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This paper presents the major outcomes of the utilization of smart phone applications in the periodical technical inspection process. Road safety is one of the main topics in transportation. Technical defects of vehicles can play an important role in fatal accidents; therefore, periodical vehicle inspection is a common practice amongst many countries across all continents. The authors observed that advancements in smart technologies presented an opportunity to enhance the efficiency and effectiveness of vehicle inspections. They specifically focused on the Slovak Republic and described the transition of technical inspections towards smart technologies in this country. The goal was to utilize new technologies and improvements without increasing costs dramatically. The paper discusses the outcomes of the first two years of using this app at every technical inspection station in the Slovak Republic. The smart phones were used not only to help with process management but the novelty is that they also collected data from the sensors and used their own sensors for the vehicle dynamics measurements. One of the important factors is the successful implementation of low cost devices at such a large scale, country wise.

The paper presents an original methodology for the implementation of the Logarithmic Number System (LNS) arithmetic, which uses Reduced Instruction Set Computing (RISC). The core of the proposed method is a newly developed algorithm for conversion between LNS and the floating point (FLP) representations named “looping in sectors”, which brings about reduced memory consumption without a loss of accuracy. The resulting effective RISC conversions use only elementary computer operations without the need to employ multiplication, division, or other functions. Verification of the new concept and related developed algorithms for conversion between the LNS and the FLP representations was realized on Field Programmable Gate Arrays (FPGA), and the conversion accuracy was evaluated via simulation. Using the proposed method, a maximum relative conversion error of less than ±0.001% was achieved with a 22-ns delay and a total of 50 slices of FPGA consumed including memory cells. Promising applications of the proposed method are in embedded systems that are expanding into increasingly demanding applications, such as camera systems, lidars and 2D/3D image processing, neural networks, car control units, autonomous control systems that require more computing power, etc. In embedded systems for real-time control, the developed conversion algorithm can appear in two forms: as RISC conversions or as a simple RISC-based logarithmic addition.

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