Latest News

30 ACEIoT students enhance machine learning skills for internet of things research

30 ACEIoT students enhance machine learning skills for internet of things research

Thirty postgraduate students from the African Centre of Excellence in Internet of Things (ACEIoT) have completed a four-day intensive seminar on applying machine learning to Internet of Things (IoT) research.

The training was facilitated by Prof. Christopher Thron from Texas A&M University–Central Texas and aimed at equipping students with practical skills to integrate machine learning techniques into their research projects.

The seminar was designed to strengthen participants’ capacity to analyze data, develop intelligent IoT solutions, and apply modern machine learning tools to address real-world challenges across various application domains.

Throughout the training, participants gained hands-on experience using Python for data visualization, exploration, and characterization. They also learned how to build machine learning pipelines for evaluating and comparing different machine learning models using real datasets, enabling them to identify the most suitable approaches for specific research problems.

A key component of the seminar introduced participants to deep learning using TensorFlow, Google’s open-source machine learning framework. Through practical exercises, students learned how to design, train, and optimize neural networks for classification and prediction tasks.

The training featured real-world use cases from diverse fields, including image analysis and natural language processing, demonstrating how machine learning can be applied to solve complex problems using IoT-generated data.

They gained skills like to load, visualize, and interpret time-series sensor data from distributed IoT stations, interpret detection performance using F1-score, precision, and recall and applying these techniques to GPS spoofing detection in a maritime environment.

In addition to practical sessions, participants explored the theoretical foundations of machine learning, gaining a deeper understanding of the mathematical concepts that underpin modern artificial intelligence techniques.

The seminar forms part of ACEIoT’s ongoing commitment to strengthening advanced digital skills, promoting high-quality research, and preparing postgraduate students to develop innovative, data-driven solutions that contribute to Africa’s technological advancement and sustainable development.

The Centre takes this opportunity to express its sincere appreciation to Prof. Christopher Thron for his valuable contributions to the Centre.