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SENSIBLEIntegrating SENSing & Processing

Researcher: Diana Marculescu


SENSIBLE - Integrating SENSing and ProcessIng in ConformaBLE Substrates for Security Applications

Given current technology and social drivers, the interface between the virtual and natural worlds will need to be completely revisited. To become truly ubiquitous, pervasive, and inconspicuously embedded in human environments, we envision computing, sensing and actuation devices as being embedded in unconventional conformable substrates (fabric-based or flexible). Such systems will be able to sense, evaluate and react based on different environmental or user changes, while at the same time providing a friendly and familiar interface that humans use in their everyday life (clothing or soft furnishings). Flexible substrates can also be designed to accommodate the constraints imposed by the ambient environment in which the user interacts, i.e., different climates or harshly operating conditions (e.g. firefighter or first responder personnel suits). At the same time, smart surroundings could provide humans with intelligent services and safe environments, without privacy intrusion or unfriendly interfaces.

Most automated security and surveillance systems in current commercial and household settings involve the installation of several individual electronic devices throughout a given area of interest. These devices, such as video cameras, proximity sensors and motion detectors, are each assigned to safeguard a specific locality. Although there have been vast improvements in their design to make them tamper proof, in most cases, these security systems remain very much dependent on a single or selected few devices responsible for the monitoring a specific area.

The aim of the proposed research is to enable the inconspicuous and dependable integration of sensors into “smart buildings” or “smart environments” that are able to safeguard themselves. The focus of our project is to create an integrated system of large area sensing processing and visual feedback, using conformable substrates comprised of a network of computational devices and sensors that can be installed into the flooring or walls of a room. The conventional alternative to the proposed safety/surveillance system is the usage of security cameras. However, information from cameras does not yield an exhaustive coverage over a given area and storage of such video data is cumbersome. In addition to streamlining the allocation of storage resources, data collected from these sensors is more concise, more utilizable, less intrusive and more flexible. The flooring of a shopping mall could be covered entirely by such a system to safeguard its compound at night, as well as to gather information for marketing and sales research during its operating hours. The same principle could be applied to airports, large exhibit halls or commercial buildings.

A major benefit of such a system is its potential to be expanded. For example, thermal, chemical, pressure sensors could be incorporated to the flooring of public buildings to provide additional security against possible life-threatening vapors or otherwise undetectable hazardous materials. This system also has the potential to be trained to trigger an indication when an unexpected event occurs. Home or commercial building owners can program the system to flag a subset of the network as ‘out of bounds,’ or teach the system to remember its owner’s behaviors and habits. For example, an unexpected detection beginning from an unofficial entry point, or an unrecognized walk-path pattern during an unusual time could trigger the activation of an alarm or other security devices.

The proposed project will benefit from leveraging results from our previous work that involved securing communication during communication across partitioned applications mapped on an Ambient Intelligent Systems. By developing techniques for fault-tolerant (and low power) implementations, our results [1-3] have shown that the system lifetime, dependability and error resilience (be it due to hardware malfunctions or external attacks) are significantly increased.

The end result of our investigation will be to explore the technical feasibility and economic viability of large area sensing for safety and security applications. To this end, we will build a representative prototype consisting of several processing and sensing nodes distributed over a large area flexible substrate that could demonstrate the concept of “computing (or sensing) by the foot.” As a driver application we will consider a typical ambient intelligent system performing motion sensing and monitoring, with the goal of expanding it to hazardous vapor sensing and detection.