, East Java, Indonesia, from March to June 2025. Data were collected through semi-structured interviews, field observation, and documentation involving small-scale farmers, agricultural extension officers, farmer group leaders, and IoT system developers selected through purposive and snowball sampling. The findings reveal five main themes: the use of sensor data as a comparison tool for local farming knowledge, the need for simple and understandable technology, gradual trust-building in sensor data, the role of farmer groups in social learning, and economic practicality as a key condition for adoption. These findings show that IoT-based precision agriculture becomes meaningful when it fits farmers’ routines, economic capacity, and local decision-making processes. The study contributes to socio-technical perspectives on digital agriculture by explaining how technology, users, institutions, and local farming practices interact in small-scale farming contexts. The study implies that IoT systems for small farmers should be affordable, adaptive, easy to use, and supported by continuous extension services. Further research should examine long-term impacts on productivity, water efficiency, and adoption sustainability.

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