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    Investigation of Wireless Body Area Network Localization Based on Measurement Data
    (2022-01-01)
    Promwong, Sathaporn
    ;
    Khongsomboon, Khamphong
    ;
    Chaisang, Aditep
    Short-range wireless communication is important for application use in wireless medical monitoring systems and wireless body area network localizations. Therefore, the channel's characteristics and the human body effect must be studied. This paper will investigate the wireless body area network localization and ZigBee technology based on the IEEE 802.15.4. Moreover, model wireless body area network measurement using a vector network analyzer at the frequency range of 2.2 GHz to 2.6 GHz for measurement and recording. In the experiment result, the wireless body area network localization is analyzed and evaluated by considering the received signal strength and distance error shown in the cumulative distribution function based on the CLEAN algorithm. From experimental studies, this project is beneficial for development studies and essential information for future research studies of wireless body area network localization applications.
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    Zigbee wireless sensor network localization evaluation schemewith weighted centroid method
    (2018-08-14)
    Thammavong, Lonesy
    ;
    Khongsomboon, Khamphong
    ;
    Tiengthong, Thanadol
    ;
    Promwong, Sathaporn
    Using wireless communication system, appropriate and correct indoor localization with Zigbee sensor network and could provide interesting services and applications. In this study the Zigbee transmission model with positioning method by using the relative-span exponentially weighted centroid method for the indoor localization. The experimental results and analyze results are evaluated a distance error. The ZigBee transmission model in measurement consists of 121 positions with distance between positions to positions is 0.3 meter. The experimental setup at every position operated at frequency band from 2.3 GHz to 2.5 GHz. The accuracy of estimated position is considered in the term of distance error with the cumulative distribution function (CDF) of distance error is shown. The result presents optimal value for REWL is 0.2 and mean of distance error is 0.65 m.
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    Quantitative Evaluation of Zigbee Localization Based on Weighted Centroid with Quadratic Means
    (2018-07-02)
    Thammavong, Lonesy
    ;
    Khongsomboon, Khamphong
    ;
    Promwong, Sathaporn
    Wireless localization for indoor radio wave propagation channels are significant interested research topic. The indoor localization is widely applying in wireless sensor network. Weighted centroid algorithm is one of the algorithm that able to work in range-free scenario of indoor localization. This research proposed the modified of weighted centroid algorithm with quadratic mean based on received signal strength of the frequency at 2.4 GHz. The ZigBee is a promising technology for operate at 2.4 GHz and good performance in the indoor environment. The experimental results are show as the average received signal strength value, the distance error, and the comparison of commutative distribution function of distance error between the normal weighted centroid algorithm and the modify weighted centroid algorithm at 1 m. The precision of modify weighted centroid algorithm is better than the weighted centroid algorithm more than 9% and have 17% no error position estimation.
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    Vehicle detection and classification system based on virtual detection zone
    (2016-11-18)
    Seenouvong, Nilakorn
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    Watchareeruetai, Ukrit
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    Nuthong, Chaiwat
    ;
    Khongsomboon, Khamphong
    ;
    Ohnishi, Noboru
    This paper proposes a vehicle detection and classification system based on virtual detection zone (VDZ). The proposed system consists of four main steps: foreground extraction, vehicle detection, vehicle feature extraction and vehicle classification. A moving vehicle is firstly detected based on Gaussian mixture model (GMM). Then, several techniques including region of interest selection, adaptive morphological operation, and contour processing are applied to obtain correct foreground objects. Next, vehicle features are calculated when the centroid of a vehicle is on the VDZ. Finally, vehicles are classified by using k-nearest neighbor classifier. Experimental results show that the proposed method can accurately detect and classify vehicles with an accuracy of 98.53%.
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    A computer vision based vehicle detection and counting system
    (2016-03-23)
    Seenouvong, Nilakorn
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    Watchareeruetai, Ukrit
    ;
    Nuthong, Chaiwat
    ;
    Khongsomboon, Khamphong
    ;
    Ohnishi, Noboru
    A vehicle detection and counting system plays an important role in an intelligent transportation system, especially for traffic management. This paper proposes a video-based method for vehicle detection and counting system based on computer vision technology. The proposed method uses background subtraction technique to find foreground objects in a video sequence. In order to detect moving vehicles more accurately, several computer vision techniques, including thresholding, hole filling and adaptive morphology operations, are then applied. Finally, vehicle counting is done by using a virtual detection zone. Experimental results show that the accuracy of the proposed vehicle counting system is around 96%.
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    Chaotic encoder-decoder on FPGA for crypto system
    (2014-02-12)
    Roeksukrungrueang, Chanathip
    ;
    Dittaphong, Xaysamone
    ;
    Khongsomboon, Khamphong
    ;
    Panyanouyong, Nounchan
    ;
    Chivapreecha, Sorawat
    An implementation of chaotic encoder-decoder on FPGA will be proposed in this paper. Overflow non-linearity by using 2's complement number in digital filter causes the phenomenon called 'Chaos' in digital filter. An 1ER filter can be used to chaotic encoder while an FIR filter is used to chaotic decoder. Filter coefficients of both encoder and decoder can be compared to the secret key in private-key crypto system. However, if filter coefficients of chaotic decoder are not same as filter coefficients of chaotic encoder, ciphertext cannot decrypt to get original plaintext. Both chaotic encoder and decoder will be implemented on FPGA to demonstrate the hardware prototype of chaotic crypto system.