1. INATO Ltd, Pancho Vladigerov 74, Office 4, Sofia 1343, BULGARIA
www.InatoLab.eu Page 1
The IoT-vision of INATO Ltd
1. INATO Ltd- The innovation company
INATO Ltd was set up in 2010 as a company from the United Software Writers circle. The company functions as
laboratory for experiments with innovative ideas. The ideas found workable are developed as products and
services for the market with the resources of the other companies from the United Software Writers circle. For this
purpose the INATO’s team is also well experienced in management of innovative projects.
2. INATO’s Unified Platform for Innovations
INATO’s developments are implemented in the establishment of the Bulgarian E-government, especially in the
field of Semantic interoperability and Administrative systems building. That was possible because of the intensive
work of INATO Ltd on Semantic networks. With the financial support of the EU (project BG161PO003-1.1.01-
0243-С0001/29.12.2011), the Unified Platform for Innovations (UPI) was created on the basis of which software
systems with new architecture - Semantic Network Based Architecture (SNBA) are built up [1].
With the new architecture, a new concept for system integration of objects with autonomous behaviour by the
means of connections is invented, which supports exchange of semantic among them [2]. The already linked
objects and the connections among them are defined as semantic assets and are saved in the UPI Semantic
Repository. This repository itself is an integral part from the semantic network of models and their instances in the
UPI Environment.
3. Main directions of work
3.1. Development of IoT-connectivity oriented semantic assets
The IoT-connectivity oriented semantic assets support the development and dissemination of non-intelligent
IoT-systems. Those semantic assets can be divided in the following groups, which support:
1) Real Time priority manageable IoT-procedures execution
Those assets form UPI Real Time Environment (RTE.upi) ensure run time support of IoT-connectivity
by execution of corresponding IoT-procedures in Real Time mode.
2) Scenarios Description Framework (SDF)
The SDF-technology and tools for scenarios modelling and interpretation support the semantic of the
IoT-connectivity realizations.
3) Creation and support of new IoT-business models
The models serve market deployment of the so created non-intelligent IoT-systems.
3.2. Development of AI oriented semantic assets
The AI oriented semantic assets support the Bottom-up development of intelligent IoT-systems [3]. The
amount of semantic assets in UPI Semantic Repository is a natural limit of the so accomplished intelligence.
In this way, higher level of intelligence can be achieved with more semantic assets in UPI Semantic
Repository.
The intelligence consist of:
1) Generating natural language
The resources for generating of natural language are used to compose in textual form the
representation of the semantic of the IoT-connected objects, their interactions and the results from
these interactions. This converts the non-intelligent IoT-systems into “speaking systems”.
2) Interpreting natural language
The resources for natural language interpretation are used for transition from semantic of natural
language to the form of semantic of the assets in the UPI Semantic Repository. This converts the
non-intelligent IoT-systems into “listening systems”.
3) Machine learning and decision making
The interactive process of machine learning is based on the accumulated semantic assets in the UPI
Semantic Repository and is used for tuning of complicated IoT-configuration, for transfer of
intelligence between UPI-systems, so on. This converts the non-intelligent IoT-systems into more or
less intelligent systems.

2. INATO Ltd & IoT
www.InatoLab.eu Page 2
4. UPI Semantic Repository, semantic programing and crowdsourcing
Every realization of IoT-connectivity is in compliance with the established and highly supported Semantic
interoperability in the UPI-Environment. The new Semantic Network Based Architecture permits full program code
decentralisation. The UPI-models of objects and their connectivity consists of the necessary semantic
representations- textual for human acceptance, formalised for machine interpretation and coded for semantic
processing.
This converts the UPI Environment into environment for semantic programing with high degree of reusability of
semantic assets in the UPI Semantic Repository and with independence of the processes of new UPI-models
building.
All of this ensures good conditions for crowdsourcing. The crowdsourcing enlarges the amount of semantic assets
in the UPI Semantic Repository which by itself makes crowdsourcing more attractive for third parties.
5. References
[1.] Blagoev L., Data organization in Information Systems as a Semantic network, CIO, 11.09.2013
[2.] Blagoev L., Spassov K., Smart home as a Digital Environment, Sofia University, Spring Scientific Session
of Faculty of Mathematics and Informatics, 28.03.2015, Sofia, Bulgaria
[3.] Blagoev L., Spassov K., The end of IoT Enthusiasm or the Beginning of a new IoT Vision, Sofia
University, Spring Scientific Session of Faculty of Mathematics and Informatics, 26.03.2016, Sofia,
Bulgaria
L.Blagoev
INATO Ltd, 2016