Pub Date : 2016-11-01DOI: 10.1109/TENCON.2016.7848268
J. Rajevenceltha, C. Santhosh Kumar, A. Anand Kumar
Multi-parameter patient monitor (MPM) uses vital signs, heart rate, blood pressure, oxygen saturation (SpO2) and respiration rate to identify the condition of patients. In this work, we use a support vector machine (SVM) backend classifier with four vital signs as its input and experimented using different kernels. It was observed that the SVM with a radial basis function kernel (SVM-RBF) outperforms the other kernels. Compared to non-linear SVMs, the linear SVM is computationally more efficient. Therefore, in this work we explore the use of feature mapping using locality constrained linear coding (LLC) to linearize the input features and thereby enhancing the performance of MPMs with a linear SVM (LLC-linSVM). To improve the performance further, we normalized LLC features by l2-norm (nLLC-linSVM). A performance improvement of 0.53% and 0.96% absolute for overall classification accuracy and specificity respectively was obtained over the baseline SVM-RBF system. However, a deterioration in the sensitivity was noted. To take advantage of both SVM-RBF and nLLC-linSVM, we finally fused the decision scores of both the systems. The fusion weights were estimated empirically using a dataset which is used neither for training nor testing. After decision fusion, we achieved a performance improvement of 0.90% absolute for classification accuracy, 0.24% absolute for sensitivity and 1.12% absolute for specificity compared to the baseline. All the systems were compared using receiver operating characteristics (ROC) and the results show that the performance of the fused system is better than the individual systems.
{"title":"Improving the performance of multi-parameter patient monitors using feature mapping and decision fusion","authors":"J. Rajevenceltha, C. Santhosh Kumar, A. Anand Kumar","doi":"10.1109/TENCON.2016.7848268","DOIUrl":"https://doi.org/10.1109/TENCON.2016.7848268","url":null,"abstract":"Multi-parameter patient monitor (MPM) uses vital signs, heart rate, blood pressure, oxygen saturation (SpO2) and respiration rate to identify the condition of patients. In this work, we use a support vector machine (SVM) backend classifier with four vital signs as its input and experimented using different kernels. It was observed that the SVM with a radial basis function kernel (SVM-RBF) outperforms the other kernels. Compared to non-linear SVMs, the linear SVM is computationally more efficient. Therefore, in this work we explore the use of feature mapping using locality constrained linear coding (LLC) to linearize the input features and thereby enhancing the performance of MPMs with a linear SVM (LLC-linSVM). To improve the performance further, we normalized LLC features by l2-norm (nLLC-linSVM). A performance improvement of 0.53% and 0.96% absolute for overall classification accuracy and specificity respectively was obtained over the baseline SVM-RBF system. However, a deterioration in the sensitivity was noted. To take advantage of both SVM-RBF and nLLC-linSVM, we finally fused the decision scores of both the systems. The fusion weights were estimated empirically using a dataset which is used neither for training nor testing. After decision fusion, we achieved a performance improvement of 0.90% absolute for classification accuracy, 0.24% absolute for sensitivity and 1.12% absolute for specificity compared to the baseline. All the systems were compared using receiver operating characteristics (ROC) and the results show that the performance of the fused system is better than the individual systems.","PeriodicalId":246458,"journal":{"name":"2016 IEEE Region 10 Conference (TENCON)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132064216","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 : 2016-11-01DOI: 10.1109/TENCON.2016.7848712
Y. Hu, A. Vibhute, S. Foong, G. Soh
This paper presents an autonomous docking strategy for miniature spherical rolling robots. Due to their small physical size, these robots do not have onboard depth sensing capabilities, and have difficulty docking autonomously to a charging station. This docking/charging station has been augmented with a 2D LiDAR, which is used to scan the immediate area to detect the position of the robot; a waypoint is then calculated and transmitted via a low power wireless network. This forms a closed-loop position control system, eliminating any accumulated position errors due to odometry or heading drift. This novel system is able to detect a spherical robot, which is devoid of any distinct features, and more importantly does not require any depth or vision sensors to be installed on the miniature robot for the docking procedure. The described strategy is implemented and practical test results are illustrated.
{"title":"Autonomous docking of miniature spherical robots with an external 2D laser rangefinder","authors":"Y. Hu, A. Vibhute, S. Foong, G. Soh","doi":"10.1109/TENCON.2016.7848712","DOIUrl":"https://doi.org/10.1109/TENCON.2016.7848712","url":null,"abstract":"This paper presents an autonomous docking strategy for miniature spherical rolling robots. Due to their small physical size, these robots do not have onboard depth sensing capabilities, and have difficulty docking autonomously to a charging station. This docking/charging station has been augmented with a 2D LiDAR, which is used to scan the immediate area to detect the position of the robot; a waypoint is then calculated and transmitted via a low power wireless network. This forms a closed-loop position control system, eliminating any accumulated position errors due to odometry or heading drift. This novel system is able to detect a spherical robot, which is devoid of any distinct features, and more importantly does not require any depth or vision sensors to be installed on the miniature robot for the docking procedure. The described strategy is implemented and practical test results are illustrated.","PeriodicalId":246458,"journal":{"name":"2016 IEEE Region 10 Conference (TENCON)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132468599","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 : 2016-11-01DOI: 10.1109/TENCON.2016.7848304
A. Garrido, I. Garrido, E. Otaola, J. Lekube, Fares M’zoughi, Khaoula Ghefiri, Diclobin G. Mundackamattam, I. Oleagordia
Climate change is challenging the current worldwide model of power generation. In this sense, European Union is promoting a deep transition collected in the 20-20-20 targets and the 2050 Energy Roadmap. These adjectives must be achieved by developing the use of clean, carbon-free energies, as it is the case of the renewableenergies and in particular of the ocean energy. The main problem with these kinds of energies is to reach a commercially mature stage so they can compete with conventional power sources. Therefore, it is crucial to reduce generation costs and increase the efficiency of the existing devices. With this regard, the work presents the modelling and experimental validation of the capture chamber of an Oscillating Water Column (OWC)-based powerplant. Although the study of the turbine and the generator may be considered a quite well-known matter, the control-oriented modelling of the capture chamber still deserves a further study to improve the power generation. In this work, a model obtained analytically of the OWC chamber is developed and numerically implemented. The model proposed is also validated and affords excellent results.
{"title":"Capture chamber modelling and validation in OWC on-shore devices","authors":"A. Garrido, I. Garrido, E. Otaola, J. Lekube, Fares M’zoughi, Khaoula Ghefiri, Diclobin G. Mundackamattam, I. Oleagordia","doi":"10.1109/TENCON.2016.7848304","DOIUrl":"https://doi.org/10.1109/TENCON.2016.7848304","url":null,"abstract":"Climate change is challenging the current worldwide model of power generation. In this sense, European Union is promoting a deep transition collected in the 20-20-20 targets and the 2050 Energy Roadmap. These adjectives must be achieved by developing the use of clean, carbon-free energies, as it is the case of the renewableenergies and in particular of the ocean energy. The main problem with these kinds of energies is to reach a commercially mature stage so they can compete with conventional power sources. Therefore, it is crucial to reduce generation costs and increase the efficiency of the existing devices. With this regard, the work presents the modelling and experimental validation of the capture chamber of an Oscillating Water Column (OWC)-based powerplant. Although the study of the turbine and the generator may be considered a quite well-known matter, the control-oriented modelling of the capture chamber still deserves a further study to improve the power generation. In this work, a model obtained analytically of the OWC chamber is developed and numerically implemented. The model proposed is also validated and affords excellent results.","PeriodicalId":246458,"journal":{"name":"2016 IEEE Region 10 Conference (TENCON)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132521213","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 : 2016-11-01DOI: 10.1109/TENCON.2016.7848032
Sharmistha Bardhan, Md. Anwar Ullah, H. Ahmed, Mohammod Golam Rabbani, K. Mamun
Autism is a neurodevelopmental disorder that limits social, behavioral and communication skills of a child. Since early intervention can improve child's condition, early screening and diagnosis are necessary. Different tools were developed for screening, diagnosing and monitoring intervention. However, no tools have integrated all these steps and in developing countries, these discrete tools are not used due to lack of resources and expertise. Autism Express is an integrated cloud based framework that can perform screening, track diagnosis outcome, provide online parent counseling and monitor intervention progress automatically for 0–17 years old children. It includes a smart device based mobile application for autism screening. Then based on the outcome, the Virtual and Actual assessment processes confirm autism. For positive cases, it automatically activates parent counseling, connects resources and tracks intervention status for effective management. It is expected that the proposed system will bring positive changes in autism diagnosis, intervention and management processes especially in a resource limited setting and also raise awareness about it.
{"title":"Autism Express - a cloud based framework for autism screening, confirmation and intervention","authors":"Sharmistha Bardhan, Md. Anwar Ullah, H. Ahmed, Mohammod Golam Rabbani, K. Mamun","doi":"10.1109/TENCON.2016.7848032","DOIUrl":"https://doi.org/10.1109/TENCON.2016.7848032","url":null,"abstract":"Autism is a neurodevelopmental disorder that limits social, behavioral and communication skills of a child. Since early intervention can improve child's condition, early screening and diagnosis are necessary. Different tools were developed for screening, diagnosing and monitoring intervention. However, no tools have integrated all these steps and in developing countries, these discrete tools are not used due to lack of resources and expertise. Autism Express is an integrated cloud based framework that can perform screening, track diagnosis outcome, provide online parent counseling and monitor intervention progress automatically for 0–17 years old children. It includes a smart device based mobile application for autism screening. Then based on the outcome, the Virtual and Actual assessment processes confirm autism. For positive cases, it automatically activates parent counseling, connects resources and tracks intervention status for effective management. It is expected that the proposed system will bring positive changes in autism diagnosis, intervention and management processes especially in a resource limited setting and also raise awareness about it.","PeriodicalId":246458,"journal":{"name":"2016 IEEE Region 10 Conference (TENCON)","volume":"236 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130000962","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 : 2016-11-01DOI: 10.1109/TENCON.2016.7848336
E. Magsino, K. Obias, John Paul Samarista, M. Say, John A. Tan
This research presents a redundant flight recovery system during a motor failure in an octocopter platform. This proposed recovery system exploits the property that the octocopter can be derived by combining two quadrotor systems. During motor failure, the octocopter switches to a stable quadrotor flight configuration while immediately landing the octocopter to prevent further damage to installed sensor and equipment and the octocopter platform. The redundant system utilizes PID and fuzzy logic controllers to stabilize altitude and attitude respectively.
{"title":"A redundant flight recovery system implementation during an octocopter failure","authors":"E. Magsino, K. Obias, John Paul Samarista, M. Say, John A. Tan","doi":"10.1109/TENCON.2016.7848336","DOIUrl":"https://doi.org/10.1109/TENCON.2016.7848336","url":null,"abstract":"This research presents a redundant flight recovery system during a motor failure in an octocopter platform. This proposed recovery system exploits the property that the octocopter can be derived by combining two quadrotor systems. During motor failure, the octocopter switches to a stable quadrotor flight configuration while immediately landing the octocopter to prevent further damage to installed sensor and equipment and the octocopter platform. The redundant system utilizes PID and fuzzy logic controllers to stabilize altitude and attitude respectively.","PeriodicalId":246458,"journal":{"name":"2016 IEEE Region 10 Conference (TENCON)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133944086","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 : 2016-11-01DOI: 10.1109/TENCON.2016.7848362
Grace R. Kingsy, R. Manimegalai, D. Geetha, S. Rajathi, K. Usha, Baseria N. Raabiathul
Air pollution affects body organs and human systems in addition to the environment. Smart air pollution monitoring consists of wireless sensor nodes, server and a database to store the monitored data. Huge amounts of data are generated by gas sensors in air pollution monitoring system. Traditional methods are too complex to process and analyze the voluminous data. The heterogeneous data are converted into meaningful information by using data mining approaches for decision making. The K-Means algorithm is one of the frequently used clustering method in data mining for clustering massive data sets. In this paper, enhanced K-Means clustering algorithm is proposed to analyze the air pollution data. The correlation coefficient is calculated from the real time monitored pollutant datasets. The Air Quality Index (AQI) value is calculated from the correlation co-efficient to determine the air pollution level in a particular place. The proposed enhanced K-Means clustering algorithm is compared with Possibilistic Fuzzy C-Means (PFCM) clustering algorithm in terms of accuracy and execution time. Experimental results show that the proposed enhanced K-Means clustering algorithm gives AQI value in higher accuracy with less execution time for when compared to existing techniques.
{"title":"Air pollution analysis using enhanced K-Means clustering algorithm for real time sensor data","authors":"Grace R. Kingsy, R. Manimegalai, D. Geetha, S. Rajathi, K. Usha, Baseria N. Raabiathul","doi":"10.1109/TENCON.2016.7848362","DOIUrl":"https://doi.org/10.1109/TENCON.2016.7848362","url":null,"abstract":"Air pollution affects body organs and human systems in addition to the environment. Smart air pollution monitoring consists of wireless sensor nodes, server and a database to store the monitored data. Huge amounts of data are generated by gas sensors in air pollution monitoring system. Traditional methods are too complex to process and analyze the voluminous data. The heterogeneous data are converted into meaningful information by using data mining approaches for decision making. The K-Means algorithm is one of the frequently used clustering method in data mining for clustering massive data sets. In this paper, enhanced K-Means clustering algorithm is proposed to analyze the air pollution data. The correlation coefficient is calculated from the real time monitored pollutant datasets. The Air Quality Index (AQI) value is calculated from the correlation co-efficient to determine the air pollution level in a particular place. The proposed enhanced K-Means clustering algorithm is compared with Possibilistic Fuzzy C-Means (PFCM) clustering algorithm in terms of accuracy and execution time. Experimental results show that the proposed enhanced K-Means clustering algorithm gives AQI value in higher accuracy with less execution time for when compared to existing techniques.","PeriodicalId":246458,"journal":{"name":"2016 IEEE Region 10 Conference (TENCON)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134344797","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 : 2016-11-01DOI: 10.1109/TENCON.2016.7848412
Ye Tiant, Takumi Saito, C. Ann
Recently, high quality data transmission system has been widely researched. To achieve the better BER performance, several detection schemes in Multiple-Input Multiple-Output (MIMO) system have been studied. In the MIMO system, Maximum-Likelihood Detection (MLD) yields the optimal BER performance. However, it requires enormous computational complexity. Regarding the problem of actual implementation, Maximum-Likelihood (ML) Detection with QR Decomposition and M-algorithm (QRM-MLD) has been proposed for reducing the system complexity. On the other hand, this detection shows a little worse BER performance than MLD. Since QRM-MLD is used with a fewer symbol replica candidates than MLD, the error in the former detection stage causes an increase of the error in the latter stage. In this paper, we propose an optimal permutation of the channel matrix using QR Decomposition. The proposed scheme arranges channel matrix optimally, thereby absolute values of the diagonal components in upper triangular matrix are arranged ascending order. From the simulation results, the proposed scheme can improve the BER performance compared with the conventional method.
{"title":"Optimal channel ranking using multiple channel permutation for QRM-MLD","authors":"Ye Tiant, Takumi Saito, C. Ann","doi":"10.1109/TENCON.2016.7848412","DOIUrl":"https://doi.org/10.1109/TENCON.2016.7848412","url":null,"abstract":"Recently, high quality data transmission system has been widely researched. To achieve the better BER performance, several detection schemes in Multiple-Input Multiple-Output (MIMO) system have been studied. In the MIMO system, Maximum-Likelihood Detection (MLD) yields the optimal BER performance. However, it requires enormous computational complexity. Regarding the problem of actual implementation, Maximum-Likelihood (ML) Detection with QR Decomposition and M-algorithm (QRM-MLD) has been proposed for reducing the system complexity. On the other hand, this detection shows a little worse BER performance than MLD. Since QRM-MLD is used with a fewer symbol replica candidates than MLD, the error in the former detection stage causes an increase of the error in the latter stage. In this paper, we propose an optimal permutation of the channel matrix using QR Decomposition. The proposed scheme arranges channel matrix optimally, thereby absolute values of the diagonal components in upper triangular matrix are arranged ascending order. From the simulation results, the proposed scheme can improve the BER performance compared with the conventional method.","PeriodicalId":246458,"journal":{"name":"2016 IEEE Region 10 Conference (TENCON)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131490762","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 : 2016-11-01DOI: 10.1109/TENCON.2016.7848561
T. Bindima, Manju Manuel, E. Elias
This paper proposes a novel transformation for the design of two-dimensional (2D) finite impulse response (FIR) wideband filters with perfect circular symmetry. The proposed transformation is based on the kth order McClellan transformation and is found to be successful in generating precise circular contours even for wideband filters. The proposed method outperforms the state of the art transformations in terms of contour approximation accuracy. Design examples illustrate the effectiveness of the proposed transformation.
{"title":"An efficient transformation for two dimensional circularly symmetric wideband FIR filters","authors":"T. Bindima, Manju Manuel, E. Elias","doi":"10.1109/TENCON.2016.7848561","DOIUrl":"https://doi.org/10.1109/TENCON.2016.7848561","url":null,"abstract":"This paper proposes a novel transformation for the design of two-dimensional (2D) finite impulse response (FIR) wideband filters with perfect circular symmetry. The proposed transformation is based on the kth order McClellan transformation and is found to be successful in generating precise circular contours even for wideband filters. The proposed method outperforms the state of the art transformations in terms of contour approximation accuracy. Design examples illustrate the effectiveness of the proposed transformation.","PeriodicalId":246458,"journal":{"name":"2016 IEEE Region 10 Conference (TENCON)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131513377","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 : 2016-11-01DOI: 10.1109/TENCON.2016.7848473
Fuping Zhong, Lihong Ma
Image annotation aims to automatically predict a set of relevant keywords for an image that describe its semantics. Nearest Neighbor (NN) based methods have been successfully applied to address image annotation problems. In this paper,a novel method is introduced to improve the performance of annotating images. Firstly, we present a relevance feedback algorithm based on Multi-view non-negative matrix factorization (MultiNMF) to improve the retrieval performance during the process of querying the nearest neighbors. Secondly, a semantic co-occurrence (SC) based strategy is derived to effectively adjust the order of the annotated keywords. Experiment results on Corel5K dataset demonstrate that the proposed method outperforms those previous similar methods.
{"title":"Image annotation using multi-view non-negative matrix factorization and semantic co-occurrence","authors":"Fuping Zhong, Lihong Ma","doi":"10.1109/TENCON.2016.7848473","DOIUrl":"https://doi.org/10.1109/TENCON.2016.7848473","url":null,"abstract":"Image annotation aims to automatically predict a set of relevant keywords for an image that describe its semantics. Nearest Neighbor (NN) based methods have been successfully applied to address image annotation problems. In this paper,a novel method is introduced to improve the performance of annotating images. Firstly, we present a relevance feedback algorithm based on Multi-view non-negative matrix factorization (MultiNMF) to improve the retrieval performance during the process of querying the nearest neighbors. Secondly, a semantic co-occurrence (SC) based strategy is derived to effectively adjust the order of the annotated keywords. Experiment results on Corel5K dataset demonstrate that the proposed method outperforms those previous similar methods.","PeriodicalId":246458,"journal":{"name":"2016 IEEE Region 10 Conference (TENCON)","volume":"643 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132960984","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 : 2016-11-01DOI: 10.1109/TENCON.2016.7848430
Mark Angelo C. Purio, Michael Joshua P.L. Sacopon, John Jason O. Salvador, Ferdinand Alerick B. Velasco
Balikbayan boxes sent by OFW's abroad are delivered by freight forwarders to their rightful recipients. But before arriving at the recipient's residence these packages pass through a series of transfers and transactions (foreign forwarder, shipping company, Bureau of Customs, local forwarder, etc.). In every transaction and transfer, the balikbayan box is vulnerable to different circumstances. The security of the items inside is at stake. I-Box (Innovated Balikbayan box Operation Express) is an innovation to the common delivery system that tracks and monitors the condition of the balikbayan box for secured delivery thus solving the flaws of the normal delivery system. A point to point implementation of this design enhances the monitoring and tracking of the boxes. The realized design uses RFID (Radio Frequency Identification) tags to monitor and track the exact location of the box that is unique to every box making the identification of the box non-reproducible.
{"title":"Development of the system and method for delivery using Radio Frequency Identification (I-BOX)","authors":"Mark Angelo C. Purio, Michael Joshua P.L. Sacopon, John Jason O. Salvador, Ferdinand Alerick B. Velasco","doi":"10.1109/TENCON.2016.7848430","DOIUrl":"https://doi.org/10.1109/TENCON.2016.7848430","url":null,"abstract":"Balikbayan boxes sent by OFW's abroad are delivered by freight forwarders to their rightful recipients. But before arriving at the recipient's residence these packages pass through a series of transfers and transactions (foreign forwarder, shipping company, Bureau of Customs, local forwarder, etc.). In every transaction and transfer, the balikbayan box is vulnerable to different circumstances. The security of the items inside is at stake. I-Box (Innovated Balikbayan box Operation Express) is an innovation to the common delivery system that tracks and monitors the condition of the balikbayan box for secured delivery thus solving the flaws of the normal delivery system. A point to point implementation of this design enhances the monitoring and tracking of the boxes. The realized design uses RFID (Radio Frequency Identification) tags to monitor and track the exact location of the box that is unique to every box making the identification of the box non-reproducible.","PeriodicalId":246458,"journal":{"name":"2016 IEEE Region 10 Conference (TENCON)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132966525","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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