Is this project an undergraduate, graduate, or faculty project?
Graduate
Project Type
individual
Campus
Daytona Beach
Authors' Class Standing
Fayruz Maysha, Graduate Student
Lead Presenter's Name
Fayruz Maysha
Lead Presenter's College
DB College of Engineering
Faculty Mentor Name
Dr. Bryan Watson
Abstract
This study introduces a novel bioinspired algorithm influenced by the kinship coefficients observed in eusocial animals, particularly honeybees (Apis mellifera). In our study, we present a novel bioinspired algorithm, taking inspiration from honeybee kinship coefficient, tailored for optimizing resource allocation in disaster scenarios. This focuses on innovative product-service and energy systems by proposing an infrastructure design that is both resilient and adaptable. By emulating the kinship coefficient observed in bees, we offer an algorithm that enhances the effectiveness of firefighting resources, underscoring the potential of bioinspired computing to revolutionize emergency management and resilience within the context of product-service systems. Our hypothesis is, if the algorithm is inspired by the kinship coefficient observed in bee colonies, then it is possible to improve the allocation and effectiveness of firefighting resources, because these biological models of organization and problem-solving are optimized through evolutionary processes for resilience and adaptability. Our study sets a new paradigm in emergency management, proposing resilient, adaptable, and efficient systems derived from the sophisticated social organizations of eusocial species. Through this work, we demonstrate the value of leveraging natural models of organization to solve complex, dynamic human problems, with potential implications across a spectrum of applications beyond firefighting.
Keywords: Bioinspired algorithm; Kinship coefficients; Resource allocation optimization; Emergency management; Resilient systems
Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, Collaborative, Climbing, or Ignite Grants) from the Office of Undergraduate Research?
No
Bioinspired Infrastructure Design: Leveraging Kinship Coefficients in Eusocial Animals for Resilient Systems
This study introduces a novel bioinspired algorithm influenced by the kinship coefficients observed in eusocial animals, particularly honeybees (Apis mellifera). In our study, we present a novel bioinspired algorithm, taking inspiration from honeybee kinship coefficient, tailored for optimizing resource allocation in disaster scenarios. This focuses on innovative product-service and energy systems by proposing an infrastructure design that is both resilient and adaptable. By emulating the kinship coefficient observed in bees, we offer an algorithm that enhances the effectiveness of firefighting resources, underscoring the potential of bioinspired computing to revolutionize emergency management and resilience within the context of product-service systems. Our hypothesis is, if the algorithm is inspired by the kinship coefficient observed in bee colonies, then it is possible to improve the allocation and effectiveness of firefighting resources, because these biological models of organization and problem-solving are optimized through evolutionary processes for resilience and adaptability. Our study sets a new paradigm in emergency management, proposing resilient, adaptable, and efficient systems derived from the sophisticated social organizations of eusocial species. Through this work, we demonstrate the value of leveraging natural models of organization to solve complex, dynamic human problems, with potential implications across a spectrum of applications beyond firefighting.
Keywords: Bioinspired algorithm; Kinship coefficients; Resource allocation optimization; Emergency management; Resilient systems