Is the sky of smart city bluer? Evidence from satellite monitoring data

Is the sky of smart city bluer? Evidence from satellite monitoring data.

Air pollution is a major issue all over the world because of its impacts on the environment and human beings. The present review discussed the sources and impacts of pollutants on environmental and human health and the current research status on environmental pollution forecasting techniques in detail; this study presents a detailed discussion of the Artificial Intelligence methodologies and Machine learning (ML) algorithms used in environmental pollution forecasting and early-warning systems; moreover, the present work emphasizes more on Artificial Intelligence techniques (particularly Hybrid models) used for forecasting various major pollutants (e.g., PM2.5, PM10, O3, CO, SO2, NO2, CO2) in detail; moreover, focus is given to AI and ML techniques in predicting chronic airway diseases and the prediction of climate changes and heat waves.The hybrid model has better performance than single AI models and it has greater accuracy in prediction and warning systems. The performance evaluation error indexes like R2, RMSE, MAE and MAPE were highlighted in this study based on the performance of various AI models.

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Artificial Intelligence Technologies for Forecasting Air Pollution and Human Health: A Narrative Review

With the world’s rapidly growing urbanization, urban sustainability is now expected for urban life. Due to this rapid growth, meeting the emerging challenges for urban management and sustainability worldwide is challenging. Big data-driven technologies can be an excellent solution to address these upcoming challenges. Therefore, this study explores the potential of big data technologies for ensuring sustainability in urban management. The study conducted a systematic literature review guided by PRISMA (preferred reporting items for systematic review and meta-analysis) on publications over the last 21 years. The study argues that urban management is an integrated function of public and private agencies to address the significant challenges of urban life and to develop the city as more competitive, habitable, and sustainable. Urban management can utilize big data analytics (BDA) for digital instrumentation, data-informed policy decisions, governance, real-time management, and evidence-based decisions. Urban sustainability can ensure the smooth operation of urban affairs through strategic planning under three major dimensions: social, economic, and environmental. Big data technologies can ensure smart transport, traffic, waste management, energy, environment, infrastructure, safety, healthcare, planning, and citizen participation in regular urban affairs to provide a better urban life. This study develops several indicators that will be helpful for concerned stakeholders in policy, planning, designing, and implementing sustainable urban development.

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Kenyon Chow

Papers

A Big Data and Artificial Intelligence Framework for Smart and Personalized Air Pollution Monitoring and Health Management in Hong Kong