ABSTRACT
The construction industry has been experiencing many occupational accidents as working on construction sites is dangerous. To reduce the likelihood of accidents, construction companies share the latest construction health and safety news and information on social media. While research studies in recent years have explored the perceptions towards these companies' social media pages, there are no big data analytic studies conducted on Instagram about construction health and safety. This study aims to consolidate public perceptions of construction health and safety by analyzing Instagram posts. The study adopted a big data analytics approach involving visual, content, user, and sentiment analyses of Instagram posts (n = 17,835). The study adopted the Latent Dirichlet Allocation, a kind of machine learning approach for generative probabilistic topic extraction, and the five most mentioned topics were: (a) training service, (b) team management, (c) training organization, (d) workers' work and family, and (e) users' action. Besides, the Jaccard coefficient co-occurrence cluster analysis revealed: (a) the most mentioned collocations were ‘construction safety week', ‘safety first', and ‘construction team', (b) the largest clusters were ‘safety training', ‘occupational health and safety administration', and ‘health and safety environment', (c) the most active users were ‘Parallel Consultancy Ltd.', ‘Pike Consulting Group', and ‘Global Training Canada', and (d) positive sentiment accounted for an overwhelming figure of 85%. The findings inform the industry on public perceptions that help create awareness and develop preventative measures for increased health and safety and decreased incidents.
ABSTRACT
Today, many cities around the globe are interested in developing or adopting smart city policy frameworks;however, the complexity of the smart city concept combined with complicated urban issues makes it a highly challenging task. Moreover, there are limited studies to consolidate our understanding of smart city policymaking. The aim of this study was to bridge this knowledge gap by placing a set of official smart city policy frameworks under the policy analysis microscope. The study approached the analysis by, firstly, internationally collating the smart city policy frameworks of 52 local governments from 17 countries. The methodology then progressed to a deductive content analysis of the identified policies with a thematic data analysis software. The investigation employed the main themes to identify common urban issues in smart city policies—i.e., smart economy, smart environment, smart governance, smart living, smart mobility, and smart people. The results revealed the targeted key planning issues, goals, and priorities, and the ways that smart city policies address these key planning issues, goals, and priorities. The study findings inform policymakers, planners and practitioners on the smart city policy priorities and provide insights for smart city policymaking.
ABSTRACT
An engaged community that reflects a diverse set of experiences is key to an equitable and livable city. However, maximizing engagement activities is often difficult when competing with residents’ busy schedules and hectic daily lives. To explore new opportunities in this space, we developed four augmented reality experiences to learn more about the potential for this technology to transform community engagement practices in the context of City 4.0. City 4.0 utilizes digital technologies to transform public services and the local economy. Its goal is to produce more sustainable urban and societal outcomes. Our findings suggest that augmented reality is least successful when used to recreate existing engagement practices, such as surveys or questionnaires, and more successful when it empowers a sense of agency and ownership over the process in its users. The way augmented reality situates information can aid in making public space feel personal to the individual. In this way, augmented reality’s affordances are less about overlaying digital information in physical space and more about how this can enable individuals to reclaim a sense of control and relevance in the relationship between citizens and councils. We aim to contribute: (a) novel interaction paradigms and an evaluation of their effectiveness and limitation, and (b) new insights into how to support citizens’ sense of agency in public discourse with augmented reality. This paper highlights the value of augmented reality’s affordances to bring to light new interactions between community engagement stakeholders.
ABSTRACT
In the context of smart cities, sustainability is an essential dimension. One of the ways to achieve sustainability and reduce the emission of greenhouse gases in smart cities is through the promotion of sustainable energy. The demand for affordable and reliable electrical energy requires different energy sources, where the cost of production often outweighs the environmental factor. This paper aims to investigate the ways smart cities promote sustainability in the electricity sector. For this, a systematic literature review using the PRISMA protocol was employed as the methodological approach. In this review, 154 journal articles were thoroughly analyzed. The results were grouped according to the themes and categorized into energy efficiency, renewable energies, and energy and urban planning. The study findings revealed the following: (a) global academic publication landscape for smart city and energy sustainability research;(b) unbalanced publications when critically evaluating geographical continents’ energy use intensity vs. smart cities’ energy sustainability research outcomes;(c) there is a heavy concentration on the technology dimension of energy sustainability and efficiency, and renewables topics in the literature, but much less attention is paid to the energy and urban planning issues. The insights generated inform urban and energy authorities and provide scholars with directions for prospective research.
ABSTRACT
Artificial intelligence (AI) is a powerful technology that can be utilized throughout a construction project lifecycle. Transition to incorporate AI technologies in the construction industry has been delayed due to the lack of know-how and research. There is also a knowledge gap regarding how the public perceives AI technologies, their areas of application, prospects, and constraints in the construction industry. This study aims to explore AI technology adoption prospects and constraints in the Australian construction industry by analyzing social media data. This study adopted social media analytics, along with sentiment and content analyses of Twitter messages (n = 7906), as the methodological approach. The results revealed that: (a) robotics, internet-of-things, and machine learning are the most popular AI technologies in Australia;(b) Australian public sentiments toward AI are mostly positive, whilst some negative perceptions exist;(c) there are distinctive views on the opportunities and constraints of AI among the Australian states/territories;(d) timesaving, innovation, and digitalization are the most common AI prospects;and (e) project risk, security of data, and lack of capabilities are the most common AI constraints. This study is the first to explore AI technology adoption prospects and constraints in the Australian construction industry by analyzing social media data. The findings inform the construction industry on public perceptions and prospects and constraints of AI adoption. In addition, it advocates the search for finding the most efficient means to utilize AI technologies. The study helps public perceptions and prospects and constraints of AI adoption to be factored in construction industry technology adoption.
ABSTRACT
The popularity and application of artificial intelligence (AI) are increasing rapidly all around the world—where, in simple terms, AI is a technology which mimics the behaviors commonly associated with human intelligence. Today, various AI applications are being used in areas ranging from marketing to banking and finance, from agriculture to healthcare and security, from space exploration to robotics and transport, and from chatbots to artificial creativity and manufacturing. More recently, AI applications have also started to become an integral part of many urban services. Urban artificial intelligences manage the transport systems of cities, run restaurants and shops where every day urbanity is expressed, repair urban infrastructure, and govern multiple urban domains such as traffic, air quality monitoring, garbage collection, and energy. In the age of uncertainty and complexity that is upon us, the increasing adoption of AI is expected to continue, and so its impact on the sustainability of our cities. This viewpoint explores and questions the sustainability of AI from the lens of smart and sustainable cities, and generates insights into emerging urban artificial intelligences and the potential symbiosis between AI and a smart and sustainable urbanism. In terms of methodology, this viewpoint deploys a thorough review of the current status of AI and smart and sustainable cities literature, research, developments, trends, and applications. In so doing, it contributes to existing academic debates in the fields of smart and sustainable cities and AI. In addition, by shedding light on the uptake of AI in cities, the viewpoint seeks to help urban policymakers, planners, and citizens make informed decisions about a sustainable adoption of AI.
ABSTRACT
Background and objectives: Due to COVID-19, various countries introduced lockdowns and limited citizen movements. These restrictions triggered an increased use of digital technologies and platforms by the public. This provides an opportunity for the authorities to capture public perceptions on COVID-19 from social media channels to make informed decisions. The use of social media analytics during pandemics for decision-making, however, is an understudied area of research. Thus, this study aims to generate insights into how social media analytics can assist authorities in pandemic-related policy decisions.Methods: This study involved a social media analysis approach—i.e., systematic geo-Twitter analysis—that contains descriptive, content, sentiment, and spatial analyses. Australian states and territories are selected as the case study context for the empirical investigation. This study collected 96,666 geotagged tweets (originated from Australia between 1 January and 4 May 2020), and analysed 35,969 of them after data cleaning.Results: The findings disclose that: (a) Social media analytics is an efficient approach to capture the attitudes and perceptions of the public during a pandemic; (b) Crowdsourced social media data can guide interventions and decisions of the authorities during a pandemic, and; (c) Effective use of government social media channels can help the public to follow the introduced measures/restrictions.Conclusion: The findings are invaluable for authorities to understand community perceptions and identify communities in needs and demands in a pandemic situation, where authorities are not in a position to conduct direct and lengthily public consultations.