Characterized as one of the key technologies contributing to the so-called "digital evolution", modern wireless sensor network (WSN) platforms are endowed with the ability to create networked artifacts (human and non-human) to sense their environment, and accordingly adapt their behavior in beneficial manners. The potential applications are numerous, including effective monitoring and sustainable governance in structural health, disaster relief, transportation, law enforcement, and public safety and security.
A major rationale for these WSN technologies is that they can enable the users to make decisions in a "smarter", more "aware" and "responsive" manner. Indeed, a distributed monitoring capacity gives us a "novel" visualization of our environment that allows more effective planning: the ability to respond in a more timely fashion, and to develop more effective actions to resolve environmental problems. The social and economic implications can be enormous, for not only public but also private organizations. Evidently, this technological innovation impacts many aspects of human life: health and safety, information and communications, energy and environment, as well as security, to name a few.
However, while there are irrefutable advantages to be reaped with the WSN infrastructures, these strategic values are not without caveats. On the one hand, the larger a sensor network becomes, the smarter and more responsive we become, as our visualization becomes more global and informative. On the other hand, as the size of the network increases, so do the associated complexity and management. To facilitate deployment and acceptance of such networks, the network sensors must be inexpensive, non-intrusive, and communicate effectively. Together, these conditions imply two fundamental requirements that influence the operation of the network: scalability and sustainability. Without these two requirements, the operation and impact of the WSN would be questionably limited, if not short-lived.
Proposed Solutions: A High-Level Overview
Motivated by the WSN tremendous potentials, coupled with the technological limitations affecting the current WSN platforms as described above, a multidisciplinary team of researchers at the University of Toronto and our industrial partners have endeavored to address the challenges from various perspectives, in order to deliver a complete WSN platform. In fact, under the aegis of the Ministry of Research and Innovation of Ontario, the objective of our Ontario Research Fund Self-Powered Sensor Networks (ORF-SPSN) project is to develop scalable, low power, wireless sensor systems, for a wide range of applications. While substantial benefits are primarily targeted for the citizens of Ontario and the general Canadian society, the technical merits of the proposed engineering solutions are also applicable to similar scenarios worldwide, thus fulfilling the motto of "designed in Ontario, ready for the world".
The proposed solutions comprise a number of key technological areas conducive to a successful WSN platform: novel sensor, data aggregation and energy harvesting technologies for ubiquitous and sustainable indoor/outdoor deployment. The ORF-SPSN consortium will develop compelling materials, communication architectures, software, and other critical technologies necessary to create ubiquitous, ad hoc, WSN platforms that are both technologically sound and economically feasible. The problems to be investigated by the ORF-SPSN consortium can be grouped into the following three high-level categories.
Sensor construction: hardware and devices with high fault tolerance, nano-enabled materials for flexible and low-cost operations; optical, electrochemical and biological sensing techniques, including a quantum dots composite based architecture.
Communication and data aggregation architecture: underlying network topologies and protocols for routing and transmitting the sensed data to various destinations; software and middleware for the extraction, processing, and characterization of real-time sensed data.
Energy harvesting and storage infrastructure: energy conserving, capture and storage systems, with innovative nanoscale materials, for delivering renewable energy resources to sustain autonomous sensor networks.
These solutions seek to address the scalability and sustainability factors, which have thus far eluded the current WSN platforms, in a comprehensive and methodical manner. In a nutshell, the proposed sensor, software and energy harvesting technologies in this ORF-SPSN project "make the life of WSN long and prosperous".
For each of the above categories, the multidisciplinary team of researchers at the University of Toronto is ready to provide the technical know-how and experience to deliver effective and practical solutions. Indeed, with experts in electronic communications, computer science, biochemistry, energy systems, material science, as well as nanotechnology, the challenges involved can be investigated and overcome with not only a sound theoretical basis, but also a feasible implementation framework for eventual product commercialization, in conjunction with our industrial partners.
As the project progresses, various specific application scenarios of the ORF-SPSN platform will be explored. Feel free to visit the Current Applications section, for more specific descriptions of the problems envisioned and methods investigated. You can also browse our Publications section to potentially discover methods and results germane to your own research projects. And do not hesitate to Contact Us for further details or knowledge exchange on the exciting field of WSN research!
Wireless sensor networks, irrespective of the applications or the target area they are monitoring, are typically characterized by limited energy and capacity resources. Optimization and control of the network topology along with proposition of energy- efficient protocols at the network and MAC layer play a critical role in extending the network lifetime, which is of prime importance in situations where node replacement is either undesirable (due to cost constraints) or practically infeasible. Our aim is to address this issue of topology control in sensor networks. More specifically, we wish to take into account the physical layer parameters such as received power at the radio receiver of a node to get the underlying path loss model. Traditional topology control algorithms are based on the free space model and the more complicated models due to multipath refelections/fading effects (such as small scale, large scale fading) are often neglected. With the help of Wireless module and the Terrain Modeling Module of Opnet, we will take into account the effects of propagation modeling on the problem of topology control.