Utilizing IntellaNest Technology for the study of collective behavior in ants
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Authors
Dykstra, Joshua
Keating, John
Tran, Rich
Mahmood, Ausif
Issue Date
2023-03-24
Type
Other
Language
en_US
Keywords
Collective Behavior , Automated Behavioral Tracking System , Ant Colony Monitoring
Alternative Title
Abstract
Ants are an ideal model with which to answer questions about collective behavior, due to their size and relative ease of rearing them in a laboratory environment. However, accurately capturing fine-scale data about individual and group interactions presents a number of challenges. Behavioral data are often collected through human observations, recorded manually, and then transposed to digital databases, introducing the opportunity for observer bias and transcription errors. Many research teams must also create custom enclosures for each experiment, and video or photo data must be high resolution to sufficiently record social interactions. Limited resources, time, and funding can lead to shortened study periods or can limit the scope of these studies. Our goal was to develop a low-cost, all-in-one setup for behavioral observations, integrating a physical enclosure that meets the environmental requirements of the given species with temperature and humidity sensors, cameras, a cloud environment and an Al detection and tracking software package. Our design allows for continuous monitoring of the colony's physical environment as well as accurate recording of individuals' behavioral data. We hope our work can support the field of collective behavior by increasing opportunities to collect fine-scale data of social interactions in insect colonies, allowing for new questions to be asked and to expand our understanding of the evolution of social behavior.
Description
UB Rise 2023
Computer Science and Engineering