Intelligent Sensing and Sense Making

Overview

Sensor and sensing technology has emerged as the primary enabling technology for a wide range of applications over the past decades, and will continue to contribute to be the core component of future technologies, such as multimedia systems, Internet of Things, control system, as well as cross-disciplinary applications with pattern recognition and artificial intelligence.

Course Description & Learning Outcomes

This intelligent sensing and sense making course presents the core theory and algorithms of signal processing fundamentals, and practical signal processing skills and strategies for real-world industrial implementations through workshop sessions. In this 4-day course, participants will learn two key skills: (i) Performing analysis of sensor data using spatial filtering and frequency and statistical analysis; (ii) Building Intelligent systems that utilise advanced signal and sensor data processing. At the end of this course, students will be able to build intelligent systems such as smart machine diagnostic systems, smart healthcare monitoring systems, etc. This course is part of the Artificial Intelligence and Graduate Certificate in Pattern Recognition Systems Series offered by NUS-ISS. At the end of the course, the participants will be able to: - Identify needs of intelligent sensing technology in various industrial applications; - Acquire knowledge of core intelligent sensing theories, analyse various signal processing models and algorithms; - Design, apply and evaluate the performance of various intelligent sensing and sense making techniques.

Recommended Prerequisites

- Previous knowledge of signal processing will be helpful - Participants should have intermediate skills in Python programming (e.g. Numpy, Pandas), and intermediate knowledge in machine learning (e.g. building a neural network model in Keras/Tensorflow). - Intermediate mathematics and statistics knowledge, e.g. linear algebra, probability.

Pre-course instructions

- No printed copies of course materials are issued. - Participants must bring their internet-enabled computing device (laptops, tablet etc) with power charger to access and download course materials. Registration close date: 02/09/2023