Intelligent Bio-Environments: Exploring Fuzzy Logic Approaches to the Honeybee Crisis
This paper presents an overview of how fuzzy logic can be employed to model intelligent bio-environments. It explores how non-invasive monitoring techniques, combined with sensor fusion, can be used to generate a warning signal if a critical event within the natural environment is on the horizon. The honeybee hive is presented as a specific example of an intelligent bio-environment that unfortunately, under certain indicative circumstances, can fail within the natural world. This is known as Colony Collapse Disorder (CCD). The paper describes the design of a fuzzy logic methodology that utilizes input from non-invasive beehive monitoring systems, combining data from dedicated sensors and other disparate sources. An overview is given of two fuzzy logic approaches that are being explored in the context of the beehive; a fuzzy logic system and an Adaptive Neuro-Fuzzy Inference System (ANFIS).
Project in collaboration with the Institute of Energy and Sustainable Development (IESD)
Citation : Bassford, M. and Painter, B. (2016) Intelligent Bio-Environments: Exploring Fuzzy Logic Approaches to the Honeybee Crisis. Proceedings of 12th International Conference on Intelligent Environments (IE'16), 14-16 September 2016, London, UK.
Research Group : Centre for Computational Intelligence
Research Institute : Institute of Energy and Sustainable Development (IESD)
Peer Reviewed : Yes