Click here to view this collection in the new DAP user interface
Swarm Sensing Modelling
Pollination provided by honey bees is crucial for global agricultural production yet bee populations are declining. To investigate potential stressors to honey bee health, the Swarm Sensing Project is developing miniature sensing devices and mounting them on large numbers of bees, in order to provide detailed information on their behaviour. An agen... moret-based computational model has been developed to simulate insect flight behaviours under different environmental conditions. The model is currently generating synthetic data to support the development of analysis and visualisation techniques for the project. Subsequently, it will process field data from the micro-sensors to characterise honey bee flight behaviour and to understand changes in their behaviour once exposed to stressors. This model provides a comprehensive platform for the simulation, representation and analysis of insect flight behaviour. Initial results have been validated using radio-frequency identification tags attached to foraging worker bees. less
Artificial Intelligence and Image Processing not elsewhere classified
Simulation and Modelling
12 Jan 2015
25 Jun 2015
Honey bee foraging behaviour
Insect flight behaviour
Radio frequency identification on bees
The data used to develop and evaluate the model came from two sources:
1. South Esk Modelling output (L&W);
2. RFID experiments with bees (Geeveston Experiment) - Data61.
Two data sets are provided in the "FIles" tab:
- The first is entitled MicroCoSM1.zip and includes a Model Description, a User Guide and a Unit Testing Regime for the python version of the Swarm Sensing Model (MicroCoSM1), together with all of the python code.
- The second is entitled BeeFlightSim.zip and includes a re-implementation of the Insect Flight Simulator in the specialised agent-based modelling language NetLogo, together with a User Guide.
Raymond Williams, Paulo de Souza, Stephen Quarrell, Setia Budi, Ferry Susanto, Benita Vincenta, Geoff Allen, Auro Almeida, Dale Worledge, Leandro Disiuta, Pascal Hirsch, Gustavo Pessin, Helder Arruda,
Peter Marendy, Leon dos Santos, Thomas Gillard, Andojo Ongjodjojo Ong
CSIRO Open Source Software Licence (Based on MIT/BSD Open Source Licence)
CSIRO (Australia), University of Sydney (Australia), University of Tasmania (Australia), Vale Institute of Technology (Brazil), Victoria University (Australia)
Williams, Ray; De Souza Junior, Paulo (2016): Swarm Sensing Modelling. v2. CSIRO. Software Collection.
All Rights (including copyright) CSIRO 2016.
The metadata and files (if any) are available to the public.
ActivePython 2.7 from ActivePython distribution, netCDF4, Numpy and Scipy, Matplotlib and Mayavi, Tkinter,
MicroSensing Technology & Systems
This project is about developing a microsensing platform of sub-mm size able to generate energy, stored it in micro-batteries, communicate data via antenna, sense data and be controlled by a clock and has a memory to store the information. As an initial demonstration of the capability to be offered we deployed electronic tags on bees and this data ... morecollection is about the initiative emerging from this OCE Science Leader project. less
Paulo De Souza Junior
Modelling swarm sensing data ingestion and analysis and visualisation
The swarm sensing project is developing micro-sensing technologies to be deployed in large numbers in the environment. In preparation for the data availability, this model was developed to prepare an simulation environmental where data from micro-sensors can be ingested, analysed and visualised. As the project currently works with honey bees, an ag... moreent-based model was developed to represent the bee flight behaviour, as if those bees were carrying small sensors. To simulate measurements to be done by these micro-sensors we used an atmospheric model output from South Esk region in Tasmania. less
Paulo De Souza Junior