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@article{206591,
        author = {Dhyan and Hithesh and K Mohammed Mudassir and M. Prajwal and Nagaraj Hebbar N},
        title = {Smart Local Service Aggregator},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {no},
        pages = {60-65},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=206591},
        abstract = {The accelerating pace of urban expansion has placed mounting pressure on city administrators to deliver services that are not only accessible but also operationally coherent. Transportation networks, utility systems, and public services have traditionally been managed through isolated platforms, a fragmentation that routinely produces bottlenecks, coordination failures, and underutilised resources. This paper introduces the Smart Local Service Aggregator — a consolidated digital platform engineered to unify these disparate services under a single, manageable architecture. The system draws on IoT-enabled sensing for live data acquisition, cloud-based transmission infrastructure for reliable connectivity, and intelligent computational methods for processing and analysis. Consolidating services within one framework reduces administrative overhead, sharpens monitoring capability, and gives urban management the scalability it increasingly demands. The paper further explores how embedding machine learning and blockchain technologies into this infrastructure can advance automation, harden security, and sustain long-term system dependability in smart urban environments.},
        keywords = {Blockchain, Cloud Computing, Internet of Things (IoT), Machine Learning, Smart City, Smart Local Service Aggregator},
        month = {July},
        }