Authors:
Zhanshan (Sam) Ma
;
Axel W. Krings
and
Robert E. Hiromoto
Affiliation:
University of Idaho, United States
Keyword(s):
Insect Sensory System, Micro Aerial Vehicle (MAV), Wireless Sensor Network, Non-cooperative Social Behaviour, Insect-Inspired Robot, Cellular Computing, Agent-based Computing, Biosensor, Dendritic Neuronal Computing, Molecular Network.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Biomedical Signal Processing
;
Devices
;
Health Information Systems
;
Human-Computer Interaction
;
Physiological Computing Systems
;
Wearable Sensors and Systems
Abstract:
This is the second article in a two-part series in which we briefly review state-of-the-art research in communications and computing inspired by insect sensory systems. While the previous article focuses on the biological systems, the present one briefly reviews the status of insect-inspired communications and computing from the engineering perspective. We discuss three major application areas: wireless sensor network, robot and micro aerial vehicle (MAV), and non-cooperative behaviours in social insects and their conflict resolution. Despite the enormous advances in insect vision and mechanosensory inspired robot and MAV, micro-flight emulation, motion detection and neuromorphic engineering, etc., the potential inspiration from insect sensory system is far from being fully explored. We suggest the following promising research topics: (1) A new grid computing architecture emulating the neuronal population such as the visual neurons that support the compound eyes, the PN (Projection N
eurons) in AL (Antennal Lobe) or the ORN (Olfactory Receptor Neurons) from insect sensory organs (sensilla). This may be further integrated and enhanced with the dendritic neuronal computing. (2) New generation of multimodal wireless sensor and ad-hoc networks that emulates insect chemosensory communication. The inspiration of multimodalities in insect sensory systems also implies that there are multiple parallel networks operating concurrently. Furthermore, the insect chemosensory is significantly robust and dependable with built-in anti-interference mechanisms. (3) Non-cooperative behaviours in social insects may offer insights to complement swarm intelligence (inspired by cooperative behaviours) or to devise new optimization algorithms. It may also provide inspiration for proposing survival selection schemes in evolutionary computing. We suggest using evolutionary game theory to model conflict resolution in social insects, given its success in modelling conflict resolution of other animals.
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