Selected Technology Cluster Research Projects

This research leverages our recent work in the active RFID traceability technologies. Our system is developed with the capability to determine the indoor location of an active tag. This system was installed inside two wards (11A & 11C) of Prince of Wales Hospital for a 4-month formal pilot study with patient and medical staff participation to improve patient care.

Based on the user feedbacks collected, we find that time and space play an important role in shaping human behaviors, inferring human interactions, and influencing epidemic spread of infectious diseases in a healthcare institute. Our research aims at enhancing the capability of tracking the movement of people and tracing the infection of a hospital-acquired disease for each individual in order to monitor and control the epidemic spread of nosocomial infections. To achieve this goal, we plan to conduct the following research activities:

• network models of dynamic human behaviors for an enhanced spatial-temporal analysis to determine human interaction patterns and contacts in a relatively close community,
• epidemic models to track and trace nosocomial infections based on the time-varying contact networks to increase our understanding of transmission mechanisms in hospital,
• traceability analysis of tracking the mobility and infection for each individual to identify risk behaviors by linking both the network and epidemic models,
• effective and efficient control strategies against epidemic spread under different scenarios to take advantage of the network structure and disease dynamics.

This research is unique. First, since our focus is on the movement of people, our methods are very different from those used to track products in a supply chain. Further, we plan to conduct the traceability analysis of the dynamic interactions and infections of people at individual level for network epidemiology study in hospital. This differs from either the popular modeling of a static network or the traditional epidemiology study for a large region. Finally, many spatial-temporal analyses and epidemiology models are developed for outdoor applications while this work deals with indoor activities.

The Tree Guard Monitoring System will make use of various sensor technologies to continuously monitor tree statuses and detect for any abnormal activity being done to a tree, like sawing and hammering. In addition, the TGMS will utilize various wireless technologies to form a scalable wireless mesh network for transmitting various sensor data to a control server. The control server will further analyze the incoming sensor data and determine whether to issue a warning signal to corresponding management and operation parties. Moreover, historical data will be analyzed for deriving activity patterns to improve the detection accuracy as well as establish preventive or predictive measures to safe guard those trees.

The project will develop the hardware devices having sensing and wireless communication capabilities for being attached to trees. Each device will be capable of synthesizing various streams of sensor data to detect abnormal activities. The project will also develop the data communication protocols to support various communication transmissions between different components in the mesh network. Monitoring and analytics software will be developed to convert sensor information into warning signals.

The reason of our focus on uncertainty and risk is the increasing importance of robust planning and robust investment decisions in the modern telecommunication environment. Traditional telecommunication networks were dominated by public monopolies which provided only a few mature services with fairly predictable user demand. Unfortunately, this predictability is a feature of the past! Due to the fast evolution of modern high speed networks, deregulation, quick development of new services with shorter life cycle, unpredictable user response to introduction of new services, modern networks operate in the presence of substantial uncertainty. The emergence of a multitude of new actors, which assume new roles and engage in complex relations of competition and collaboration, further complicates the situation and compounds the risks. Traditional planning methods are not adequate for design of networks in this new environment due to their essential lack of capability to treat this instability and uncertainty. New planning methods are needed which would facilitate design of robust networks. These networks will be able, within reasonable bounds, to absorb unpredictable user reaction to new services, technological change and other uncertainties without consuming unreasonable amount of critical resources. Our aim is to develop planning tools for design of robust networks using the latest developments in optimization technology integrated with some ideas developed recently for evaluation of industrial projects. These tools will be useful both for industrial actors and for governmental regulatory bodies.