Green Artificial Intelligence: Towards an Efficient, Sustainable and Equitable Technology for Smart Cities and Futures

Abstract

Smart cities and artificial intelligence (AI) are among the most popular discourses in urban policy circles. Most attempts at using AI to improve efficiencies in cities have nevertheless either struggled or failed to accomplish the smart city transformation. This is mainly due to short-sighted, technologically determined and reductionist AI approaches being applied to complex urbanization problems. Besides this, as smart cities are underpinned by our ability to engage with our environments, analyze them, and make efficient, sustainable and equitable decisions, the need for a green AI approach is intensified. This perspective paper, reflecting authors’ opinions and interpretations, concentrates on the “green AI” concept as an enabler of the smart city transformation, as it offers the opportunity to move away from purely technocentric efficiency solutions towards efficient, sustainable and equitable solutions capable of realizing the desired urban futures. The aim of this perspective paper is two-fold: first, to highlight the fundamental shortfalls in mainstream AI system conceptualization and practice, and second, to advocate the need for a consolidated AI approach—i.e., green AI—to further support smart city transformation. The methodological approach includes a thorough appraisal of the current AI and smart city literatures, practices, developments, trends and applications. The paper informs authorities and planners on the importance of the adoption and deployment of AI systems that address efficiency, sustainability and equity issues in cities.

Innovation Trajectories for a Society 5.0

“…ICT and cloud computing [13,23,30,47] have the ability to use IoT technologies [19,28,46,48] and Big Data [24,28,49] to generate, process, analyze, and exploit urban data. In this way, it is easier to make decisions that accurately address the problems [25,45,50], issues, and challenges related to sustainability [51][52][53] and urbanization [15,16,54].…”

“…These devices are based on standardized communication protocols, which allow for the sharing and exchange of information across heterogeneous platforms. Consequently, the IoT improves the interactivity and efficiency of critical infrastructures, such as those used in transport [31,45,55], in security [19,56,57], in education [16], and in healthcare [20,58]. Furthermore, IoT allows physical objects to mimic human characteristics, such as sight and hearing [59,60], the decision-making process for communicating [25,61], and the sharing of information and the coordination of actions with each other [23,46,48].…”

“…The results made it possible to identify 25 factors covering different fields (Table 2). The highest numbers of higher studies (Figure 9) were found in the areas of Big Data technology and data processing (23) and sustainability (21), Objective (16), connection technologies (13), manufacturing technologies (11), stakeholders (8), governance (7), and communication (2) (Table 2).…”

“…The two reforms in the vision of a new world share a common direction. From this perspective, Industry 4.0 can be considered as a tool to promote sustainable innovation and is, therefore, a policy-driven discourse on innovation [10][11][12][13][14][15][16].…”

DNA Profiling: An Investigation of Six Machine Learning Algorithms for Estimating the Number of Contributors in DNA Mixtures

“…Moreover, we will use deep learning to improve classification performance. A major theme of our research is smart cities and societies [23]- [25], big data [26]- [28], high performance computing [29], [30], healthcare [31]- [33], information systems [34], [35], system integration [36], [37], and artificial intelligence [38], [39]. Future work on DNA profiling will also look into developing new smart applications for DNA profiling and its integration with other smart city systems.…”