The following diploma thesis deals with the management of asynchronous motor revolutions by a frequency converter MICROMASTER 440 via the programmable controller S7-200. At the beginning, I researched the company documentation of Siemens, which is the producer of the frequency converter and the programmable controller mentioned above. As my work proceeded, I also started to study the company documentation of Mitsubishi Electric, which produces the operating pannel. The first part of my thesis provides a general description of the stated devices and the second part deals with the solution of the task itself. My task was to design a way of communication between the converter and the controller. I chose a USS protocol via serial port RS-485. The operation of the controller was performed by using an operating terminal type GOT1000 which was connected to the controller. In summary, my diploma thesis primarily deals with the construction of an operating programme for the controller and with creating of a graphical control on the terminal. In the end, I evaluated the knowledge gained during the work on this subject and suggested further procedures.

Indiana University-Purdue University Indianapolis (IUPUI) / Physical activity monitoring using wearable sensors give valuable information about patient's neuro activities. Fall among ages of 60 and older in US is a leading cause for injury-related health issues and present serious concern in the public health care sector. If the emergency treatments are not on time, these injuries may result in disability, paralysis, or even death. In this work, we present an approach that early detect fall occurrences. Low power capacitive accelerometers incorporated with microcontroller processing units were utilized to early detect accurate information about fall events. Decision tree algorithms were implemented to set thresholds for data acquired from accelerometers. Data is then verified against their thresholds and the data acquisition decision unit makes the decision to save patients from fall occurrences. Daily activities are logged on an onboard memory chip with Bluetooth option to transfer the data wirelessly to mobile devices. In this work, a system prototype based on neurosignal activities was built and tested against seven different daily human activities for the sake of differentiating between fall and non-fall detection. The developed system features low power, high speed, and high reliability. Eventually, this study will lead to wearable fall detection system that serves important need within the health care sector. In this work Inter-Integrated Circuit (I2C) protocol is used to communicate between the accelerometers and the embedded control system. The data transfer from the Microcontroller unit to the mobile device or laptop is done using Bluetooth technology.

Discontinous regulation, PLC control system, Programmable controller, Temperature control using Peltier´s module.