Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10199866
Junghoon Lee, Seungah Jang, Eunjung Park
This paper designs a FHIR (Fast Healthcare Interoperable Resources) interface to provide a standard clinical data exchange for personal wearable healthcare devices, aiming at taking them as a part of remote medical services. In uploading, the agent converts the series of sensor readings, such as electrocardiogram, to the JSON-based standard format, divides it into several subparts if necessary, finds the references to relevant resources, and submits the request via RESTful API. For download, a Python client specifies the set of search parameters, gets the target resources from the server, converts them to the language-specific data structure, and hands over to the analysis module. Our testbed is implemented, making use of diverse FHIR tools including the FRED resource editor and the HAPI server.
{"title":"Design of a FHIR interface for wearable healthcare devices","authors":"Junghoon Lee, Seungah Jang, Eunjung Park","doi":"10.1109/ICUFN57995.2023.10199866","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10199866","url":null,"abstract":"This paper designs a FHIR (Fast Healthcare Interoperable Resources) interface to provide a standard clinical data exchange for personal wearable healthcare devices, aiming at taking them as a part of remote medical services. In uploading, the agent converts the series of sensor readings, such as electrocardiogram, to the JSON-based standard format, divides it into several subparts if necessary, finds the references to relevant resources, and submits the request via RESTful API. For download, a Python client specifies the set of search parameters, gets the target resources from the server, converts them to the language-specific data structure, and hands over to the analysis module. Our testbed is implemented, making use of diverse FHIR tools including the FRED resource editor and the HAPI server.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128905460","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 : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10199608
Q. V. Toan, Min Young Kim
Semantic segmentation is a complex topic where they assign each pixel of an image with a corresponding class and demand accuracy at objective boundaries. The method plays a vital role in scene-understanding scenarios. For self-driving applications, the input source includes various types of objects such as trucks, people, or traffic signs. One receptive field is only effective in capturing a short range of sizes. Feature pyramid network (FPN) utilizes different fields of view to extract information from the input. The FPN approach obtains the spatial information from the high-resolution feature map and the semantic information from the lower scales. The final feature representation contains coarse and fine details, but it has some drawbacks. They burden the system with extensive computation and reduce the semantic information. In this paper, we devise an effective multiscale predictions network (MPNet) to address these issues. A multiscale pyramid of predictions effectively processes the prominent characteristics of each feature. A pair of adjacent features is combined together to predict the output separately. A lower-scale feature of each prediction is assigned as the contextual contributor, and the other provides coarser information. The contextual branch is passed through the atrous spatial pyramid pooling to improve performance. The segmentation scores are fused to obtain advantages from all predictions. The model is validated by a series of experiments on open data sets. We have achieved good results 76.5% mIoU at 50 FPS on Cityscapes and 43.9% mIoU on Mapillary Vistas.
{"title":"MPNet: Multiscale predictions based on feature pyramid network for semantic segmentation","authors":"Q. V. Toan, Min Young Kim","doi":"10.1109/ICUFN57995.2023.10199608","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10199608","url":null,"abstract":"Semantic segmentation is a complex topic where they assign each pixel of an image with a corresponding class and demand accuracy at objective boundaries. The method plays a vital role in scene-understanding scenarios. For self-driving applications, the input source includes various types of objects such as trucks, people, or traffic signs. One receptive field is only effective in capturing a short range of sizes. Feature pyramid network (FPN) utilizes different fields of view to extract information from the input. The FPN approach obtains the spatial information from the high-resolution feature map and the semantic information from the lower scales. The final feature representation contains coarse and fine details, but it has some drawbacks. They burden the system with extensive computation and reduce the semantic information. In this paper, we devise an effective multiscale predictions network (MPNet) to address these issues. A multiscale pyramid of predictions effectively processes the prominent characteristics of each feature. A pair of adjacent features is combined together to predict the output separately. A lower-scale feature of each prediction is assigned as the contextual contributor, and the other provides coarser information. The contextual branch is passed through the atrous spatial pyramid pooling to improve performance. The segmentation scores are fused to obtain advantages from all predictions. The model is validated by a series of experiments on open data sets. We have achieved good results 76.5% mIoU at 50 FPS on Cityscapes and 43.9% mIoU on Mapillary Vistas.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132525119","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 : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10199969
Jinheng Shao, Chao Zhang
In this paper, a real-time visible light communication (VLC) based on blue laser diode is implemented on field programmable gate array (FPGA) platform. To reduce requirements for signal processing speed, we propose a parallel scheme for modulation and demodulation with simple hardware implementation and low performance loss. Finally, we successfully constructed a VLC system prototype with 600 MHz transmission bandwidth and 2.4 Gbps communication rate over 1 m link distance. Actual measurements shows that $10 -^{5}$ magnitude bit error rate (BER) is achieved without forward error correction (FEC), which demonstrates excellent performance in reported single-source VLC system.
{"title":"2.4 Gbps Real-Time Visible Light Communication System Based on Blue Laser Diode","authors":"Jinheng Shao, Chao Zhang","doi":"10.1109/ICUFN57995.2023.10199969","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10199969","url":null,"abstract":"In this paper, a real-time visible light communication (VLC) based on blue laser diode is implemented on field programmable gate array (FPGA) platform. To reduce requirements for signal processing speed, we propose a parallel scheme for modulation and demodulation with simple hardware implementation and low performance loss. Finally, we successfully constructed a VLC system prototype with 600 MHz transmission bandwidth and 2.4 Gbps communication rate over 1 m link distance. Actual measurements shows that $10 -^{5}$ magnitude bit error rate (BER) is achieved without forward error correction (FEC), which demonstrates excellent performance in reported single-source VLC system.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126832423","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 : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10200998
Geun-Hyeong Kim, Minuk Yang, Geun-Hyeong Kim, Seong-Hwan Eom, Tae-Soo Lee, Seung Park
Although heart failure (HF) diagnosis and treatment techniques have advanced, more than 50% of HF patients are readmitted. Readmission worsens the life quality of patients due to economic and psychological burdens. Therefore, readmission prediction for patients is important to prevent unnecessary readmissions. We used a feature tokenizer transformer (FT-transformer) to predict readmission by embedding all features and analyzing via transformer encoder. Our experiment with 615 HF patients outperformed conventional machine learning models, achieving an area under the curve of 0.7434 within 28 days, 0.7063 within 3 months, and 0.7039 within 6 months. FT-transformer can potentially improve patient outcomes by enabling early interventions to prevent readmissions.
{"title":"Predicting heart failure prognosis using deep learning based on FT-transformer","authors":"Geun-Hyeong Kim, Minuk Yang, Geun-Hyeong Kim, Seong-Hwan Eom, Tae-Soo Lee, Seung Park","doi":"10.1109/ICUFN57995.2023.10200998","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200998","url":null,"abstract":"Although heart failure (HF) diagnosis and treatment techniques have advanced, more than 50% of HF patients are readmitted. Readmission worsens the life quality of patients due to economic and psychological burdens. Therefore, readmission prediction for patients is important to prevent unnecessary readmissions. We used a feature tokenizer transformer (FT-transformer) to predict readmission by embedding all features and analyzing via transformer encoder. Our experiment with 615 HF patients outperformed conventional machine learning models, achieving an area under the curve of 0.7434 within 28 days, 0.7063 within 3 months, and 0.7039 within 6 months. FT-transformer can potentially improve patient outcomes by enabling early interventions to prevent readmissions.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124902466","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 : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10200723
Saud Alhajaj Aldossari, Abdullah Aldosary, Kwang-Cheng Chen
Wireless technology has faced technical challenges that have been unresolved or only partially addressed. Issues such as modeling the wireless channel and selecting the optimum signal This paper proposes using Artificial Intelligence (AI) to tackle these concerns. Machine Learning (ML) can estimate wireless channel states based on available data. Regression and classification techniques have been used to improve communication and meet 5G standards. The effectiveness of ML and Deep Learning techniques were compared to achieve the best accuracy. This paper shows how AI can revolutionize the design of 5G-NR and future generations with an accurate prediction of 99.99%.
{"title":"Overcoming Wireless Channel modeling and Relay Signal Selection Via Artificial Intelligence Techniques in the 5G and Beyond","authors":"Saud Alhajaj Aldossari, Abdullah Aldosary, Kwang-Cheng Chen","doi":"10.1109/ICUFN57995.2023.10200723","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200723","url":null,"abstract":"Wireless technology has faced technical challenges that have been unresolved or only partially addressed. Issues such as modeling the wireless channel and selecting the optimum signal This paper proposes using Artificial Intelligence (AI) to tackle these concerns. Machine Learning (ML) can estimate wireless channel states based on available data. Regression and classification techniques have been used to improve communication and meet 5G standards. The effectiveness of ML and Deep Learning techniques were compared to achieve the best accuracy. This paper shows how AI can revolutionize the design of 5G-NR and future generations with an accurate prediction of 99.99%.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"199 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124929333","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 : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10200399
Chaeyeon Cha, Hyunggon Park
With the increasing development of the Internet of Things (IoT), there is a growing need for efficient resource allocation to the many devices in the IoT system. This need is particularly acute in the case of time-sensitive applications, where fast resource allocation is essential. However, the resource allocation based on the Nash bargaining solution (NBS) necessitates exponentially increasing computational complexity for user dynamic systems. We propose an approach that makes groups based on the requested services and predicts a disagreement point whenever the group size changes, with the aim of reducing the computational complexity to find the NBS. Through simulation results, we demonstrate that our proposed approach outperforms the existing method in terms of execution time to find the NBS, maintaining the optimality in finding NBS.
{"title":"Service-Based Optimal Group Resource Allocation Strategy","authors":"Chaeyeon Cha, Hyunggon Park","doi":"10.1109/ICUFN57995.2023.10200399","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200399","url":null,"abstract":"With the increasing development of the Internet of Things (IoT), there is a growing need for efficient resource allocation to the many devices in the IoT system. This need is particularly acute in the case of time-sensitive applications, where fast resource allocation is essential. However, the resource allocation based on the Nash bargaining solution (NBS) necessitates exponentially increasing computational complexity for user dynamic systems. We propose an approach that makes groups based on the requested services and predicts a disagreement point whenever the group size changes, with the aim of reducing the computational complexity to find the NBS. Through simulation results, we demonstrate that our proposed approach outperforms the existing method in terms of execution time to find the NBS, maintaining the optimality in finding NBS.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127724335","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 : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10200250
P. Srivastav, Hoon Lee
Millimeter wave (mmWave) communication techniques have been regarded as promising solutions for wireless communication networks. However, short wavelength of mmWave signals poses fundamental challenges in estimating wireless channels. This paper tackles the channel estimation problems for frequency selective mmWave imposed on a multiple-input and multiple-output (MIMO) systems. In particular, we leverage the low-rank and sparse properties of mmWave channel matrices. The alternating direction method of multipliers (ADMM) with a relaxation parameter in a symmetrical order is employed. The numerical results exhibit the superiority of proposed methodology in terms of mean-squared-error and spectral efficiency.
{"title":"ADMM-Based Channel Estimation Methods for Millimeter Wave MIMO System","authors":"P. Srivastav, Hoon Lee","doi":"10.1109/ICUFN57995.2023.10200250","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200250","url":null,"abstract":"Millimeter wave (mmWave) communication techniques have been regarded as promising solutions for wireless communication networks. However, short wavelength of mmWave signals poses fundamental challenges in estimating wireless channels. This paper tackles the channel estimation problems for frequency selective mmWave imposed on a multiple-input and multiple-output (MIMO) systems. In particular, we leverage the low-rank and sparse properties of mmWave channel matrices. The alternating direction method of multipliers (ADMM) with a relaxation parameter in a symmetrical order is employed. The numerical results exhibit the superiority of proposed methodology in terms of mean-squared-error and spectral efficiency.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132278501","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 : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10200101
Tri Gia Nguyen, Amit Samanta
In recent years, the rapid development of Wireless Body Area Networks (WBANs) has provided efficient healthcare services to emergent medical patients. Nevertheless, the WBANs provide efficient healthcare services; however, the mobility and interference in WBANs inherently affect the quality of links between sensors and coordinators. Therefore, with poor link qualities, selecting the optimal coordinators among sensor nodes is necessary to minimize the network’s heavy energy consumption rate and traffic load. Additionally, in mobile architecture, it is necessary to offload the medical data efficiently from sensor nodes to selected optimal coordinators to manage the Quality-of-Service (QoS) of sensor nodes. Thus, unlike most existing works in this paper, we propose a fairness-aware data offloading scheme for inter-BAN communication to optimize the traffic load and QoS of WBANs. Extensive simulation results show that FARE improves section rate, data offloading price, and throughput over other existing solutions.
{"title":"Fairness-Aware Data Offloading in Wireless Body Area Networks with QoS Constraint","authors":"Tri Gia Nguyen, Amit Samanta","doi":"10.1109/ICUFN57995.2023.10200101","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200101","url":null,"abstract":"In recent years, the rapid development of Wireless Body Area Networks (WBANs) has provided efficient healthcare services to emergent medical patients. Nevertheless, the WBANs provide efficient healthcare services; however, the mobility and interference in WBANs inherently affect the quality of links between sensors and coordinators. Therefore, with poor link qualities, selecting the optimal coordinators among sensor nodes is necessary to minimize the network’s heavy energy consumption rate and traffic load. Additionally, in mobile architecture, it is necessary to offload the medical data efficiently from sensor nodes to selected optimal coordinators to manage the Quality-of-Service (QoS) of sensor nodes. Thus, unlike most existing works in this paper, we propose a fairness-aware data offloading scheme for inter-BAN communication to optimize the traffic load and QoS of WBANs. Extensive simulation results show that FARE improves section rate, data offloading price, and throughput over other existing solutions.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125431128","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 : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10199477
Da-un Jang, Subin Jo, Gayeon Kim, Jeonghoon Bae, Taejun Choi, Taehyoung Kim
In this paper, we evaluate the performance of sidelink synchronization signal block (SL-SSB) for 5G vehicular-to-everything (V2X) communication systems. The SLSSB serves to establish communication link by synchronizing signals between the vehicles. We first introduce the transmission structure of SL-SSB and related synchronization procedures based on the standard documents presented by 3rd Generation Partnership Project (3GPP). Then, we develop a link level simulator (LLS), and evaluate the SL identity (ID) detection performance based on the SL-SSB and block error rate (BLER) performance for the physical sidelink broadcast channel (PSBCH).
{"title":"Link-Level Performance Evaluation of Sidelink Synchronization Signal Block for 5G V2X","authors":"Da-un Jang, Subin Jo, Gayeon Kim, Jeonghoon Bae, Taejun Choi, Taehyoung Kim","doi":"10.1109/ICUFN57995.2023.10199477","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10199477","url":null,"abstract":"In this paper, we evaluate the performance of sidelink synchronization signal block (SL-SSB) for 5G vehicular-to-everything (V2X) communication systems. The SLSSB serves to establish communication link by synchronizing signals between the vehicles. We first introduce the transmission structure of SL-SSB and related synchronization procedures based on the standard documents presented by 3rd Generation Partnership Project (3GPP). Then, we develop a link level simulator (LLS), and evaluate the SL identity (ID) detection performance based on the SL-SSB and block error rate (BLER) performance for the physical sidelink broadcast channel (PSBCH).","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134144975","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 : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10201138
Jin-Youle Lee, Suwoong Lee, Min Young Kim
Tactile sensors are used in various fields such as automated factories and human collaboration. Tactile sensors exist in a variety of technological ways. In particular, most of the contact determination methods are mainly performed through the detection of the physical surface. In contrast, recently, various Vision-based tactile sensors that can replace the existing method based only on visual data from an image viewed through a camera sensor have been proposed. The hardware proposed in this paper is also a Vision-based tactile sensor, and it is a method that determines contact based only on patterns. In addition, we propose a vision-based tactile sensor as hardware in the form of air bag based on an air cushion. As the biggest feature of the Vision-based tactile sensor is estimation through image reading, it is easy to update various functions through algorithm improvement. Based on these points, through continuous research, we will develop algorithms for position estimation stability improvement, force estimation, and multi-touch discrimination, among at the possibility of application to fields such as cooperative human interaction robots.
{"title":"Visual Tactile Sensor based on Feature Tracking of Patterns for Soft Human-Machine Interaction","authors":"Jin-Youle Lee, Suwoong Lee, Min Young Kim","doi":"10.1109/ICUFN57995.2023.10201138","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10201138","url":null,"abstract":"Tactile sensors are used in various fields such as automated factories and human collaboration. Tactile sensors exist in a variety of technological ways. In particular, most of the contact determination methods are mainly performed through the detection of the physical surface. In contrast, recently, various Vision-based tactile sensors that can replace the existing method based only on visual data from an image viewed through a camera sensor have been proposed. The hardware proposed in this paper is also a Vision-based tactile sensor, and it is a method that determines contact based only on patterns. In addition, we propose a vision-based tactile sensor as hardware in the form of air bag based on an air cushion. As the biggest feature of the Vision-based tactile sensor is estimation through image reading, it is easy to update various functions through algorithm improvement. Based on these points, through continuous research, we will develop algorithms for position estimation stability improvement, force estimation, and multi-touch discrimination, among at the possibility of application to fields such as cooperative human interaction robots.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"17 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134363033","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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