Intelligent Lighting Networks

Using Internet-enabled lights, artificial intelligence and sensing technologies to create lighting networks that address societal, economic and environmental-health issues.

The 2.5 million Australian street lights represent one of the most comprehensive and potentially versatile networks in the country. The annual energy cost of public lighting in Australia exceeds $125 million and street lighting is the single largest source of carbon emissions from local government, typically accounting for 30–60% of total emissions. Global shifts in lighting technology have resulted in the installation of half a million next-generation smart lights with a further 2 million proposed. In Victoria alone, it is estimated that these energy-saving lights will reduce carbon emissions by 1.21 million tonnes, saving councils and ratepayers up to $340 million through reduced electricity and maintenance costs.

The global increase of artificial light (approximately 2.2% per year on average) is one of the most pervasive forms of environmental pollution. Research in medicine and ecology demonstrates a broad range of negative consequences associated with the presence of artificial light at night. Light at night affects animal migration, foraging, mating, and can result in increased mortality – it is estimated that hundreds of millions of birds die annually from crashing into lit structures. There are also physiological costs including an increased risk of cancer, immune suppression, depression, and heart disease. These consequences affect all organisms, including humans.

While energy-saving LED technology has reduced carbon emissions and energy costs, it also encourages further increases in lighting levels. This amount of lighting is broadly harmful and often unnecessary.

This project explores how Internet-enabled lights, artificial intelligence and sensing technologies  can significantly improve the performance of lighting systems to create lighting networks that address societal, economic and environmental-health issues.

This project will use the rapidly growing technologies of the Internet of Things to design intelligent lighting systems that will be aware of their environments and their inhabitants. Relying on networked computing, such systems will: know past trends; react to unfolding events; predict future patterns; and collect data for the optimisation of their performance. Intelligent lighting networks will be able to modify patterns and intensity of illumination automatically, precisely matching the needs, minimising negative impacts, and providing new creative capabilities for urban design.

Intelligent lighting networks should act as integral members of urban ecosystems. Therefore, their design parameters need to account for interactions with existing urban environments. The deployment of systems interacting with multiple stakeholders cannot succeed without their approval. This requirement is particularly pertinent in the case of artificial lighting where the cultural tendency of evolutionary-diurnal humans to increase illumination at night contradicts the urgent need for darkness. Security and safety are often cited as the justifications for maintaining uniform bright lighting. However, the increased safety may be perceived rather than real, while there are well-evidenced harmful biological consequences.

In response to this misalignment between needs and perceptions, the project proposes to identify the design parameters for intelligent lighting networks by developing a co-design workflow based on a data-driven, immersive and interactive virtual-reality simulation. This simulation will allow flexible, rapid and safe appraisal of alternative solutions with a variety of human audiences. This testing will analyse the feasibility, efficiency and cultural acceptability of possible designs, generating specifications for future full-scale prototyping and implementation.

The project will implement a reusable co-design tool for prototyping and testing of intelligent lighting networks in a virtual environment and deploy this tool to elucidate design parameters for ecologically-sensitive intelligent lighting networks.

Research Team

Postgraduate Students

Ashton Disckerson, School of BioSciences, University of Melbourne

Julian Rutten, Melbourne School of Design, Swinburne University

Tony Yu, Melbourne School of Design, University of Melbourne

External Collaborators

Dr Andre Chiaradia, Phillip Island Nature Parks

Keith Harwood, Ironbark Sustainability

Rod van Der Ree, City of Melbourne

Tim Hunt, Arup Group

Funding

Seed Funding 2018

References

Alamdar, F., Kalantari, M. & Rajabifard, A. 2015, 'An Evaluation of Integrating Multisourced Sensors for Disaster Management', International Journal of Digital Earth, vol. 8, no. 9, pp. 727-749.

Alamdar, F., Kalantari, M. & Rajabifard, A. 2016, 'Towards Multi-Agency Sensor Information Integration for Disaster Management', Computers, Environment and Urban Systems, vol. 56, no. March, pp. 68-85.

Botts, M., Percivall, G., Reed, C. & Davidson, J. 2008, 'OGC® Sensor Web Enablement: Overview and High Level Architecture', in GeoSensor Networks, eds. S. Nittel, A. Labrinidis & A. Stefanidis, Springer, Berlin, DE, pp. 175-190.

Durrant, J., Botha, L. M., Green, M. P. & Jones, T. M.. 2018, 'Artificial Light at Night Prolongs Juvenile Development Time in the Black Field Cricket', Journal of Experimental Zoology Part B: Molecular and Developmental Evolution, vol. 330, no. 4, pp. 225-233.

Holland, A. & Roudavski, S. 2016, 'Design Tools and Complexity: Mobile Games and Collective Imagination', in Proceedings of the 34th International Conference on Research in Computer Aided Architectural Design in Europe: Complexity and Simplicity, A. Herneoja, T. Österlund and P. Markkanen, Brussels, BE; Oulu, FI, eCAADe; University of Oulu, pp. 555-564.

Jones, T. M., Durrant, J., Michaelides, E. B. & Green, M. P. 2015, 'Melatonin: A Possible Link between the Presence of Artificial Light at Night and Reductions in Biological Fitness', Philosophical Transactions of the Royal Society B: Biological Sciences, vol. 370, no. 1667.

McLay, L. K., Green, M. P. & Jones, T. M. 2017, 'Chronic Exposure to Dim Artificial Light at Night Decreases Fecundity and Adult Survival in Drosophila Melanogaster', Journal of Insect Physiology, vol. 100, pp. 15-20.

Roudavski, S., Holland, A. & Rutten, J. 2018, 'Mould Racing, or Ecological Design through Located Data Games', in Proceedings of the 24th International Symposium on Electronic Art (ISEA), R. Adebayo, I. Farouk, S. Jones and M. Rapeane-Mathonsi, Durban, SA, Durban University of Technology, pp. 193-200.

What happens to wildlife in a city that never sleeps?, by Dr Therésa Jones, Pursuit, 5 June 2018.