The emergence of smart cities has addressed many critical challenges associated with conventional urbanization worldwide. However, sustainable traffic management in smart cities has received less attention from researchers due to its complex and heterogeneous nature, which directly affects smart cities’ transportation systems. The study aimed at addressing traffic-related issues in smart cities by focusing on establishing a sustainable framework based on the Internet of Things (IoT) and Intelligent Transportation System (ITS) applications. To sustain the management of traffic in smart cities, which is composed of a hybridized stream of human-driven vehicles (HDV) and connected automated vehicles (CAV), a dual approach was employed by considering traffic as either modeling- and analysis-based, or/and the decision-making issues of previous research works. Moreover, the two techniques utilized real-time traffic data, and collected vehicle and road users’ information using AI sensors and ITS-based devices. These data can be processed and transmitted using machine learning algorithms and cloud computing for traffic management, traffic decision-making policies, and documentation for future use. The proposed framework suggests that deploying such systems in smart cities’ transportation could play a significant role in predicting traffic outcomes, traffic forecasting, traffic decongestion, minimizing road users’ lost hours, suggesting alternative routes, and simplifying urban transportation activities for urban dwellers. Also, the proposed integrated framework adopted can address issues related to pollution in smart cities by promoting public transportation and advocating low-carbon emission zones. By implementing these solutions, smart cities can achieve sustainable traffic management and reduce their carbon footprint, making them livable and environmentally friendly.

With recent and unprecedented attention toward the implementation of Energy efficient building which aids in advocating sustainable construction, numerous attempts have made in establishing flexible approaches to which these practices will assist in savings cost of construction, improve the quality of indoor air as well as lowering the GHG emissions. However, the system is lacking proper and standardized methodology of implementations. Therefore, this, study dwelt in examining several factors capable of influencing the application of energy conservation practices in buildings, along with the advantages and barriers for implementation based on existing literatures, which focuses on raising awareness, providing information, implementing proper policies, and creating incentives to provide alternative solutions for building owners. As presented, study's outcomes offer a blueprint for comprehending the nuanced dynamics of building energy efficiency and lay out a clear course for further investigation. The study also, identifies significant factors which majorly influences building energy efficiency which include government supervision, design standards, construction quality, and energy-efficient materials. The study recommends utilizing cutting-edge innovations, building automation systems, and IoT devices to improve energy monitoring and conservation.