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Related Experiment Video

Updated: Jul 15, 2026

A Precise and Autonomous System for the Detection of Insect Emergence Patterns
06:22

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Published on: January 9, 2019

An autonomous YOLOv9-edge-to-cloud intelligence system for proactive honeybee mortality mitigation.

Tai-Sheng Su1, Chih-Ying Li1, Chin-Chun Wu2

  • 1National Pingtung University of Science and Technology, Taiwan.

Journal of Invertebrate Pathology
|July 13, 2026
PubMed
Summary

An automated system uses AI to detect honeybee deaths from pesticide poisoning, enabling faster responses. This early-warning tool aids beekeepers in protecting vital pollinators and biodiversity.

Keywords:
Automated early-warning systemDeep learningHoneybee mortalityPesticide-associated mortalityYOLOv9

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Area of Science:

  • Agricultural Science
  • Environmental Science
  • Computer Science

Background:

  • Honeybee mortality is a major threat to apiculture and biodiversity.
  • Manual hive inspections are time-consuming and may miss early signs of pesticide exposure.
  • Timely detection of pesticide-associated bee deaths is crucial for evidence collection and beekeeper intervention.

Purpose of the Study:

  • To develop an automated early-warning system for detecting honeybee mortality.
  • To differentiate between naturally senescent bees and those affected by neurotoxic pesticide poisoning.
  • To provide rapid alerts for timely on-site investigations and sample collection.

Main Methods:

  • Integration of YOLOv9 deep learning with a real-time IoT framework.
  • Development of a waterproof beehive with an edge-side image acquisition terminal.
  • Training the model on a field dataset and utilizing a lightweight IoT communication protocol.

Main Results:

  • The system achieved a mean average precision (mAP@0.5) of 0.937 in classifying honeybee mortality.
  • The model detected morphological signs indicative of neurotoxic pesticide exposure.
  • The system successfully provided instantaneous mobile alerts via Discord Webhook.

Conclusions:

  • The automated system offers a viable solution for early detection of pesticide-induced honeybee mortality.
  • This tool complements standard colony management practices by providing timely alerts.
  • The system supports rapid response, aiding in the collection of residue samples for analysis.