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Machine Learning Approach for Smart City Development

A Comprehensive Study on IoT Integration and Data Analytics

Penulis: Dr. Ahmad Sutanto, Prof. Sri Wahyuni, M.Eng, Dr. Bambang Priyanto

Informasi Konferensi

Konferensi: International Conference on Information and Communication Technology (ICICT)

Tanggal: 2024-10-15

Lokasi: Jakarta, Indonesia

Penyelenggara: IEEE Indonesia Section

Publisher: IEEE

Halaman: 123-130

IEEE Xplore Scopus Web of Science

Abstrak

Abstract

This paper presents a comprehensive study on the application of machine learning techniques in smart city development through IoT integration and data analytics. The research focuses on developing efficient algorithms for urban data processing, real-time decision-making systems, and predictive analytics for city management.

Key Contributions:

  • Novel machine learning framework for smart city data processing
  • IoT integration architecture for real-time urban monitoring
  • Predictive analytics model for traffic and energy management
  • Case study implementation in Jakarta smart city initiative

The experimental results demonstrate significant improvements in urban resource management efficiency, with 25% reduction in traffic congestion and 30% improvement in energy consumption optimization.

Kata Kunci

machine learning, smart city, IoT, artificial intelligence, data analytics, urban computing

Info Singkat

Jenis Presentasi: oral

Peringkat Konferensi: A

Bidang: Machine Learning, IoT, Smart City, Data Analytics

Sitasi: 15

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