Work

Toward Resilient Rural Resource Governance: A Cost-Effective, Data-Driven IoT System for Sustainable Beehive Monitoring and Management

Year: 2026

Type: article

Abstract: Beekeeping occupies a challenging intersection: it is economically vital across vast, under-served rural areas, yet the tools available to manage it rarely match that scale. This paper presents a low-cost, solar-powered IoT system designed to address this gap. Rather than treating beehive management as a narrow agricultural concern, the system frames it as a case study in distributed, data-driven resource governance. Each hive is fitted with an ESP32-based sensor node that tracks temperature, humidity, and equivalent CO2 (eCO2), while solar-powered base stations provide GPS positioning and intrusion detection. All components are connected through a tiered wireless architecture: a 100 m 2.4 GHz RF sensor link connects individual hive nodes to solar-powered base stations, which forward aggregated telemetry to the cloud over a 120 m Wi-Fi or cellular uplink. The system was evaluated in an active apiary across five hives and two solar-powered base stations, which operated continuously for two weeks without failure, including during periods of darkness. The sensors are supported by a four-layer backend architecture that converts raw readings into real-time alerts and monitoring dashboards, providing a decision-support layer designed to assist beekeeping associations and agricultural authorities. The modular backend enables these organizations to coordinate operations, such as pesticide-spraying schedules and hive density across branches, while establishing a practical software foundation for future integration of AI-based analytics and additional sensing modalities. Taken together, the results present a practical, low-cost model for extending resilient, sustainable resource monitoring into rural and agricultural settings, with direct relevance to Saudi Arabia’s beekeeping sector and potential applications in similar deployments elsewhere.

Source: Sustainability

DOI: 10.3390/su182010404

Authors: Ahmad Alghamdi, Sofien Gannouni, Ameur Touir, Kais Belwafi, Achraf Gazdar

Institutions: King Saud University, University of Sharjah

Language: English

Topic: Smart Agriculture and AI

Subfield: Plant Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDGs: Industry, innovation and infrastructure, Zero hunger

Open Access status: gold

Estimated APC paid: $2,896