Dear Colleagues,

Smart cities and societies are underpinned by our ability to engage with our environments and analyse and make efficient, sustainable, and equitable decisions [1], [2]. The fundamental fabric of these smart cities and societies is built on smart devices, mobile and other device apps, digital systems, and platforms. The lifeblood of these smart devices and systems are algorithms increasingly powered by artificial intelligence (AI). These algorithms make decisions about virtually everything individuals, organisations, and governments do, such as finding the love of our life; recruiting employees; identifying immoral, illegal, and criminal behaviours in individuals and communities; and so on indefinitely. The decisions of these algorithms relate to many core concepts that characterise us humans and our morals, ethics, principles, laws. These algorithms make decisions about our everyday routines that impact—every second or less—innumerable design and process efficiencies, energy usage, planet environment, and individual and national economies. There is an urgent need to develop green AI algorithms, methods, and technologies for smart cities and societies.               

We call for contributions from scientists and engineers to develop green AI algorithms and technologies for smart applications, devices, digital systems, and platforms.

The topics include but are not limited to the development of green AI in the following application domains:

• Green computing
• Green data
• Green communications and networking
• Green manufacturing and Industry 5.0
• Green food sciences and technologies
• Green robotics and cobotics
• Green land transportation and mobility
• Green aerospace engineering and transportation
• Green precision agriculture
• Green energy
• Green devices, systems, and platforms
• Green environmental technologies
• Green healthcare technologies

References

[1] T. Yigitcanlar, R. Mehmood, and J. M. Corchado, “Green Artificial Intelligence: Towards an Efficient, Sustainable and Equitable Technology for Smart Cities and Futures,” Sustain. 2021, Vol. 13, Page 8952, vol. 13, no. 16, p. 8952, Aug. 2021, doi: 10.3390/SU13168952.

[2] S. Alotaibi, R. Mehmood, I. Katib, O. Rana, and A. Albeshri, “Sehaa: A Big Data Analytics Tool for Healthcare Symptoms and Diseases Detection Using Twitter, Apache Spark, and Machine Learning,” Appl. Sci., vol. 10, no. 4, p. 1398, Feb. 2020, doi: 10.3390/app10041398.

Prof. Dr. Rashid Mehmood
Prof. Dr. Tan Yigitcanlar
Prof. Dr. Juan M. Corchado
Guest Editors

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