Pub Date : 2017-11-01DOI: 10.1109/ICAWST.2017.8256461
Ruo-Wei Hung, Jun-Lin Li, Chih-Han Lin
Supergrid graphs are first introduced by us and their structures are derived from grid and triangular-grid graphs. The Hamiltonian path problem on general supergrid graphs is a NP-complete problem. A graph is said to be Hamiltonian connected if a Hamiltonian path between any two nodes in it does exist. In the past, deciding whether or not a general supergrid graph contains a Hamiltonian path has been proved to be NP-complete. Very recently, we verified the Hamiltonian connectivity of some special supergrid graphs, including triangular, parallelogram, trapezoid, and rectangular supergrid graphs, except few conditions. In this paper, the Hamiltonian connectivity of alphabet supergrid graphs will be verifed. There are 26 types of alphabet supergrid graphs in which every capital letter is represented by a type of alphabet supergrid graphs. We will provide constructive proofs to verify the Hamiltonian connectivity of L-, F-, C-, and E-alphabet supergrid graphs. The results can be used to verify the Hamiltonian connectivity of other alphabet supergrid graphs with similar structure, such as G-, H-, J-, I-, O, P-, T-, S-, and U-alphabet supergrid graphs. The application of the Hamiltonian connectivity of alphabet supergrid graphs can be to compute the minimum stitching track of computer embroidery machines while a string is sewed into an object.
{"title":"The Hamiltonian connectivity of some alphabet supergrid graphs","authors":"Ruo-Wei Hung, Jun-Lin Li, Chih-Han Lin","doi":"10.1109/ICAWST.2017.8256461","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256461","url":null,"abstract":"Supergrid graphs are first introduced by us and their structures are derived from grid and triangular-grid graphs. The Hamiltonian path problem on general supergrid graphs is a NP-complete problem. A graph is said to be Hamiltonian connected if a Hamiltonian path between any two nodes in it does exist. In the past, deciding whether or not a general supergrid graph contains a Hamiltonian path has been proved to be NP-complete. Very recently, we verified the Hamiltonian connectivity of some special supergrid graphs, including triangular, parallelogram, trapezoid, and rectangular supergrid graphs, except few conditions. In this paper, the Hamiltonian connectivity of alphabet supergrid graphs will be verifed. There are 26 types of alphabet supergrid graphs in which every capital letter is represented by a type of alphabet supergrid graphs. We will provide constructive proofs to verify the Hamiltonian connectivity of L-, F-, C-, and E-alphabet supergrid graphs. The results can be used to verify the Hamiltonian connectivity of other alphabet supergrid graphs with similar structure, such as G-, H-, J-, I-, O, P-, T-, S-, and U-alphabet supergrid graphs. The application of the Hamiltonian connectivity of alphabet supergrid graphs can be to compute the minimum stitching track of computer embroidery machines while a string is sewed into an object.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"55 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":"116788188","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/ICAWST.2017.8256481
Chiun-Li Chin, Bing-Jhang Lin, Guei-Ru Wu, Tzu-Chieh Weng, Cheng-Shiun Yang, Rui-Cih Su, Yu-Jen Pan
Over the past few years, stroke has been among the top ten causes of death in Taiwan. Stroke symptoms belong to an emergency condition, the sooner the patient is treated, the more chance the patient recovers. However, the location of ischemic stroke in the CT image is not obvious, so the diagnosis need to rely on doctors to assess the image. The purpose of this paper is to develop an automated early ischemic stroke detection system using CNN deep learning algorithm. After entering the CT image of the brain, the system will begin image preprocessing to remove the impossible area which is not the possible of the stroke area. Then we will select the patch images and use Data Augmentation method to increase the number of patch images. Finally, we will input the patch images into the convolutional neural network for training and testing. In this paper, we used 256 patch images to train and test a CNN module that it had the ability to recognize the ischemic stroke. From the experimental results, we can find that the accuracy of the proposed method is higher than 90%. It means that the method proposed in this paper can effectively assist the doctor to diagnose.
{"title":"An automated early ischemic stroke detection system using CNN deep learning algorithm","authors":"Chiun-Li Chin, Bing-Jhang Lin, Guei-Ru Wu, Tzu-Chieh Weng, Cheng-Shiun Yang, Rui-Cih Su, Yu-Jen Pan","doi":"10.1109/ICAWST.2017.8256481","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256481","url":null,"abstract":"Over the past few years, stroke has been among the top ten causes of death in Taiwan. Stroke symptoms belong to an emergency condition, the sooner the patient is treated, the more chance the patient recovers. However, the location of ischemic stroke in the CT image is not obvious, so the diagnosis need to rely on doctors to assess the image. The purpose of this paper is to develop an automated early ischemic stroke detection system using CNN deep learning algorithm. After entering the CT image of the brain, the system will begin image preprocessing to remove the impossible area which is not the possible of the stroke area. Then we will select the patch images and use Data Augmentation method to increase the number of patch images. Finally, we will input the patch images into the convolutional neural network for training and testing. In this paper, we used 256 patch images to train and test a CNN module that it had the ability to recognize the ischemic stroke. From the experimental results, we can find that the accuracy of the proposed method is higher than 90%. It means that the method proposed in this paper can effectively assist the doctor to diagnose.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","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":"132979625","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/ICAWST.2017.8256439
Jeang-Kuo Chen, Wei-Zhe Lee
Enterprises widely use RDB to store business data, but a complex query usually takes a long time to join some tables for obtaining accurate data. Therefore, RDB is not suitable for applications that only require fast query but not care the query result is accurate or not. Hadoop HBase just has this feature. This paper presents a method that converts RDB data into nonrelational data of Hadoop HBase. Enterprises can quickly build a new HBase database through the original RDB to reduce business costs.
{"title":"Data conversion from RDB to HBase","authors":"Jeang-Kuo Chen, Wei-Zhe Lee","doi":"10.1109/ICAWST.2017.8256439","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256439","url":null,"abstract":"Enterprises widely use RDB to store business data, but a complex query usually takes a long time to join some tables for obtaining accurate data. Therefore, RDB is not suitable for applications that only require fast query but not care the query result is accurate or not. Hadoop HBase just has this feature. This paper presents a method that converts RDB data into nonrelational data of Hadoop HBase. Enterprises can quickly build a new HBase database through the original RDB to reduce business costs.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"9 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":"122512402","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}
With the video capturing devices (e.g., webcam, digital camera, and so on) being popular, image processing has become a complex research topic. It can be widely used in many different fields, such as medical image, identity identification, computer vision, face detection, and skin detection. After taking a picture, it used to do skin detection. In this paper, we propose a method which detecting facial wrinkle by Laws' Mask filter and Gabor wavelets transformation. Afterward, connected component labeling algorithm can detect connected regions in wrinkles' binary digital images. Then, this system could classify whether connected regions are wrinkle or not by counting each label's length. However, there are also a few error detection when the wrinkle is too slim, but the accurate rate also could reach 80%. We will improve the accurate rate of this system continually.
{"title":"Facial wrinkle detection with texture feature","authors":"Chiun-Li Chin, Ho-Feng Chen, Bing-Jhang Lin, Ming-Chieh Chi, Wei-En Chen, Zih-Yi Yang","doi":"10.1109/ICAWST.2017.8256475","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256475","url":null,"abstract":"With the video capturing devices (e.g., webcam, digital camera, and so on) being popular, image processing has become a complex research topic. It can be widely used in many different fields, such as medical image, identity identification, computer vision, face detection, and skin detection. After taking a picture, it used to do skin detection. In this paper, we propose a method which detecting facial wrinkle by Laws' Mask filter and Gabor wavelets transformation. Afterward, connected component labeling algorithm can detect connected regions in wrinkles' binary digital images. Then, this system could classify whether connected regions are wrinkle or not by counting each label's length. However, there are also a few error detection when the wrinkle is too slim, but the accurate rate also could reach 80%. We will improve the accurate rate of this system continually.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"21 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":"122894619","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/ICAWST.2017.8256528
Chih-Yu Wang, Jia-Jung Wang, Jeng-Yiiang Li, Shing-Hong Liu
Dyslexia is one of learning disorder symptoms. Patients with dyslexia have varying degrees of difficulties in reading comprehension, including texts and words, resulting in poor academic performance and seriously affecting their learning achievements. This study attempted to explore the phenomenon of inferior ability in reciting and writing Chinese characters for dyslexic students through the use of electroencephalogram (EEG) analysis. The study recruited eight dyslexic and eight normal children, aged around 10 years old. The results showed that children with dyslexia present significantly lower EEG power of θ, α, low-α and high-α oscillations than normal students in both recitation and writing. For the EEG power of β oscillation, however, no significant difference was present in both recitation and writing activities. In perspective cerebral cortex regions, the EEG power of most bands in frontal, parietal, occipital and temporal lobes for dyslexic students were significantly lower than normal students in both recitation and writing activities. These findings can indirectly reflect the inferior performance of dyslexic students in their learning. Thus, the current results in the study can be utilized as references for policy setting to improve the student learning achievement.
{"title":"Exploring the performance of dyslexic children in reciting and writing Chinese characters through the use of electroencephalogram","authors":"Chih-Yu Wang, Jia-Jung Wang, Jeng-Yiiang Li, Shing-Hong Liu","doi":"10.1109/ICAWST.2017.8256528","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256528","url":null,"abstract":"Dyslexia is one of learning disorder symptoms. Patients with dyslexia have varying degrees of difficulties in reading comprehension, including texts and words, resulting in poor academic performance and seriously affecting their learning achievements. This study attempted to explore the phenomenon of inferior ability in reciting and writing Chinese characters for dyslexic students through the use of electroencephalogram (EEG) analysis. The study recruited eight dyslexic and eight normal children, aged around 10 years old. The results showed that children with dyslexia present significantly lower EEG power of θ, α, low-α and high-α oscillations than normal students in both recitation and writing. For the EEG power of β oscillation, however, no significant difference was present in both recitation and writing activities. In perspective cerebral cortex regions, the EEG power of most bands in frontal, parietal, occipital and temporal lobes for dyslexic students were significantly lower than normal students in both recitation and writing activities. These findings can indirectly reflect the inferior performance of dyslexic students in their learning. Thus, the current results in the study can be utilized as references for policy setting to improve the student learning achievement.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"10 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":"127760523","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/ICAWST.2017.8256496
Hung-Chi Chu, Chi-Kun Wang
Traffic congestion is one of the important issues in developed and developing countries. Due to the rapid development of information communication technology, the use of data mining technology in the intelligent traffic monitoring system has become the current trend of research and development. Use the information collected by the vehicle detector (VD) to analyze the causes of traffic congestion and find a suitable road junction time period classification. The k-means algorithm was used in cluster analysis to group the traffic flow and divide traffic time. According to the more precise analysis, the traffic congestion problem can be solved by the appropriate traffic signal lights cycle arrangements. The experimental result showed that the proposed mechanism can provide a suitable traffic flow classification and can indicate the difference of traffic pattern between weekday and weekend.
{"title":"Using K-means algorithm for the road junction time period analysis","authors":"Hung-Chi Chu, Chi-Kun Wang","doi":"10.1109/ICAWST.2017.8256496","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256496","url":null,"abstract":"Traffic congestion is one of the important issues in developed and developing countries. Due to the rapid development of information communication technology, the use of data mining technology in the intelligent traffic monitoring system has become the current trend of research and development. Use the information collected by the vehicle detector (VD) to analyze the causes of traffic congestion and find a suitable road junction time period classification. The k-means algorithm was used in cluster analysis to group the traffic flow and divide traffic time. According to the more precise analysis, the traffic congestion problem can be solved by the appropriate traffic signal lights cycle arrangements. The experimental result showed that the proposed mechanism can provide a suitable traffic flow classification and can indicate the difference of traffic pattern between weekday and weekend.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"15 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":"117150037","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/ICAWST.2017.8256449
Yu-Huei Cheng, Ching-Ming Lai, J. Teh
As the energy crisis and environmental pollution problems become increasingly serious, hybrid electric vehicles (HEVs) have been seen as the world's more fuel-efficient and cleaner vehicles to provide one of the solutions. In this study, we designed the appropriate control strategy parameters use memetic algorithm (MA) with two small population sizes 5 and 10 and iterations 1000 to make the HEV not only reduce the toxic emissions, but also keep the road driving vehicle performance while reducing fuel consumption (FC). In this study, the software ADVISOR was used as a simulation tool and the driving cycle UDDS was used to evaluate FC, emissions and vehicle dynamic performance. Compared with the preset parallel HEV defined in ADVISOR, the results show that MA is a powerful tool for improving the control strategy parameters of the parallel HEV to improve FC and emissions without sacrificing vehicle performance. The method helps to mitigate the energy crisis and environmental pollution problems.
{"title":"Memetic algorithm for fuel economy and low emissions parallel hybrid electric vehicles","authors":"Yu-Huei Cheng, Ching-Ming Lai, J. Teh","doi":"10.1109/ICAWST.2017.8256449","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256449","url":null,"abstract":"As the energy crisis and environmental pollution problems become increasingly serious, hybrid electric vehicles (HEVs) have been seen as the world's more fuel-efficient and cleaner vehicles to provide one of the solutions. In this study, we designed the appropriate control strategy parameters use memetic algorithm (MA) with two small population sizes 5 and 10 and iterations 1000 to make the HEV not only reduce the toxic emissions, but also keep the road driving vehicle performance while reducing fuel consumption (FC). In this study, the software ADVISOR was used as a simulation tool and the driving cycle UDDS was used to evaluate FC, emissions and vehicle dynamic performance. Compared with the preset parallel HEV defined in ADVISOR, the results show that MA is a powerful tool for improving the control strategy parameters of the parallel HEV to improve FC and emissions without sacrificing vehicle performance. The method helps to mitigate the energy crisis and environmental pollution problems.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"147 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":"115693082","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/ICAWST.2017.8256513
Chung-Hong Lee, Hsin-Chang Yang, Bo-Chun Xu
The ability to compute the degree of semantic similarity of real world events represented by social data and tracking the cross-event clues on a huge collection of social messages (i.e., tweets) has proven useful for a wide variety of event-awareness applications. The developed system should be able to overcome the challenge of high redundancy in social corpus (e.g. Twitter messages) and the sparsity inherent in their short texts. In this work, we propose a method to explore implicit relations on Twitter-based detected event datasets using an online event detection and word embedding technique for event analysis. The preliminary empirical result showed that the combined framework in our system is sensible for mining more unknown knowledge about event impacts.
{"title":"Exploring cross-event relations on Twitter datasets via topic recommendation and word embedding","authors":"Chung-Hong Lee, Hsin-Chang Yang, Bo-Chun Xu","doi":"10.1109/ICAWST.2017.8256513","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256513","url":null,"abstract":"The ability to compute the degree of semantic similarity of real world events represented by social data and tracking the cross-event clues on a huge collection of social messages (i.e., tweets) has proven useful for a wide variety of event-awareness applications. The developed system should be able to overcome the challenge of high redundancy in social corpus (e.g. Twitter messages) and the sparsity inherent in their short texts. In this work, we propose a method to explore implicit relations on Twitter-based detected event datasets using an online event detection and word embedding technique for event analysis. The preliminary empirical result showed that the combined framework in our system is sensible for mining more unknown knowledge about event impacts.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"18 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":"124940149","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/ICAWST.2017.8256512
Yi-Chun Chang, Jian-Wei Li, Fu-Syuan Yang
The push notation services have emerged as a result of promotion of information communication technologies when diversified multimedia services are available to smart device users who hope to learn multimedia updates via networks anytime and anyplace. For the evolving multimedia services, the IP Multimedia Subsystem (IMS) is the core technology of the Next Generation Network (NGN) and the platform of integrated multimedia application services, which become the tendency through IMS, as well as the push notification services for multimedia contents particularly. Thus, with IMS serving as the environment for development of a network system, the multimedia broadcasting system on multiple IMS network platforms, in which the multimedia subject content subscription and push notification mechanism is available, was designed and implemented in this research.
{"title":"The implementation of the multimedia content subscription and push notification mechanism based on the IP multimedia subsystem","authors":"Yi-Chun Chang, Jian-Wei Li, Fu-Syuan Yang","doi":"10.1109/ICAWST.2017.8256512","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256512","url":null,"abstract":"The push notation services have emerged as a result of promotion of information communication technologies when diversified multimedia services are available to smart device users who hope to learn multimedia updates via networks anytime and anyplace. For the evolving multimedia services, the IP Multimedia Subsystem (IMS) is the core technology of the Next Generation Network (NGN) and the platform of integrated multimedia application services, which become the tendency through IMS, as well as the push notification services for multimedia contents particularly. Thus, with IMS serving as the environment for development of a network system, the multimedia broadcasting system on multiple IMS network platforms, in which the multimedia subject content subscription and push notification mechanism is available, was designed and implemented in this research.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"13 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":"123167063","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/ICAWST.2017.8256458
Yi-Jui Chen, H. Chien
Greenhouse agriculture has the advantage of protecting the plants from outside harsh conditions and providing suitable conditions for plant growth; it can effectively improve the crop yield and quality. But the traditional monitoring/control system of greenhouse construction costs a lot and the traditional control interface is not friendly (some are just manual setting); it is, therefore, not very cost-effective, friendly and high-productive. With the advent of the cloud computing and low-cost Internet-of-Things (IoT) systems, we can apply these low-cost and effective technologies to monitor environment conditions/plant growth and control the facilities. In addition to conveniently monitor/control greenhouse facilities, a real-time platform to dynamically analyzing the collected data can greatly improve the efficiency of greenhouse cultivation, maintenance costs and decision making. In this study, a low-cost greenhouse monitoring system is developed for small-sized and medium-sized greenhouse installations with real-time data analysis. With RethinkDB, raspyberry pi, tornado, and Splunk, we develop an efficient-and-effective greenhouse system to achieve the above goals. This system design acts as a promising solution/bridge toward the final precise agriculture.
{"title":"IoT-based green house system with splunk data analysis","authors":"Yi-Jui Chen, H. Chien","doi":"10.1109/ICAWST.2017.8256458","DOIUrl":"https://doi.org/10.1109/ICAWST.2017.8256458","url":null,"abstract":"Greenhouse agriculture has the advantage of protecting the plants from outside harsh conditions and providing suitable conditions for plant growth; it can effectively improve the crop yield and quality. But the traditional monitoring/control system of greenhouse construction costs a lot and the traditional control interface is not friendly (some are just manual setting); it is, therefore, not very cost-effective, friendly and high-productive. With the advent of the cloud computing and low-cost Internet-of-Things (IoT) systems, we can apply these low-cost and effective technologies to monitor environment conditions/plant growth and control the facilities. In addition to conveniently monitor/control greenhouse facilities, a real-time platform to dynamically analyzing the collected data can greatly improve the efficiency of greenhouse cultivation, maintenance costs and decision making. In this study, a low-cost greenhouse monitoring system is developed for small-sized and medium-sized greenhouse installations with real-time data analysis. With RethinkDB, raspyberry pi, tornado, and Splunk, we develop an efficient-and-effective greenhouse system to achieve the above goals. This system design acts as a promising solution/bridge toward the final precise agriculture.","PeriodicalId":378618,"journal":{"name":"2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)","volume":"63 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":"129719046","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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