Toward Resilient Rural Resource Governance: A Cost-Effective, Data-Driven IoT System for Sustainable Beehive Monitoring and Management
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.
Authors
- Kais Belwafi (ORCID: https://orcid.org/0000-0003-1455-439X)
- Achraf Gazdar (ORCID: https://orcid.org/0000-0002-3646-6959)
- Ameur A. Touir (ORCID: https://orcid.org/0000-0002-5145-6484)
- Sofien Gannouni (ORCID: https://orcid.org/0000-0002-6026-4257)
- Ahmad Alghamdi (ORCID: https://orcid.org/0000-0002-7225-5729)
Institutions
- King Saud University (SA)
- University of Sharjah (AE)
Publication Details
- Journal
- Sustainability
- Published
- 2026-10-13
- DOI
- https://doi.org/10.3390/su182010404
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- King Saud University