SensITs realises the Artificial Live of Intelligent Sensing Entities (ISE) – cognition, learning and action main functions on the Internet of Sensing Things - as a natural sequence (stream) and logical consequence of virtual/real sensing-spectrograms at 1-25 frames per second.

IoST applies the actual available technologies to create novel solutions in the area of artificial perception and reasoning for sensing devices, such as, sensors, mobile-phones, RFIDs, PLCs and intelligent embedded systems. 

IoST outilnes models and paradigms of sensing event processing, sensing resources computing, and Information Technologies, for embodying perception capacities, learning abilities, and cognition faculties into artificial intelligent sensing entities, living in real/virtual worlds.

The Sensing Event Computing for Artificial Intelligence and Ambient Intelligent Applications (SECAIA) group swallows that the problem and real need of Internet of Sensing Things ((a)) is to reach the sensing capacity to perceive the environment and the reasoning faculties to understand the context.

The IoST vision is to extend human senses to the artificial sensing systems of local and remote environments, and local and global applications and information services through the Internet. The possibility to extract, use and exploit the sensing-raw data, information and knowledge that can be made available from sensing entities opens up a huge potential to improve the quality and efficiency of the knowledge pyramid and connect the virtual and real worlds.

IoST foresees that persons on 2020, will trust extraordinarily in their sensing mobile phone, for extending its natural perception of the environment and their-self. The sensing device will be able to detect if there is some toxicity in the meal before to eat, or a gas escapes when sleeping or an intense radioactivity area, dangerous physiological variables in our body, and other situations that humans can not perceive and understand. This means that IoST will change the actual situation, where sensing entities has less perception capacities and less cognition faculties than humans to become super-humans with incredible perception and detection capacities via their inseparable sensing-devices.

IoST aims to use all the information derived from the real/virtual world to enable sensing entities that are aware of the environment, and
that can understand the meaning of sensing events conveyed by environmental information, and that can thereby provide locally and
remotely useful services to the society in an improved, bio-inspired way.

IoST goals to investigate, develop, implement, experiment and validate a framework of information and communication paradigms,
models and systems for endowing perception capacities, learning abilities and embodying cognition, personalisation, adaptation and evolution
faculties into artificial intelligent sensing entities, and build an incipient platform prototype for the proof of concepts, features and performances.

The basic goal of SensITs research is understanding the computational and statistical foundations of computing artificial cognition, and using this understanding and adapted available semantic sensing technologies to develop and experiment both better accounts of ISE perception and behaviour, and better robotic/automatic services for supporting the challenging human perception problems and limitations.

IoST pursues this goal by analysing artificial cognition in terms of computational solutions to natural and behavioural based on ten simple and basic human processes and features  models.

The inductive problems of developing models based on the principles of probability theory, and exploring how ideas from humans, natural environments and statistics (particularly Bayesian statistics) connect to artificial cognition.

These models through experiments with artificial intelligent sensing entities (ISE), looking at how ISE evolve a wide range of inductive problems, including semi-driven learning, action and evolution, and other psychological features and performances.

Mathematical, probabilistic, computational and pshycological models provide a way to explore many of the key-questions of artificial cognition science.

The IoST objective is the exploitation of the world of artificial sense at its greatest potential. The impact on the society can be as profound as the Internet’s impact.

IoST targets foundational breakthroughs, that open novel avenues of research and original ways, different from present day ICT, towards radically extraordinary new forms of human awareness, and uses of sensing objects and systems, applying openly available information technologies, within a clear longterm vision that is far beyond the state of the art.

IoST proposes the exploration and development of new, alternative, novel and multidisciplinary ideas, concepts and paradigms of sensing real/virtual worlds that, because of their radical, fragile, incipient and high-risk nature, may be supported in the Future Emerging Technologies work programme.

IoST purposes at developing its supporting scientific foundation, and at achieving a first proof of concept, strengthening the future potential for highrisk/ high-impact research and innovation.

IoST intends to draft a framework of paradigms and models of a new way of aware, perceive and realise the reality by the humans beings in the future.

IoST needs new inter-disciplinary collaborations, research alliances, and exploiting synergies, possibly with prominent and internationally recognized EU and non-EU research teams where these can provide a significant added value, in the global science and technology scene for increased impact and excellence.

IoST defines five main novelties and S/T challenges:
1. Sensing event-driven detection (SED) processing for the environment perception and SED analysis for context reasoning. Computational principles underlying the representation and processing of complex real-world patterns.
2. Evolutionary model of nine steps for artificial sensing entities, from perception to evolution, following the traditional scheme of the "knowledge pyramid", from sensing-raw data to wisdom for efficient adaptation.
3. Leverage the rich though untapped potential of the information associated to sensing events.
4. Semi-driven learning process for artificial sensing entities, based on update SED database and upgrade SW of processing units of sensing entities.
5. Internet semantic repository of “Sensing spectrograms” for filtering and processing SED by means of algorithms of lattices patterns and available image processing tools.

The Sensing Event Computing for Artificial Intelligence and Ambient Intelligent Applications (SECAIA) community swallows that the problem and real need of Internet of Sensing Things (IoST) is to reach the sensing capacity and possibilities to perceive the environment and the reasoning faculties to understand the context. Hence the necessity to define the models and paradigms of sensing event processing, sensing resources computing, and Information and Communication Technologies to embody perception capacities, learning abilities, and cognitive faculties into artificial intelligent sensing entities (ISE) living in real/virtual worlds.

Anticipatory system contains a predictive model of itself and/or its environment, which allows it to change state at an instant in accord with the model's prediction pertaining to a later instant.

IoST believes that “The problem of sensing entities lies in reaching the capacity to sense the surrounding environment and the reasoning faculties to understand that context in order to provide useful and reliable services and profitable society solutions,” and, moreover, “The future problem will be that we have too much data and we need to find a way to distil it to obtain what the user needs to know, and to directly provide actionable information or more efficiently extracted knowledge to enhance real life.”

As ICT experts, we realise how important it can be for the society and for Europe to succeed in the IoST, which lays a foundation for future success in the artificial, virtual and natural merged-reality in ambient intelligent areas for robotics and augmented humans capacities, as well as in the development of industrial applications and Internet services.

The IoST vision is to extend human senses to the artificial sensing systems of local and remote environments, local and global applications and information services through the Internet. The possibility to extract, use and exploit the sensing raw data, information and knowledge that can be made available from sensing entities opens up a huge potential to improve the quality and efficiency of the knowledge pyramid and interconnect the virtual and real worlds. We assume that people till 2020 will extensively trust their sensing devices to extend their natural perception of the environment and themselves. For example the sensing devices and artifacts that acquire, interpret, select and organise the sensory information will be able to detect toxicity in the meal before being ingested, a gas leak when sleeping, intense radioactivity areas, alarming physiological signals in our body, and other situations that humans currently cannot perceive, understa#00000a;">nd and react accordingly with. This means that SensITs will change the actual situation, where sensing entities have less perception capacities and less cognition faculties than humans. By their use, end-users will acquire incredible perception capacities thanks to their inseparable sensing devices that will support their living. In a natural way, SensITs provides to Intelligent Sensing Entities (ISE) the faculties to learn, adapt and evolve while living on Internet, to develop their perception and understand the senses to provide important and additional information services to the society.

IoST studies, analyses and experiments the computational implementation of artificial cognition of ISE, under the thesis of computational sufficiency, which means that the right kind of computational structure suffices for the possession of intelligence , and the thesis of computational explanation, which means that computation provides a general framework for the explanation of cognitive processes. Fulfillment of these requirements will lead to a computational framework, compatible with a wide variety of human mind experimental and empirical approaches, which will allow computation to serve as a true foundation for cognitive robotics science.

This experimentation requires new mathematical and computational models, and graphical technologies to simulate natural living processes. SensITs sets on raising technologies of semantic graphics, applies these technologies to Sensing Events Detection (SED) in order to embed the meaning of the sensation in the graphical pattern, and proposes the use of spectrograms for filtering the event and process sequences of SED. The simulation of the natural life is based on the processing of a video-stream of SED, that extracts the meaning of each sensation, for instance to recognise the activity, define the context and decide the appropriate action. Moreover, SensITs simulates the natural semi-driven learning process by means of an IT model of retraining. The ISE manages an unknown sensing-event by sending it to the Internet “School”, where a “Master” professional can analyse and process the filtering models for updating regularly the ISE. This continuous improvement of capacities allows the adaptation to the environment and activity and produces the ISE evolution.

IoST