As global markets become more competitive, companies are under pressures to find ways for cutting costs to survive and remain competitive in their respective markets. Therefore, good supplier selection is very important issue in production process and business for cost saving and quality improvement. Most supplier selection models take into account the buyer’s point of view and maximize the buyer’s profit. This does not lead to the best situation for all members of the supply chain. Thus, this study applies analytical hierarchy process (AHP) technique for supplier selection process. In this study, the authors chose 3 main criteria and 14 sub-criteria to evaluate importance level of each criterion in supplier selection process. Following the results, this study finds that product quality, price/cost, and manufacturing capability are the top three supplier selection criteria. Meanwhile, research & development, geographical location, and environment and safety are the least important issues.
{"title":"Supplier Selection for Manufacturing Industries","authors":"Chia-Nan Wang, Dinh-Chien Dang, Quoc-Quan Vu, Yubeng Zeng","doi":"10.1109/AMCON.2018.8614833","DOIUrl":"https://doi.org/10.1109/AMCON.2018.8614833","url":null,"abstract":"As global markets become more competitive, companies are under pressures to find ways for cutting costs to survive and remain competitive in their respective markets. Therefore, good supplier selection is very important issue in production process and business for cost saving and quality improvement. Most supplier selection models take into account the buyer’s point of view and maximize the buyer’s profit. This does not lead to the best situation for all members of the supply chain. Thus, this study applies analytical hierarchy process (AHP) technique for supplier selection process. In this study, the authors chose 3 main criteria and 14 sub-criteria to evaluate importance level of each criterion in supplier selection process. Following the results, this study finds that product quality, price/cost, and manufacturing capability are the top three supplier selection criteria. Meanwhile, research & development, geographical location, and environment and safety are the least important issues.","PeriodicalId":438307,"journal":{"name":"2018 IEEE International Conference on Advanced Manufacturing (ICAM)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114495402","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 : 2018-11-01DOI: 10.1109/AMCON.2018.8614873
Ching-Been Yang, W. Peng, Yan-Wen Huang, H. Chiang
Polypropylene (PP) is a common thermoplastic polymer material with high impact resistance and strong mechanical properties, and it is thus widely used in the industry. With high thermal conductivity and low resistivity, graphene is expected to be used to develop a new generation of electrical components. In this study, we mix blended graphene and PP into a composite material for injection molding specimens. Experiments were designed using an orthogonal array in the Taguchi method to obtain the optimal parameter combination for thermal conductivity, the process parameters including A. injection temperature, B. holding time, C. injection pressure, and D. the graphene ratio. The study results indicate that the optimal parameter combination in the Taguchi analysis was A3BlC2D3, the resulting thermal conductivity coefficient of which was 0.102 (W/m2x2122; K). The optimal parameter combination of the original design in the L9 orthogonal array was A2BlC2D3, the thermal conductivity coefficient of which was 0.081 (W/m2x2122; K). Thus, the improvement rate 25.9%.
{"title":"Analysis of injection molding parameters for graphene/polypropylene composite material with thermal conductivity as quality objective","authors":"Ching-Been Yang, W. Peng, Yan-Wen Huang, H. Chiang","doi":"10.1109/AMCON.2018.8614873","DOIUrl":"https://doi.org/10.1109/AMCON.2018.8614873","url":null,"abstract":"Polypropylene (PP) is a common thermoplastic polymer material with high impact resistance and strong mechanical properties, and it is thus widely used in the industry. With high thermal conductivity and low resistivity, graphene is expected to be used to develop a new generation of electrical components. In this study, we mix blended graphene and PP into a composite material for injection molding specimens. Experiments were designed using an orthogonal array in the Taguchi method to obtain the optimal parameter combination for thermal conductivity, the process parameters including A. injection temperature, B. holding time, C. injection pressure, and D. the graphene ratio. The study results indicate that the optimal parameter combination in the Taguchi analysis was A3BlC2D3, the resulting thermal conductivity coefficient of which was 0.102 (W/m2x2122; K). The optimal parameter combination of the original design in the L9 orthogonal array was A2BlC2D3, the thermal conductivity coefficient of which was 0.081 (W/m2x2122; K). Thus, the improvement rate 25.9%.","PeriodicalId":438307,"journal":{"name":"2018 IEEE International Conference on Advanced Manufacturing (ICAM)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126920099","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 : 2018-11-01DOI: 10.1109/AMCON.2018.8614900
Jung-Wei Chen, C. Kuo, Cheng-Haw Lee, Bi-Wen Lee
Taiwan's high-temperature hot spring area often use the diversification, such as: bathing, cooking, agricultural irrigation. The development of products can reduce the use of gas, electricity and other fuel use, also reduce the generation of carbon emissions. This study will be informed by telephone means of sales of eggs, the hot spring eggs mature time to calculate the amount of electricity, and estimate the required amount of carbon emissions. This study shows that the highest sales of Jinlun hot spring eggs for weekdays can be sold 400, the holiday is as high as 1,000, sales at least is about weekdays 2-3 times. Chihben hot spring area on normal day sales of about 10-65, holiday 20-150, holiday sales of about 2 times the normal day. Hatonozawa hot spring on normal day 39, holiday 181, holiday sales of about 4.5 times the normal day. The estimated carbon emissions from cooking a hot spring egg are between 0.10 and 0.15 (kgCO2e). If the number of days on weekdays is 255 days and the holiday is 110 days, it is estimated that the use of hot spring to cook the eggs process, each hot spring industry can reduce carbon emissions each year. The results show the carbon reductions of Jinlun, Chihpen and Jiuzize Hot Springs will reach 27,982, 7,320 and 4,564 (kgCO2e, respectively.
{"title":"Study of the Reducing Carbon Emission by Using Hot Spring Eggs","authors":"Jung-Wei Chen, C. Kuo, Cheng-Haw Lee, Bi-Wen Lee","doi":"10.1109/AMCON.2018.8614900","DOIUrl":"https://doi.org/10.1109/AMCON.2018.8614900","url":null,"abstract":"Taiwan's high-temperature hot spring area often use the diversification, such as: bathing, cooking, agricultural irrigation. The development of products can reduce the use of gas, electricity and other fuel use, also reduce the generation of carbon emissions. This study will be informed by telephone means of sales of eggs, the hot spring eggs mature time to calculate the amount of electricity, and estimate the required amount of carbon emissions. This study shows that the highest sales of Jinlun hot spring eggs for weekdays can be sold 400, the holiday is as high as 1,000, sales at least is about weekdays 2-3 times. Chihben hot spring area on normal day sales of about 10-65, holiday 20-150, holiday sales of about 2 times the normal day. Hatonozawa hot spring on normal day 39, holiday 181, holiday sales of about 4.5 times the normal day. The estimated carbon emissions from cooking a hot spring egg are between 0.10 and 0.15 (kgCO2e). If the number of days on weekdays is 255 days and the holiday is 110 days, it is estimated that the use of hot spring to cook the eggs process, each hot spring industry can reduce carbon emissions each year. The results show the carbon reductions of Jinlun, Chihpen and Jiuzize Hot Springs will reach 27,982, 7,320 and 4,564 (kgCO2e, respectively.","PeriodicalId":438307,"journal":{"name":"2018 IEEE International Conference on Advanced Manufacturing (ICAM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125796420","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 : 2018-11-01DOI: 10.1109/AMCON.2018.8615044
Matthias Milan Strljic, T. Korb, T. Tasci, Erik-Felix Tinsel, Daniel Pawlowicz, O. Riedel, A. Lechler
For flexible and highly networked industry 4.0 production processes, software components are becoming more and more significant for reconfiguring production systems or facilitating complex functionalities. Standards for communication such as OPC UA have a crucial role in the data exchange required in this context. However, these systems adopt the static properties from their domain, which have led to their success and widespread use in Industry 4.0. The most critical core difficulties with OPC UA are the definition of communication mechanisms and the data model to be used in a strictly coupled environment. Because of their central client-server architecture and missing communication patterns, these systems do not offer the necessary flexibility and platform independence to use the entire spectrum of possible software tools efficiently. Especially negatively affected is the initial effort to integrate such systems and to guarantee the scalability of the infrastructure later on. With a focus on these challenges, the message-based communication framework XSC has been developed for the shop-floor, which uses the high-performance ZeroMQ framework and the data format Google Protocol Buffers for platform independence and a high degree of efficiency. It has a scalable and distributed multi-agent architecture that provides a distributed registry for the usage and provision of microservice components. Besides, multiple communication patterns were provided to meet the requirements of both environments, shop-floor, and cloud computing applications.
{"title":"A platform-independent communication framework for the simplified development of shop-floor applications as microservice components*","authors":"Matthias Milan Strljic, T. Korb, T. Tasci, Erik-Felix Tinsel, Daniel Pawlowicz, O. Riedel, A. Lechler","doi":"10.1109/AMCON.2018.8615044","DOIUrl":"https://doi.org/10.1109/AMCON.2018.8615044","url":null,"abstract":"For flexible and highly networked industry 4.0 production processes, software components are becoming more and more significant for reconfiguring production systems or facilitating complex functionalities. Standards for communication such as OPC UA have a crucial role in the data exchange required in this context. However, these systems adopt the static properties from their domain, which have led to their success and widespread use in Industry 4.0. The most critical core difficulties with OPC UA are the definition of communication mechanisms and the data model to be used in a strictly coupled environment. Because of their central client-server architecture and missing communication patterns, these systems do not offer the necessary flexibility and platform independence to use the entire spectrum of possible software tools efficiently. Especially negatively affected is the initial effort to integrate such systems and to guarantee the scalability of the infrastructure later on. With a focus on these challenges, the message-based communication framework XSC has been developed for the shop-floor, which uses the high-performance ZeroMQ framework and the data format Google Protocol Buffers for platform independence and a high degree of efficiency. It has a scalable and distributed multi-agent architecture that provides a distributed registry for the usage and provision of microservice components. Besides, multiple communication patterns were provided to meet the requirements of both environments, shop-floor, and cloud computing applications.","PeriodicalId":438307,"journal":{"name":"2018 IEEE International Conference on Advanced Manufacturing (ICAM)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127120575","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}
In smart mariculture, an automatic and accurate prediction of key water quality parameters is a significant and challenge issue. This paper focuses on the prediction of pH and water temperature parameters in key water quality parameters. Firstly, the water quality parameters are preprocessed by improved method. Then, the Pearson correlation coefficient method is used to find the correlation between the water quality parameters. Finally, the SRU (Simple Recurrent Unit) deep learning model is used to establish a prediction model for the key water quality parameters, so as to achieve accurate prediction. Meanwhile, we also evaluate the prediction effect of prediction model built by RNN (Recurrent Neural Network) deep learning network. The experimental results show that the proposed prediction method has higher prediction accuracy than the method based on RNN when the time complexity is similar. The proposed method takes 11.3ms to predict every data in average, and the prediction accuracy can reach 98.91%.
{"title":"Automatic and Accurate Prediction of Key Water Quality Parameters Based on SRU Deep Learning in Mariculture","authors":"Juntao Liu, Chuang Yu, Zhuhua Hu, Yaochi Zhao, Xin Xia, Zhigang Tu, Ruoqing Li","doi":"10.1109/AMCON.2018.8615048","DOIUrl":"https://doi.org/10.1109/AMCON.2018.8615048","url":null,"abstract":"In smart mariculture, an automatic and accurate prediction of key water quality parameters is a significant and challenge issue. This paper focuses on the prediction of pH and water temperature parameters in key water quality parameters. Firstly, the water quality parameters are preprocessed by improved method. Then, the Pearson correlation coefficient method is used to find the correlation between the water quality parameters. Finally, the SRU (Simple Recurrent Unit) deep learning model is used to establish a prediction model for the key water quality parameters, so as to achieve accurate prediction. Meanwhile, we also evaluate the prediction effect of prediction model built by RNN (Recurrent Neural Network) deep learning network. The experimental results show that the proposed prediction method has higher prediction accuracy than the method based on RNN when the time complexity is similar. The proposed method takes 11.3ms to predict every data in average, and the prediction accuracy can reach 98.91%.","PeriodicalId":438307,"journal":{"name":"2018 IEEE International Conference on Advanced Manufacturing (ICAM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129585950","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 : 2018-11-01DOI: 10.1109/AMCON.2018.8614972
Chia-Wei Chao, J. Teng, Bin-Han Liu, Wei-Hao Huang, J. Chiu
An effective Communication Performance Index (CPI) is proposed in this paper to evaluate and monitor the communication performance of Advanced Metering Infrastructure (AMI). Reading success rate and response time acquired from a smart meter are used to design the proposed CPI. The CPIs for Data Concentrator Units (DCUs) and whole AMI can then be extended from meter CPIs. Test results for a small-scale AMI demonstrate the validity of proposed CPI. The proposed CPI can effectively supervise the communication quality and stability of AMI and would be helpful for the future deployment and operation of AMI.
{"title":"An Effective Communication Performance Index for Advanced Metering Infrastructure","authors":"Chia-Wei Chao, J. Teng, Bin-Han Liu, Wei-Hao Huang, J. Chiu","doi":"10.1109/AMCON.2018.8614972","DOIUrl":"https://doi.org/10.1109/AMCON.2018.8614972","url":null,"abstract":"An effective Communication Performance Index (CPI) is proposed in this paper to evaluate and monitor the communication performance of Advanced Metering Infrastructure (AMI). Reading success rate and response time acquired from a smart meter are used to design the proposed CPI. The CPIs for Data Concentrator Units (DCUs) and whole AMI can then be extended from meter CPIs. Test results for a small-scale AMI demonstrate the validity of proposed CPI. The proposed CPI can effectively supervise the communication quality and stability of AMI and would be helpful for the future deployment and operation of AMI.","PeriodicalId":438307,"journal":{"name":"2018 IEEE International Conference on Advanced Manufacturing (ICAM)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121111453","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 : 2018-11-01DOI: 10.1109/amcon.2018.8615086
Chia-Ming Jan, Cheng-Bang Huo
According to the requirement of a precisely exposing process of PCB, how well you controlled the beam expanding and guaranteed the half-angle divergence in the PCB inner-layer exposing facility would be significant obviously. Shack-Hartmann (SH) wavefront sensor is a powerful and robust tool focusing on wavefront sensing, meanwhile, which had a good performance even compared with interferometer or shearing interferometer so as to do highly accurate metrology applied to many other fields like position sensing and ocular optics. It’s also available about making sure of the beam quality of the exposing light module in the semiconductor industry. The paper claimed that we adopted an array-type sub-wavelength annular aperture (SAA) micro-structure (12x12) to build up a new wavefront sensing system instead of a conventional micro-lens array. The metrology resolution was limited by its feature size of the micro-lens array about several hundred micrometers. Our proposed design can achieve the specific characteristics of the long depth of focus and sub-wavelength focusing capability, so our prior device would be obviously more suitable for highly precise wavefront measurement.
{"title":"Development of the half-angle divergence metrology applied to the inner-layer exposure facility for PCB industry","authors":"Chia-Ming Jan, Cheng-Bang Huo","doi":"10.1109/amcon.2018.8615086","DOIUrl":"https://doi.org/10.1109/amcon.2018.8615086","url":null,"abstract":"According to the requirement of a precisely exposing process of PCB, how well you controlled the beam expanding and guaranteed the half-angle divergence in the PCB inner-layer exposing facility would be significant obviously. Shack-Hartmann (SH) wavefront sensor is a powerful and robust tool focusing on wavefront sensing, meanwhile, which had a good performance even compared with interferometer or shearing interferometer so as to do highly accurate metrology applied to many other fields like position sensing and ocular optics. It’s also available about making sure of the beam quality of the exposing light module in the semiconductor industry. The paper claimed that we adopted an array-type sub-wavelength annular aperture (SAA) micro-structure (12x12) to build up a new wavefront sensing system instead of a conventional micro-lens array. The metrology resolution was limited by its feature size of the micro-lens array about several hundred micrometers. Our proposed design can achieve the specific characteristics of the long depth of focus and sub-wavelength focusing capability, so our prior device would be obviously more suitable for highly precise wavefront measurement.","PeriodicalId":438307,"journal":{"name":"2018 IEEE International Conference on Advanced Manufacturing (ICAM)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124093837","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 : 2018-11-01DOI: 10.1109/AMCON.2018.8614766
Wen-Yang Chang, Sheng-Jhih Wu, Bo-Shang Lin
For the CNC machine tool, the processing parameters of cutting are a key factor to affect the manufacturing accuracy and tool wear. However, this study proposes a prediction system based on neural network algorithm to estimate the wear of turning tool. For neural network algorithm, the processing parameters, the cutting speed, feed rate and material removal rate are investigated as the input parameters of the BNN. The output parameters of the BNN are the wear of turning tool and the surface accuracy of workpiece. Experimental results showed that the turning cutting wear of prediction accuracy compared with the experiment is 93.44%. The max error of cutting wear between the prediction and the experiment is $15mu mathrm {m}.$
{"title":"Intelligent Prediction Platform of Lathe Machine Based on Back Propagation Neural Network","authors":"Wen-Yang Chang, Sheng-Jhih Wu, Bo-Shang Lin","doi":"10.1109/AMCON.2018.8614766","DOIUrl":"https://doi.org/10.1109/AMCON.2018.8614766","url":null,"abstract":"For the CNC machine tool, the processing parameters of cutting are a key factor to affect the manufacturing accuracy and tool wear. However, this study proposes a prediction system based on neural network algorithm to estimate the wear of turning tool. For neural network algorithm, the processing parameters, the cutting speed, feed rate and material removal rate are investigated as the input parameters of the BNN. The output parameters of the BNN are the wear of turning tool and the surface accuracy of workpiece. Experimental results showed that the turning cutting wear of prediction accuracy compared with the experiment is 93.44%. The max error of cutting wear between the prediction and the experiment is $15mu mathrm {m}.$","PeriodicalId":438307,"journal":{"name":"2018 IEEE International Conference on Advanced Manufacturing (ICAM)","volume":"152 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132557039","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 : 2018-11-01DOI: 10.1109/AMCON.2018.8615057
The-Vinh Do, Ngoc-Chien Vu, Q. Nguyen
In metal machining, the selection of cutting parameters and cooling conditions affects the quality of the cutting process as surface roughness. For this purpose, the effect of cutting fluids (dry, MQL, and Nanofluid based MQL) and cutting parameters (cutting speed, depth-of-cut, and feed rate) on surface roughness was investigated during hard milling of AISI H13 steel. The experiments were carried out by using the Taguchi method and the optimal values were introduced based on an analysis of the signal-to-noise response and ANOVA. The results of the present study indicated that the cooling condition and the feed rate are the factors holding the most influence on surface roughness.
{"title":"Optimization of cooling conditions and cutting parameters during hard milling of AISI H13 steel by using Taguchi method","authors":"The-Vinh Do, Ngoc-Chien Vu, Q. Nguyen","doi":"10.1109/AMCON.2018.8615057","DOIUrl":"https://doi.org/10.1109/AMCON.2018.8615057","url":null,"abstract":"In metal machining, the selection of cutting parameters and cooling conditions affects the quality of the cutting process as surface roughness. For this purpose, the effect of cutting fluids (dry, MQL, and Nanofluid based MQL) and cutting parameters (cutting speed, depth-of-cut, and feed rate) on surface roughness was investigated during hard milling of AISI H13 steel. The experiments were carried out by using the Taguchi method and the optimal values were introduced based on an analysis of the signal-to-noise response and ANOVA. The results of the present study indicated that the cooling condition and the feed rate are the factors holding the most influence on surface roughness.","PeriodicalId":438307,"journal":{"name":"2018 IEEE International Conference on Advanced Manufacturing (ICAM)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131371300","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}
Most tourism attractions are introduced to the public by multimedia information such as text, images and videos. They are well received by visitors but nevertheless fall short in conveying more intuitive and authentic feelings. To overcome this problem, this paper develops an intelligent tourism information system. It uses virtual reality technology to show the landscape information intelligently by detecting what the user sees. The experimental results demonstrate that the system can smartly identify what the user sees and present the corresponding information in real time.
{"title":"Development of Intelligent Tourism Information System Based On Virtual Reality","authors":"Juin-Ling Tseng, Yanxu Jiang, Sheng-Jun Peng, Hsiao-En Wei","doi":"10.1109/AMCON.2018.8615073","DOIUrl":"https://doi.org/10.1109/AMCON.2018.8615073","url":null,"abstract":"Most tourism attractions are introduced to the public by multimedia information such as text, images and videos. They are well received by visitors but nevertheless fall short in conveying more intuitive and authentic feelings. To overcome this problem, this paper develops an intelligent tourism information system. It uses virtual reality technology to show the landscape information intelligently by detecting what the user sees. The experimental results demonstrate that the system can smartly identify what the user sees and present the corresponding information in real time.","PeriodicalId":438307,"journal":{"name":"2018 IEEE International Conference on Advanced Manufacturing (ICAM)","volume":"230 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131749265","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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