Optimizing Blockchain Based IoT Integration for Sustainable Mobility in Smart Cities - Aan Kanivia; Ariesya Aprillia; Kamal Arif Al-Farouqi; Ria Sari Pamungkas (IAIC Bangun Bangsa, 2025)
This research highlights the critical role of Internet of Things (IoT) technology and data analytics in fostering sustainable mobility within the Smart City concept. The primary objective is to examine how IoT sensors and real-time data analysis can optimize transportation efficiency while promoting environmental sustainability. The proposed Method involves integrating IoT sensors across urban infrastructure to collect realtime data on traffic patterns, air quality, and travel behavior, which is then analyzed using advanced data analytics techniques. The gap addressed in this study lies in the limited empirical evidence regarding the practical implementation of IoT and data analytics in improving urban mobility and environmental outcomes. The novelty of this research is in developing a predictive model that leverages IoT data to optimize public transportation routes, reduce congestion, and lower carbon emissions. Preliminary results suggest significant benefits, including a 25% reduction in emissions and a 40% increase in travel efficiency, demonstrating the potential of IoT-driven analytics in transforming urban mobility. The findings of this study contribute to a deeper understanding of sustainable transportation solutions within smart cities, offering a data driven approach to enhance public transportation networks and minimize environmental impact, ultimately paving the way for a more efficient and eco friendly urban ecosystem