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All Journal JURNAL EDUCATION AND DEVELOPMENT Blockchain Frontier Technology (BFRONT)
Ariesya Aprillia
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Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Education Languange, Linguistic, Communication & Media Library & Information Science

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Journal : Blockchain Frontier Technology (BFRONT)

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Optimizing Blockchain Based IoT Integration for Sustainable Mobility in Smart Cities Ria Sari Pamungkas; Aan Kanivia; Ariesya Aprillia; Kamal Arif Al-Farouqi
Blockchain Frontier Technology Vol. 4 No. 2 (2025): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/bfront.v4i2.710

Abstract

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
Adaptive Workflow Management with Decentralized AI in Blockchain Based Distributed Ledger Systems Tessa Handra; Ninda Lutfiani; Ariesya Aprillia; Fitra Putri Oganda; Fhia Amelia; Noah Rangi
Blockchain Frontier Technology Vol. 5 No. 1 (2025): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/bfront.v5i1.804

Abstract

Blockchain technology has rapidly evolved as a decentralized solution offering high security and transparency; however, several challenges still hinder the effective management of workflows within blockchain based environments. This study aims to develop an adaptive workflow management model that utilizes decentralized artificial intelligence (AI) and distributed ledger technology (DLT) to enhance the performance, security, and flexibility of processes in blockchainn networks. A mixed method approach combining simulation and experimentation on a dedicated blockchain platform was employed. The adaptive workflow model consists of a realtime process monitoring module, a decentralized AI module for adaptive decision making, and a DLT component that ensures data consistency and security. Statistical methods and system performance evaluations were used to analyze the experimental data. Results show that the proposed model can reduce workflow response times by up to 25% and increase the successful execution rate of smart contracts to 98%. Moreover, the integration of decentralized AI optimizes workload distribution across nodes, enabling network scalability improvements of up to 150% without significant performance degradation. The findings demonstrate that the adaptive workflow model combining AI and DLT enhances the flexibility and governance of blockchain networks through AI’s predictive capabilities and DLT’s security. Nevertheless, challenges such as high computational resource demands and technical complexities must be addressed. This research opens opportunities for further development to expand the scope of complex and dynamic blockchain applications and supports their integration with technologies like the Internet of Things (IoT).
Co-Authors Aan Kanivia Fhia Amelia Fitra Putri Oganda Kamal Arif Al-Farouqi Kevin Cahyadi Ninda Lutfiani Noah Rangi Nonie Magdalena Ria Sari Pamungkas Rizky Kusumah Rony Setiawan Steven Daniel Tessa Handra Tessa Handra