# IoT System for Detecting the Condition of Rotating Machines Based on Acoustic Signals
## 3 Architecture of the Proposed System
### Hardware Implementation  
The device we present in this paper is intended to work in an industrial environment and therefore must meet a number of conditions. First, it must be as small as possible, resistant to adverse working conditions in the environment, autonomous, portable, easy to install and use, and a modest consumer of electricity. A small and light device would take up little space and interfere less with the usual working environment around a rotating machine whose condition it needs to estimate. Since this is mostly an estimation of the industrial machines, working and ambient conditions are often unsuitable for the operation of electronic devices. The presence of abrasive substances and dust, exposure to low and high temperatures, as well as their rapid changes, the danger of mechanical influences caused by force majeure or insufficient attention of the operator, cause the designed device must have a high dose of resistance and protection from these influences. A device of this type and purpose is usually designed to be used on different machines, so it must be easily portable and autonomous in its work. This means that it must also have an autonomous power supply that will ensure long enough operation between two battery charges. Finally, since the device is portable, it is necessary that its installation and commissioning be simple so that it can be performed by a less skilled user. Figure 7: The proposed system architecture. After the initial consideration of the most suitable platform for the realization of the device for acoustic signal acquisition and processing, we decided to use the Raspberry Pi (RPi) platform [32]. First, it provides sufficient processing power to perform the required tasks. In addition, unlike many microcontroller platforms, it works like a regular computer with an operating system, which significantly facilitates software development, integration of hardware components and shortens the time required for implementation. Last, but not least, for our specific application, it allows easy utilization of large storage space. Namely, acoustic signal recording produces relatively large files that need to be recorded somewhere for possibly later processing. If we also want to keep earlier recordings for comparisons and later additional analyzes, the requirements for storage space are growing rapidly. Managing such files is an additional challenge if we do not have operating system support. RPi uses an SD memory card as a storage device. It provides space for an operating system with all the available software applications. It also uses the same memory card to store files that are the result of the user's work. There are several supported operating systems, but in our implementation, we used Raspberry Pi OS (formerly called Raspbian) [33], which is a scaled-down version of the Linux operating system, adapted to run on RPi. The Raspberry Pi OS with desktop and recommended software takes up just under 4 GB on the memory card, but the need for space grows with the installation of additional software applications and tools. That is why we used a 32 GB memory card in our implementation. It turned out that this memory capacity is enough to install all the necessary programs and tools, as well as to store recordings from a number of acquisitions. Acquisition of the acoustic signal is performed using a small and affordable commercial microphone, model AK5371, which connects to the microprocessor platform via a USB port. The quality of the microphone certainly affects the quality of the recording, and thus the quality of the obtained information about the condition of the machine. However, in the initial phase of the research, we found that with the help of a small, portable and affordable microphone, as we use in our system, we could get quite relevant results [34]. An additional advantage of the used microphone is a built-in A/D converter, which further facilitates its integration into the system.