Bio-inspiration for efficient mobile sensor networks

Abstract

Mobile sensor networks are a rapidly emerging technology with broadapplications in surveillance and defense. However, engineers designing mobilesensor networks face a significant challenge; how do you design a mobile sensornetwork that can reliably detect information in noisy, dynamically changingenvironments, and at the same time make this network energy efficient? Thischallenge is extremely difficult to solve owing to its multi- dimensionality, and hasbeen highlighted as one of the major challenges facing robotics in the next five toten years.Moving animal groups such as flocks of birds or schools of fish function and facethe same challenges as our own engineered sensor networks. Individuals inmoving animal groups have to collectively sense and explore environmentswhere information is difficult to detect, and then communicate detectedinformation between group members. Therefore, animal groups behaveeffectively the same way as mobile sensor networks. Because natural selectionhas shaped animal groups sensing and communication networks to beadaptable, robust and efficient, they can be used to inform the design of our ownsensor network technology.This project is designed around the ONRs priorities of Integrated and DistributedForces, Operational Endurance and Sensing and Sense-Making. The project willquantify how animal groups self-organize to form mobile sensor networks thatcan reliably detect information in noisy and dynamically changing environments.This information will be used to design new protocols for mobile sensor networksthat can adapt their network configuration in response to changing environmentalconditions, while at the same time remaining energy efficient.

Document Details

Document Type
DoD Grant Award
Publication Date
Nov 09, 2020
Source ID
N629092112005

Entities

People

  • James E Herbert-Read

Organizations

  • Office of Naval Research
  • United States Navy
  • University of Cambridge

Tags

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Data Mining and Knowledge Discovery.
  • Distributed Systems and Data Platform Development

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy
  • Autonomy - Autonomous System Control