Smart systems and data-driven services have witnessed notable advancement in today's fast-paced and interconnected world. They have become the driving force of a wide range of industries, boosting their efficiency and intelligence. The convergence of cutting-edge technologies and data-driven algorithms has led to an era of unprecedented opportunities and transformative innovations. Their powerful solutions utilize big data to deliver intelligent services for a particular domain, such as "Sustainable Smart Cities".  

This research topic explores the role of machine learning and data analytics in shaping smarter and more sustainable cities. In these sustainable smart cities, data science helps city planners make better decisions to address several issues by analyzing information from sensors and devices. Consequently, cities can provide several smart and efficient services, such as smart agriculture, smart energy, smart health, and smart transport.

Specifically, the student's task is to investigate and utilize data science methods and techniques to enhance and support the data-driven services of sustainable smart cities.

Required skills:

• Basics of Python programming language.
  • Proficiency in one or more of the following Python libraries: (Pandas, NumPy, Matplotlib, Tslearn, Keras, TensorFlow, and Scikit-learn).
• Theoretical basics of Data Analytics and Machine Learning.