Big Data Analytics and Machine Learning for Secure and Flexible Mobile Service towards Smart Utilities

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The proliferation of smart utilities has revolutionized the way we manage essential services such as energy, water, and transportation. Mobile technologies play a pivotal role in delivering these services efficiently. However, the sheer volume of data generated by these systems poses significant challenges in terms of security, flexibility, and overall performance. This research explores the synergy of Big Data Analytics and Machine Learning (ML) to address these challenges. We investigate how these technologies can enhance the security of mobile service infrastructures in smart utilities, ensuring the protection of sensitive data and safeguarding against cyber threats. Moreover, we explore the potential of ML algorithms to adapt and optimize mobile service delivery, ensuring flexibility in response to changing demands and environmental conditions. The study leverages real-world data from smart utility deployments, applying advanced analytics techniques to extract valuable insights and patterns. These insights enable the development of proactive security measures and the creation of flexible, adaptive mobile service models. By harnessing the power of Big Data Analytics and ML, we aim to create a foundation for smarter, more secure, and highly responsive mobile services in the context of smart utilities, ultimately contributing to the sustainable development of smart cities and communities.