Sonorama R-Bus
This was my master thesis project for my MA Degree in New Media Arts. The project was funded by the Helsinki Art Museum HAM.
Acoustic ecology is an interdisciplinary field that aims to understand the relationship
mediated through sound between human beings and their environment. The impact of
industrialization and urbanization has led to a growing concern about noise pollution,
its effects on wildlife, and how humans understand and perceive sounds in their
increasingly loud habitats. Within this field, the niche hypothesis proposes that each
species occupies a unique acoustic niche in the environment to minimize interference
and maximize communication efficiency. Therefore, using these principles, this thesis
aims to create a system that can simulate a natural sonic ecosystem that can react
and adapt to natural and artificial sonic inputs. This work is part of a larger art
project called R-Bus, where an autonomous driverless bus roams the streets of
Helsinki.
Urban soundscapes are captured by microphones deployed around the
city and fed into an artificial life physarum simulation (Alife), where the system
processes the incoming sound by ransforming the signals into a spectrogram, then
feeding this into the simulation, and finally producing sounds by using IFFT from
the resulting simulated image. The agent-based simulation is controlled by a neural
network (NN) guided by an evolutionary genetic algorithm (NEAT). This process
determines the ecosystem’s behavior and final sonic expression. The system also
implements autopoietic and sympoietic concepts that describe life as self-organizing
and co-evolving systems to produce a naturalistic evolutionary process. The resulting
audio signal is played for the audience inside the bus alongside the signals from the
microphones and other soundscapes. The sounds produced by the ALife simulation
vary widely, ranging from whale-like to machine-like and encompassing various
insect-like noises and other mechanical sounds.
Image (A) shows creatures that are stable at higher frequencies. Image (B)
shows a more homogeneous distribution. The image (C) showcases a good example
of adaptability, where stable bands can be observed. Image (D) is an example of a
larger emergent structure that quickly recovers after a disruption is triggered in the
middle-range frequencies.
Niche differentiation was achieved,
though the agents’ lifetimes were relatively short, and convergence was not always
observed. Approximately 1,200 people experienced the R-Bus installation. For
some participants, the sounds were familiar, understandable, and even described as
beautiful, while for others, the synthetic sounds were imperceptible. This project highlights the disruption that human-generated sounds cause to natural environments
and offers a system that could be used to understand this disruption better, as well
as the relationship between humans and their sonic environment.