From Review to Refinement: An Expert-Informed Environmental Diagnostic Model for Stingless Bee Colony Monitoring

The resilience of stingless bee colonies has become increasingly challenged by erratic climate conditions and intensified environmental stressors. While previous studies have introduced diagnostic models for monitoring colony health, most remain constrained by a narrow reliance on either environmental or behavioral parameters alone. This study proposes a refined diagnostic model that builds on existing frameworks and is further shaped by expert insights from the field. The model integrates environmental inputs, specifically temperature and humidity, with behavioral activity detected via video analysis to deliver a multi-dimensional assessment of colony status. Through a structured review of the literature and interviews with apiculture experts, we identify critical gaps in conventional systems and translate those findings into a more responsive and field-deployable architecture. The result is an improved model capable of categorizing colony health with greater sensitivity and clarity, designed to support early intervention and long-term monitoring. The model is visualized through comparative schematic diagrams, showing the evolution from a basic environmental-only logic to a more holistic decision-making system.

@article{Lejing2025,
  title     = {From Review to Refinement: An Expert-Informed Environmental Diagnostic Model for Stingless Bee Colony Monitoring},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {8},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {Yang Lejing and Rozi Nor Haizan Nor and Yusmadi Yah Jusoh and Nur Ilyana Ismarau Tajuddin and Khairi Azhar Aziz},
  doi       = {10.14569/IJACSA.2025.01608103},
  url       = {https://doi.org/10.14569/IJACSA.2025.01608103}
}