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Sentient & Cognitive Computing

Sentient Computing is a form of ubiquitous computing which uses sensors to perceive its environment and react accordingly. A common use of the sensors is to construct a world model which allows location-aware or context-aware applications to be constructed.
Course Info

Sentient Computing:

It is a form of ubiquitous computing which uses sensors to perceive its environment and react accordingly. A common use of the sensors is to construct a world model which allows location-aware or context-aware applications to be constructed. Some example applications of the system include:

  • A "follow-me phone" which would cause the telephone nearest the recipient to ring.
  • Teleporting desktops via Virtual Network Computing (VNC) just by clicking their Active Bat near the computer.
  • Spatial buttons which were activated by clicking the Active Bat at a particular spot (such as a poster).
  • Measuring and surveying buildings.
  • Location-based games

Cognitive Computing:

At present, there is no widely agreed upon definition for cognitive computing in either academia or industry.

  • In general, the term cognitive computing has been used to refer to new hardware and/or software that mimics the functioning of the human brain and helps to improve human decision-making.
  • In this sense, CC is a new type of computing with the goal of more accurate models of how the human brain/mind senses, reasons, and responds to stimulus.
  • CC applications link data analysis and adaptive page displays or adaptive user interface (AUI) to adjust content for a particular type of audience. As such, CC hardware and applications strive to be more affective and more influential by design.

Features of Cognitive Systems :

  • Adaptive:

    They may learn as information changes and as goals and requirements evolve. They may resolve ambiguity and tolerate unpredictability. They may be engineered to feed on dynamic data in real time, or near real time.

  • Interactive:

    They may interact easily with users so that those users can define their needs comfortably. They may also interact with other processors, devices, and Cloud services, as well as with people

  • Iterative and Stateful:

    They may aid in defining a problem by asking questions or finding additional source input if a problem statement is ambiguous or incomplete. They may "remember" previous interactions in a process and return information that is suitable for the specific application at that point in time.

  • Contextual:

    They may understand, identify, and extract contextual elements such as meaning, syntax, time, location, appropriate domain, regulations, user’s profile, process, task and goal. They may draw on multiple sources of information, including both structured and unstructured digital information, as well as sensory inputs (visual, gestural, auditory, or sensor-provided).