Sensitivity analysis of condominium lightning protection risk analysis

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Today we live in an accelerated world. In our environment there are more facilities to serve our needs than ever before, and today's devices have multiple functions, and probably they will gain new functions as well. They are called smart devices. Smartphones, tablets, smart TV-s and potential smart vehicles will create a new environment. As a result of the continuous development of human living communities (villages, towns and settlements), the dominant usage of smart tools and technologies already represents a new quality level (Smart City). These new devices require a new level of lightning protection. Natural forces endanger buildings as well as human lives. The protection of artificially created objects and of the built environment has always played a prominent role, and nowadays, one of its main areas is the lightning protection of structures. The calculation of the lightning protection is based on the MSZ EN 62305 [1] standard. In the past, several changes were made in the standards and decrees [2], and now the current standard is the MSZ EN 62305. It contains the exact mathematical methods of risk assessment using the parameters of buildings and their installations (e.g. lightning protection installations, cables, flooring etc.). The present research aims to identify the relationships between output parameters determined by the input parameters based on the current standards, and the identification of risks by their analysis in different types of buildings.

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Our hypothesis was that the ecosystem of self-driving cars could be treated as a complex system. The proof of this was based on the definition of self-driving car ecosystem and definition of complex system. We not found definition for ecosystem of self-driving cars. That's why we made our own definition of self-driving car ecosystem. Self-driving car ecosystem is all technology and person and service that connect to the self-driving car and have effect to the self-driving car technology, self-driving car design, self-driving car traffic, self-driving car environment (infrastructure), self-driving car maintenance, self-driving car education and self-driving car law.
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