Professor Saifur Rahman


Title: Energy Efficiency in Smart Buildings through IoT Sensor Integration

Abstract: Internet of Things (IoT) deployments offer a much higher value proposition if these can function in the context of smart buildings. Such advanced information and communication technology (ICT) applications in commercial buildings, schools, libraries, shopping centers, etc. offer low cost but highly effective monitoring and control opportunities. Sensors deployed in key locations can monitor the building environment in real-time, collect information for intelligent decision making, and facilitate various services. An IoT sensor platform has been developed that provides a unified communication platform which can integrate information from disparate sources and provide one control hierarchy. It is a powerful, low-cost, open-architecture software platform that can monitor and control major electrical loads (e.g., HVAC, lighting and plug loads), as well as solar PV systems, energy storage units and other IoT sensors in commercial buildings. The platform can provide new or legacy buildings with a building automation system (BAS) or connect with existing BAS systems in large and small commercial buildings. This platform leverages machine learning algorithms to draw insights from a deployed building’s historical operating data and occupant preferences to save energy (kWh) while increasing occupant comfort. This also allows buildings to reduce peak demand (kW) through direct communication with utilities using demand response protocols such as openADR.

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Professor Kai Sang LOCK

Affiliation: Professor (Engineering) & Head, Energy Efficiency Technology Centre, Singapore Institute of Technology

Emeritus President, Institution of Engineers, Singapore, Deputy Chair, the Washington Accord

Title: Ethics and Sustainability Education in
Information and Communication Technology Programmes


This paper examines and argues for the need to emphasize ethics and sustainability education in information and communication technology programmes.

Information and communication technology, together with AI, is driving the world for the next wave of economic revolution by building on 5G networks and the massive data being generated, combined, processed and exploited in areas such as IoT, e-business, industry 4.0, intelligent transportation systems, healthcare and wellness, and the smart cities. The huge impact of ICT on national security and the privacy and safety of the general public demand ethical considerations in the design and application of ICT infrastructure.
Even under the present covid-19 pandemic, data centres are mushrooming around the world to accompany the explosive growth in ICT infrastructure. Data centres are recognized as the world’s greatest energy guzzles and are contributing to challenges in sustainability. Engineers have the responsibilities to design energy-efficient data centres and ICT infrastructure. ICT education programmes should inculcate Green Computing which encompasses all facets of computing lifecycle from the design and manufacturing of computing hardware to software architecture, materials utilization and recycling, system operation and management. The major objectives are to achieve high energy efficiency in computing resources to ensure environmental and economic sustainability.

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Dr. Mohammad S. Alam

Affiliation: Fellow – IEEE, IET, OSA, SPIE, IoP, IS&T, IAPR, and AAAS
Professor and Dean, Frank H. Dotterweich College of Engineering
Texas A&M University – Kingsville, Texas, USA

On April 20, 2010 the BP Deepwater Horizon drilling rig in the Gulf of Mexico exploded releasing 206 million gallons of crude oil contaminating the Gulf and 665 miles of coastlines. The oil and gas volumes released from this accident are the largest in US history and have resulted in catastrophic impacts on environment, ecological balance, marine life, regional industry and economy. Characterizing the distribution, composition and ecosystem interactions of the oil is essential to understanding the long term consequences of this and future oil spills. This incident cost billions of dollars in economic losses while billions were used for clean-up efforts as well as environmental and economic recovery.
Many techniques exist to identify and track oil slick and to aid in the clean-up and mitigation efforts. However, most of these methods are limited in scope and cover very small areas. Remote sensing techniques, such as hyperspectral imaging (HSI), is a fast and effective way to capture oil spill information over a vast region of interest encompassing several hundred square miles. HSI provides spatial and time-resolved measurements of the composition and distribution of emissive, reflective or transmissive sources for ground, water, atmospheric or space applications. Hyperspectral sensors can record over 300 selected wavelengths of reflected and emitted energy. Because both spectral and spatial information are obtained, HSI sensors provide a three-dimensional data cube. By extracting all pixels in a single ground resolution cell as a function of wavelength, one can obtain the spectral signature for that cell. However, by extracting all the pixels in the same spectral band, one can obtain a 2D intensity image showing the spatial distribution of reflectance values of the scene for that particular wavelength. By analyzing the spectral signature of oil or oil-derived substances one can detect minute concentrations of hydrocarbon on the surface, subsurface and other areas of interest.
Detailed analytical modelling and robust algorithms were developed to identify potential regions-of-interest and classify the oil and/or oil derived substances at the surface and sub-surface levels. Test results using real life hyperspectral imagery available from various agencies (e.g. NASA Jet Propulsion Lab) will be presented to verify the effectiveness of the proposed techniques.

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