Pub Date : 2017-11-01DOI: 10.1109/ICSAI.2017.8248423
Liang Pang, Zhi Xue
In wireless sensor networks, the shared wireless medium and the broadcast nature make the network vulnerable to intelligent jamming attacks. Such attacks are launched timely by eavesdropping on packets being sent across the network. They can severely affect the network capacity to execute its preset functions. In order to address this issue, we propose a novel anti-jamming method which uses the jammer location as the prerequisite to restore the communication links. The proposed method is based on using the artificial noise generated by the synergistic sensor nodes to degrade the wiretap channel of jammer. The feasibility of our method is theoretically proved with the possible network and jammer model. We also provide a simplified scheme to estimate some unknown parameters which are important for practical application. Extensive experiments are conducted in MATLAB to evaluate the effectiveness and performance of our method. The experimental results suggest that the proposed method can make the jammer unable to correctly decode the received packets because of the low Signal-to-Noise Ratio, and significantly restore the communication links by increasing the Packet Send Ratio (PSR)/Packet Delivery Ratio (PDR) at the transmitter/receiver side.
{"title":"A novel anti-jamming method in wireless sensor networks: Using artificial noise to actively interfere the intelligent jammer","authors":"Liang Pang, Zhi Xue","doi":"10.1109/ICSAI.2017.8248423","DOIUrl":"https://doi.org/10.1109/ICSAI.2017.8248423","url":null,"abstract":"In wireless sensor networks, the shared wireless medium and the broadcast nature make the network vulnerable to intelligent jamming attacks. Such attacks are launched timely by eavesdropping on packets being sent across the network. They can severely affect the network capacity to execute its preset functions. In order to address this issue, we propose a novel anti-jamming method which uses the jammer location as the prerequisite to restore the communication links. The proposed method is based on using the artificial noise generated by the synergistic sensor nodes to degrade the wiretap channel of jammer. The feasibility of our method is theoretically proved with the possible network and jammer model. We also provide a simplified scheme to estimate some unknown parameters which are important for practical application. Extensive experiments are conducted in MATLAB to evaluate the effectiveness and performance of our method. The experimental results suggest that the proposed method can make the jammer unable to correctly decode the received packets because of the low Signal-to-Noise Ratio, and significantly restore the communication links by increasing the Packet Send Ratio (PSR)/Packet Delivery Ratio (PDR) at the transmitter/receiver side.","PeriodicalId":285726,"journal":{"name":"2017 4th International Conference on Systems and Informatics (ICSAI)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115648667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/ICSAI.2017.8248389
Yilun Sun, Qiang Sun, Kai-Di Chang
In order to improve the accuracy of indoor positioning in wireless sensor network, an indoor localization algorithm based on improved Kalman filtering is proposed. By introducing suboptimal unbiased maximum a posteriori (MAP) noise statistical estimator, the system noise covariance and measurement noise covariance of Kalman algorithm is modified adaptively to replace Gaussian white noise sequence of zero mean difference and known covariance, which makes the algorithm have the good filtering effect. In order to show the performance of the proposed algorithm, the indoor localization algorithm performance is compared. The experiment result shows that the proposed algorithm can improve indoor positioning accuracy of unknown nodes.
{"title":"The application of indoor localization systems based on the improved Kalman filtering algorithm","authors":"Yilun Sun, Qiang Sun, Kai-Di Chang","doi":"10.1109/ICSAI.2017.8248389","DOIUrl":"https://doi.org/10.1109/ICSAI.2017.8248389","url":null,"abstract":"In order to improve the accuracy of indoor positioning in wireless sensor network, an indoor localization algorithm based on improved Kalman filtering is proposed. By introducing suboptimal unbiased maximum a posteriori (MAP) noise statistical estimator, the system noise covariance and measurement noise covariance of Kalman algorithm is modified adaptively to replace Gaussian white noise sequence of zero mean difference and known covariance, which makes the algorithm have the good filtering effect. In order to show the performance of the proposed algorithm, the indoor localization algorithm performance is compared. The experiment result shows that the proposed algorithm can improve indoor positioning accuracy of unknown nodes.","PeriodicalId":285726,"journal":{"name":"2017 4th International Conference on Systems and Informatics (ICSAI)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115683022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/ICSAI.2017.8248273
N. Dimitrov, A. Topalov, Sevil A. Ahmed, Pavel Radev
The demand of the industry for high performance electric motors has significantly increased nowadays. This has boosted the usage of permanent magnet brushless synchronous motors (BLSM) in many applications where the accuracy and performance requirements are high. Further improvement of the BLSM drive systems performance can be achieved by providing them with adaptive control capabilities. The relative complexity of adaptive control schemes and algorithms and the computational load that they impose have prevented until recently their practical implementation into the industrial servo systems. In this investigation, a neuro-adaptive control scheme where the rule for parameter adaptation is designed by taking into account the variable structure control (VSC) concepts and Lyapunov stability, is proposed and embedded into an inexpensive, available on the market, position control system for brushless synchronous servomotors. The experimental tests have been carried on using compact and flexible, based on open hardware and software concept, dual-axis motion controllers PMC201/PMC202 manufactured by the PicoMotion Inc. The applied software has been written using the Motion Control Framework software platform, provided together with the above controllers. The results obtained with the proposed neuro-adaptive control scheme have been compared to those obtained using the originally built into the system PI controller. The experiments have shown that the implemented advanced adaptive control approach is practically viable and can be embedded into the industrial motion control systems which will lead to their improved performance.
{"title":"Implementing neuro-adaptive control algorithms with sliding mode learning on industrial servo drives","authors":"N. Dimitrov, A. Topalov, Sevil A. Ahmed, Pavel Radev","doi":"10.1109/ICSAI.2017.8248273","DOIUrl":"https://doi.org/10.1109/ICSAI.2017.8248273","url":null,"abstract":"The demand of the industry for high performance electric motors has significantly increased nowadays. This has boosted the usage of permanent magnet brushless synchronous motors (BLSM) in many applications where the accuracy and performance requirements are high. Further improvement of the BLSM drive systems performance can be achieved by providing them with adaptive control capabilities. The relative complexity of adaptive control schemes and algorithms and the computational load that they impose have prevented until recently their practical implementation into the industrial servo systems. In this investigation, a neuro-adaptive control scheme where the rule for parameter adaptation is designed by taking into account the variable structure control (VSC) concepts and Lyapunov stability, is proposed and embedded into an inexpensive, available on the market, position control system for brushless synchronous servomotors. The experimental tests have been carried on using compact and flexible, based on open hardware and software concept, dual-axis motion controllers PMC201/PMC202 manufactured by the PicoMotion Inc. The applied software has been written using the Motion Control Framework software platform, provided together with the above controllers. The results obtained with the proposed neuro-adaptive control scheme have been compared to those obtained using the originally built into the system PI controller. The experiments have shown that the implemented advanced adaptive control approach is practically viable and can be embedded into the industrial motion control systems which will lead to their improved performance.","PeriodicalId":285726,"journal":{"name":"2017 4th International Conference on Systems and Informatics (ICSAI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121121716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/ICSAI.2017.8248289
J. Ferreira, Tao Liu, Portugal Coimbra, Paulo Coimbra
The main objective of this research project is to develop a low cost computerized system to automatically diagnose gait disorders and characterize their severity. The system uses 2 video cameras to provide a 3D position acquisition system connected to a personal computer. The patient gait and posture are analyzed from the data acquired by a vision-based gait acquisition system. The whole system will be an important novel tool in medical rehabilitation and diagnosis, resulting on a more effective functional rehabilitation of a patient's gait, assessing their clinical evolution and solving the limitations of the current subjective gait diagnosis tools. The system allows the calculation of 17 human gait joint trajectories. This system will provide a much more objective understanding of the patient's clinical evolution, and thus enables a more effective functional rehabilitation of a patient's gait. In this paper it is presented the selection of the relevant diagnosis parameters of the gait patterns, which is one of the steps to get to the main objective, the automatic diagnosis of human gaits.
{"title":"Parameter analysis and selection for human gait characterization using a low cost vision system","authors":"J. Ferreira, Tao Liu, Portugal Coimbra, Paulo Coimbra","doi":"10.1109/ICSAI.2017.8248289","DOIUrl":"https://doi.org/10.1109/ICSAI.2017.8248289","url":null,"abstract":"The main objective of this research project is to develop a low cost computerized system to automatically diagnose gait disorders and characterize their severity. The system uses 2 video cameras to provide a 3D position acquisition system connected to a personal computer. The patient gait and posture are analyzed from the data acquired by a vision-based gait acquisition system. The whole system will be an important novel tool in medical rehabilitation and diagnosis, resulting on a more effective functional rehabilitation of a patient's gait, assessing their clinical evolution and solving the limitations of the current subjective gait diagnosis tools. The system allows the calculation of 17 human gait joint trajectories. This system will provide a much more objective understanding of the patient's clinical evolution, and thus enables a more effective functional rehabilitation of a patient's gait. In this paper it is presented the selection of the relevant diagnosis parameters of the gait patterns, which is one of the steps to get to the main objective, the automatic diagnosis of human gaits.","PeriodicalId":285726,"journal":{"name":"2017 4th International Conference on Systems and Informatics (ICSAI)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121194899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/ICSAI.2017.8248432
M. R. Silva, P. Machado, L. E. Souza, Carlos Waldecir de Souza
This paper presents a methodology to analyze the performance of a switched IEC 61850-9-2 network using the formalism of Colored Petri Nets (CPN). In order to decrease the complexity of the network analysis, it is assumed a model with distinct hierarchical levels, and this model allows describing the function and interaction of each element in an easy way. After the modeling process, the proposed methodology is validated by an implementation of an IEC 61850 scenario where the transfer of Sampled Value messages is put in a critical condition. As the simulations show, this methodology allows the evaluation of message latency and capacity limits using just modeling based on discrete events.
{"title":"Colored Petri Net modeling of communication systems based on IEC 61850","authors":"M. R. Silva, P. Machado, L. E. Souza, Carlos Waldecir de Souza","doi":"10.1109/ICSAI.2017.8248432","DOIUrl":"https://doi.org/10.1109/ICSAI.2017.8248432","url":null,"abstract":"This paper presents a methodology to analyze the performance of a switched IEC 61850-9-2 network using the formalism of Colored Petri Nets (CPN). In order to decrease the complexity of the network analysis, it is assumed a model with distinct hierarchical levels, and this model allows describing the function and interaction of each element in an easy way. After the modeling process, the proposed methodology is validated by an implementation of an IEC 61850 scenario where the transfer of Sampled Value messages is put in a critical condition. As the simulations show, this methodology allows the evaluation of message latency and capacity limits using just modeling based on discrete events.","PeriodicalId":285726,"journal":{"name":"2017 4th International Conference on Systems and Informatics (ICSAI)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121852676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/ICSAI.2017.8248455
Jiaqi Wang, Qinghua Huang, Xin Zhang
Ultrasound elastography is a common medical imaging applied in medical applications since it can provide the tissue hardness information. Most ultrasound elastography techniques are window based methods. The key of the quasi-static ultrasound elastography is to do the similarity measure between two windows from pre- and post-compression to compute the displacement. In view of this situation, the window size has an important influence on the strain images quality. In this paper, a reasonable method utilizing PSO algorithm to search for the optimal window length for different data is brought out to solve this problem. The displacement map can be estimated with the optimal window length using the normalized cross correlation method. And a spatial derivative operator is applied to estimate the strain map. The strain images with the fixed window length 12 and 50 and the optimal window length using PSO algorithm are compared in this paper. Results show that using PSO algorithm to search for the optimal window length can improve the SNR and CNR of strain images.
{"title":"Ultrasound elastography based on the normalized cross-correlation and the PSO algorithm","authors":"Jiaqi Wang, Qinghua Huang, Xin Zhang","doi":"10.1109/ICSAI.2017.8248455","DOIUrl":"https://doi.org/10.1109/ICSAI.2017.8248455","url":null,"abstract":"Ultrasound elastography is a common medical imaging applied in medical applications since it can provide the tissue hardness information. Most ultrasound elastography techniques are window based methods. The key of the quasi-static ultrasound elastography is to do the similarity measure between two windows from pre- and post-compression to compute the displacement. In view of this situation, the window size has an important influence on the strain images quality. In this paper, a reasonable method utilizing PSO algorithm to search for the optimal window length for different data is brought out to solve this problem. The displacement map can be estimated with the optimal window length using the normalized cross correlation method. And a spatial derivative operator is applied to estimate the strain map. The strain images with the fixed window length 12 and 50 and the optimal window length using PSO algorithm are compared in this paper. Results show that using PSO algorithm to search for the optimal window length can improve the SNR and CNR of strain images.","PeriodicalId":285726,"journal":{"name":"2017 4th International Conference on Systems and Informatics (ICSAI)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122010625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/ICSAI.2017.8248507
Weimin Ouyang
Discovery of interesting effectiveness itemsets has been a hot topics in data mining and knowledge discovery. Most previous researches related to effectiveness mining in literature employ a individual minimal threshold of effectiveness to decide on if an item is a interesting effectiveness item. Nevertheless, a individual minimal threshold of effectiveness could not express the varied natures of diverse items. In this paper, the author put forward a algorithm to discover interesting effectiveness itemsets with several minimal thresholds using average constraint. The reports of tests demonstrated that our algorithm is better than other baseline algorithms in performance.
{"title":"Discovery of interesting effectiveness itemsets with several minimal thresholds using average constraint","authors":"Weimin Ouyang","doi":"10.1109/ICSAI.2017.8248507","DOIUrl":"https://doi.org/10.1109/ICSAI.2017.8248507","url":null,"abstract":"Discovery of interesting effectiveness itemsets has been a hot topics in data mining and knowledge discovery. Most previous researches related to effectiveness mining in literature employ a individual minimal threshold of effectiveness to decide on if an item is a interesting effectiveness item. Nevertheless, a individual minimal threshold of effectiveness could not express the varied natures of diverse items. In this paper, the author put forward a algorithm to discover interesting effectiveness itemsets with several minimal thresholds using average constraint. The reports of tests demonstrated that our algorithm is better than other baseline algorithms in performance.","PeriodicalId":285726,"journal":{"name":"2017 4th International Conference on Systems and Informatics (ICSAI)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123473588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/ICSAI.2017.8248480
Guanghua Chen, Qiang Zhang, Meiqian Chen, H. Yin
Log Diameter Classes 3D measurement with binocular stereo vision system was adopted. According to the log-end histogram feature, a region labeling method was proposed based on the maximum entropy threshold segmentation. Adopting the region labeling based on pixel labeled method of connecting area, each log could be precisely identified and counted by the system. Extraction of log edge using a Canny operator, completed stereo matching based on the epipolar line rectification, then obtained the matching 3D coordinate points. According to the quasi-circular of the log ends, selected the appropriate initial value to fit the elliptic boundary value. The smallest Euclidean distance between the boundary points and fitting points was calculated by using least squares principle, thus the best fitting ellipse and log diameter class parameters of major axis and minor axis were gotten. Experiment shows that the proposed algorithms can accurately and rapidly detect the log diameter classes.
{"title":"Rapid detection algorithms for log diameter classes based on stereo vision","authors":"Guanghua Chen, Qiang Zhang, Meiqian Chen, H. Yin","doi":"10.1109/ICSAI.2017.8248480","DOIUrl":"https://doi.org/10.1109/ICSAI.2017.8248480","url":null,"abstract":"Log Diameter Classes 3D measurement with binocular stereo vision system was adopted. According to the log-end histogram feature, a region labeling method was proposed based on the maximum entropy threshold segmentation. Adopting the region labeling based on pixel labeled method of connecting area, each log could be precisely identified and counted by the system. Extraction of log edge using a Canny operator, completed stereo matching based on the epipolar line rectification, then obtained the matching 3D coordinate points. According to the quasi-circular of the log ends, selected the appropriate initial value to fit the elliptic boundary value. The smallest Euclidean distance between the boundary points and fitting points was calculated by using least squares principle, thus the best fitting ellipse and log diameter class parameters of major axis and minor axis were gotten. Experiment shows that the proposed algorithms can accurately and rapidly detect the log diameter classes.","PeriodicalId":285726,"journal":{"name":"2017 4th International Conference on Systems and Informatics (ICSAI)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123333941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/ICSAI.2017.8248499
Minjun Wang, Zhihui Wang, Jinlin Li
This paper proposes a method combining local binary patterns (LBP) and deep convolution neural network. This paper extracts LBP features of face image as an input of CNN, and train the CNN network with the LBP features, then use the trained network for face recognition, so that we can get rid of disadvantages of poor stability of CNN gray scale and identify the trained CNN network more effectively. This algorithm has been experimented on several common face libraries, Indicating that its performance than the traditional methods and general deep learning methods have improved.
{"title":"Deep convolutional neural network applies to face recognition in small and medium databases","authors":"Minjun Wang, Zhihui Wang, Jinlin Li","doi":"10.1109/ICSAI.2017.8248499","DOIUrl":"https://doi.org/10.1109/ICSAI.2017.8248499","url":null,"abstract":"This paper proposes a method combining local binary patterns (LBP) and deep convolution neural network. This paper extracts LBP features of face image as an input of CNN, and train the CNN network with the LBP features, then use the trained network for face recognition, so that we can get rid of disadvantages of poor stability of CNN gray scale and identify the trained CNN network more effectively. This algorithm has been experimented on several common face libraries, Indicating that its performance than the traditional methods and general deep learning methods have improved.","PeriodicalId":285726,"journal":{"name":"2017 4th International Conference on Systems and Informatics (ICSAI)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123635200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/ICSAI.2017.8248397
Guibing Hu, Xue-song Qiu, Luoming Meng
RFID is widely adopted for human activity recognition in interior environments, e.g., elder-caring. Gaining insight through raw RFID data analysis is the key part of the human activity recognition systems. However, the inviolable uncertainty in RFID data, including external environment noise and fragmentary reading (reading collision), increase the difficulty for high-level application widely adoption. In order to address these challenges, we proposing a Hidden Markov Models based data analysis approach in this paper, comparing with previous researches, our method need less limitations and requires only a few prior knowledge about RFID placing, the approach learns from raw RFID data and apply it to analyze the data. Our method analyzes RFID RSSI and 3D-accelerometer data collecting from human movement recognition to overcome aforementioned issues. This system has already been built and successfully deployed in a real experimental room. Result shows that the system run well to obtains an activity recognition with low error rate of 2.5%.
{"title":"Human activity recognition based on Hidden Markov Models using computational RFID","authors":"Guibing Hu, Xue-song Qiu, Luoming Meng","doi":"10.1109/ICSAI.2017.8248397","DOIUrl":"https://doi.org/10.1109/ICSAI.2017.8248397","url":null,"abstract":"RFID is widely adopted for human activity recognition in interior environments, e.g., elder-caring. Gaining insight through raw RFID data analysis is the key part of the human activity recognition systems. However, the inviolable uncertainty in RFID data, including external environment noise and fragmentary reading (reading collision), increase the difficulty for high-level application widely adoption. In order to address these challenges, we proposing a Hidden Markov Models based data analysis approach in this paper, comparing with previous researches, our method need less limitations and requires only a few prior knowledge about RFID placing, the approach learns from raw RFID data and apply it to analyze the data. Our method analyzes RFID RSSI and 3D-accelerometer data collecting from human movement recognition to overcome aforementioned issues. This system has already been built and successfully deployed in a real experimental room. Result shows that the system run well to obtains an activity recognition with low error rate of 2.5%.","PeriodicalId":285726,"journal":{"name":"2017 4th International Conference on Systems and Informatics (ICSAI)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124788607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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