Conference Papers

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    People Identification and Counting System Using Raspberry Pi
    The work in this paper focuses on an implementation of OpenCV in an embedded system like raspberry Pi to create a mini-standalone station for counting people. The key feature of AU-PiCC (Assumption University's raspberry Pi Customer counter) is to count a number of interested people on target product in a pre-defined area along with a simple face identification to avoid counting duplicates. The experimental results show that this raspberry Pi-based system can be used as a simple people counter station.
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    PiFrame: A Framework for Home Automation Platform on the Full Feature OS
    This work provides the framework for implementing the embedded systems on the embedded computer that running full-feature OS to shorten the development cycle and reduces the embedded system limitation. The Raspberry Pi, running the full-feature Linux, is used as the based system of the framework with the additional development of software environment and general purpose hardware extension. The framework can be used for both education and research.
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    Design and Development of a Flood Warning System via Mobile and Computer Networks
    ( 2016-01) Anand Dersingh
    Environmental data plays an important role in forecasting and warning of possible natural disaster such as flooding. Thailand faced a major flood in 2011, which at that time lacks automated mechanism in collecting environmental data and warning system. This work presents the design and development of a flood warning system. The system contains an embedded data acquisition module that can be placed in a remote area in order to collect environmental data such as amount of rainfall, water level, and image periodically. The collected data are then sent to a server over the Internet via a cellular data network, which are stored on a database and processed to determine early warning of flood in the area based on historical data. A web application and a mobile application have been designed and developed for users to view measured data. Moreover, the mobile application is capable of receiving a push notification of a warning message of potential flooding.
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    Ball On The Plate Model Based on PID Tuning Methods
    Controller design is one of the important steps during the modelling of various systems, starting with constructing an electric kettle to an aircraft system. To achieve a good controller it is needed to define suitable values for the controller coefficients. This paper describes the research practices of the tuning technique by using MATLAB/Simulink compared with manually PID tuning based on the trial and error process, as well as, PID tuning methods from Ziegler- Nichols and Tyreus-Luyben (closed-loop proportional gain control or P-Control tests). The paper can be useful for readers who want to have a basic knowledge of research assignments based on PID tuning.
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    An optimal performance investigation for bilateral filter under four different image types
    The merit of bilateral filter is that it preserves the edges of the image and smooth the image at the same time. This can be done by controlling two important parameters — spatial domain parameter and range domain parameter. The contribution of this paper is two-fold. First, we investigate the optimal parameters of the bilateral filter under four different types of images — aerial, face, object and texture. The simulation results show that the parameters — spatial domain parameter and range parameter — should be changed depending on the noise power and the details of image. If the noise power is high, the parameters should be set at high levels. These values should be decreased on the increasing in an SNR. Second, we determine the appropriate types of image that the bilateral filter can be applied to perform filtering. Then, we compare bilateral filter’s performance to Gaussian filter and switching bilateral filter. The simulation results show that the bilateral filter gives the best performance when perform de-nosing of aerial, face and object image where the detail of these images are less than texture image.