The world we live in has become increasingly digital, interconnected, distributed and intelligent (DIDI). It is projected that by 2030, 75% of the world’s population would have mobile connectivity and 60% with broadband access. Every facet of our lives from energy, transport, communication and multimedia systems, health, education, commerce and scientific discovery will be closely linked by sensors of all kinds. Ubiquitous sensors will govern communications devices, smart cloths, houses, automobiles and drones. These sensors, the Internet of Things (IoT), Industry 4.0, and new 5G/6G cellular communication technologies will generate data sets of a magnitude that are difficult to handle due to increasing volume, velocity, variety, and veracity. Multiplication of big data will affect and transform the whole of society. The ability to collect, store and control these data will be regarded as an essential resource for the economies and societies of the future. The availability of big data has driven both the development of and the need for Artificial Intelligence (AI). The Internet of Things, big data analytics and storage, artificial intelligence and machine learning tools will enable the emergence of smart machines that will be increasingly adjustable through sensor technologies, cheap computing power and the real-time use of algorithms.

Under the DIDI environment, security and privacy are critical risks. Hackers may be able to remotely take over connected objects, such as the electricity grid and driverless cars, or manipulate IoT-generated data. The reliability of the network is a major issue, since human lives may depend on successful, sometimes real-time transfers of data. The key issue of consent and perhaps the notion of privacy itself are also challenged by the near-continuous flow of sensitive data that the billions of ubiquitous sensors will produce.

The research in this thrust is imperative as we strive to extract information from large amount of unstructured data produced by ubiquitous sensors and systems to make prediction and decision, while preserving security and privacy in the DIDI society. Research within this thrust draws on foundational strengths in Big Data Analytics & Data Science, Artificial Intelligence (AI) & Machine Learning, Computer Vision & Video Analytics applications, Advancing Sensing Technologies, Cyber & Network Security, Positioning & RF Technologies, Communication & Network Systems, Massive Data Storage, and Urban Environment Analytics. Currently, the thrust has 37 affiliated faculty, 85 research staff and 91 graduate students and 10 laboratories comprising Centre for Information Sciences and Systems (CISS), Smart Nation Translational Lab (SNTL), Communication Research Lab I, Communication Research Lab II, Connected Smart Mobility Lab, Digital Signal Processing Lab, Information Systems Research Lab, Media Technology Lab, ROSE (Rapid-Rich Object Search) Lab, and SHARE (Schaeffler Hub for Advanced REsearch at NTU) Lab.