Mr Stenford Ruvinga

Research project: Bees as environmental sensors:The application of signal proceessing and machine learning to model, quantify and predict the effects of environmental stressors on the health and well-being of bees


Recently, there has been much concern over how environmental stressors, pesticides, and related issues may be detrimental to both people and wildlife. For example, the decline in numbers and health of honeybees has become a major concern over recent years. This is believed to be due to a variety of factors, including parasites, diseases and the use of neonicotinoid pesticides. To date, no monitoring studies with living bees have been performed to assess and quantify the distress and harm that pesticides, pollution and other factors cause to bees. Furthermore, evidence has been found that monitoring the well-being of bees can also yield valuable Information about the wider environment

In this project, mathematical and statistical tools and machine learning models will be used to identify natural and anomalous patterns in bee behaviour. Data has already been collected from a variety of types of sensors in some beehives and analysis of patterns in signals from these will provide important information about the well-being of the bees, their daily and seasonal variation in behaviour and status of the local environment. The academic team on this project are collaborating with the University (and other) beekeepers who can provide a valuable alternative perspective on the work.


Mathematics Teacher and Mathematics and Statistics Tutor

Areas of research interest

  • Applied Statistics
  • Machine Learning


  • Bsc Mathematics and Statistics, Kingston University
  • MScRes Applied Statistics, Kinngston University

Funding or awards received

  • Kingston University BMeE Studentship