Prof. Rajan Jose
Universiti Malaysia Pahang
Research Area：Renewable Energy Materials & Devices
Title：Electrospun Flexible Energy Devices
Smart textiles are a convenient platform to deploy electromechanical systems and internet of things (IoT); thereby making the textile electronics as a fast-growing industry with a predicted global market of US$ 9.3 billion by 2024. The smart textiles integrate the state-of-the-art electronic gadgets such as sensors, actuators, controllers, displays, and others in consumer clothing; and powering these gadgets is a critical issue. One of the most viable approaches to power the smart textiles electronics is to develop energizers (solar cells, piezoelectric cells, batteries and supercapacitors) into the fundamental constituent of the cloth, for example, fibers (or synonymously yarns) as energy conversion and storage system. This lecture will focus on the current state of flexible energy devices developed by electrospinning, both in the lecturer’s laboratory and elsewhere, and foreseeable initiatives required to leverage the laboratory developments to the commercial sector. Of particular interest will be supercapacitors, perovskite solar yarns, and piezoelectric yarns.
Prof. Zhou Wu
Chongqing University, China
Title: Building energy efficiency retrofit: artificial intelligence and informatics approaches
Abstract: Reducing energy consumption of buildings can effectively reduce global energy demand and carbon emission, so green buildings are widely concerned in the energy professionals. Energy efficient retrofit of old building is an important means to improve green performance. The difficulty of building energy efficient retrofit (BEER) is the optimization of retrofit and maintenance schedules, which aim to minimize the economic cost and maximize the energy saving. Compared with energy control and dispatch tasks, BEER needs more support from Internet of things and big data. Using artificial intelligence (AI) and data mining techniques, optimal decision of building life cycle can be made. The study mainly introduces the latest results of information theory in BEER with respects to modeling, optimization, control, and game theory. In addition, based on the requirements of different dimensions, such as single-task, multi-task, static and dynamic, certain innovative AI algorithms are proposed.