WaggleNet: A LoRa and MQTT-Based Monitoring System for Internal and External Beehive Conditions

2025-12-08

AI Summary

Global bee populations are declining continuously due to habitat loss, pesticide exposure, and climate change, threatening agricultural productivity and food security. Existing smart beehive systems predominantly monitor internal hive parameters while neglecting external environmental influences, suffering from high cost, poor scalability, and lack of contextual analytics. This paper proposes a dual-perspective beehive monitoring system leveraging LoRaWAN and MQTT protocols, the first to jointly integrate multi-source environmental data—both inside and outside the hive—including temperature, humidity, ambient light, and GPS coordinates for context-aware anomaly detection. The system adopts a modular, low-power node architecture coupled with a centralized gateway, enabling cost-effective, large-scale deployment. Experimental evaluation demonstrates 100% packet delivery within 110 m line-of-sight range; under obstructed conditions, reliable communication is maintained up to 95 m, with end-to-end latency under 5 seconds and continuous operation exceeding 60 days.

Technology Category

• Application Domains: Internet of Things, Sensor Networks & Smart Cities
• Intelligent Robots: Multi-Robot Systems
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Bee populations are declining globally due to habitat loss, pesticide exposure, and climate change, threatening agricultural productivity and food security. While existing smart beehive systems monitor internal conditions, they typically overlook external environmental factors that significantly influence colony health, and are constrained by high cost, limited scalability, and inadequate contextual analysis. We present WaggleNet, a novel dual-scope monitoring system that simultaneously captures both internal hive conditions and external environmental parameters using a cost-effective LoRa-MQTT architecture. Our system deploys modular worker nodes ($sim$$15 each) equipped with temperature, humidity, light, and GPS sensors both inside and around beehives. A master node functions as a LoRa-MQTT gateway, forwarding data to a cloud server with a mobile application interface. Field experiments confirmed reliable operation with 100% packet delivery over 110 meters in line-of-sight conditions and 95 meters in obstructed environments, including successful deployment inside wooden hive structures. Our system demonstrated stable end-to-end latency under 5 seconds and continuous operation over a two-month period across diverse environmental conditions. By bridging the gap between internal and external monitoring, WaggleNet enables contextual anomaly detection and supports data-driven precision beekeeping in resource-constrained settings.

Problem

• Monitors internal and external beehive conditions simultaneously
• Addresses high cost and limited scalability of existing systems
• Enables contextual anomaly detection for precision beekeeping

Innovation

• LoRa-MQTT architecture for dual-scope hive monitoring
• Modular low-cost sensor nodes with GPS and environmental sensors
• Cloud server and mobile app for contextual anomaly detection