Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10199942
Shivani Sanjay Kolekar, Haoyu Chen, Kyungbaek Kim
Recently, there has been a growing interest in researching and developing personalized medical AI services. The previous AI medical systems rarely provided model output compared to multiple datasets and AI models. Currently, only few medical AI systems offer integrated platforms for multidisciplinary precision medicine services. Most existing medical AI systems include AI prognosis with a singular discipline in focus, such as elderly healthcare. This paper proposes a novel digital twin-based integrated precision medicine web-services platform. Our proposed system architecture can be easily implemented in hospital organization interfaces because of the ensured platform independence. Based on the prognostic requirements, we design the service interface with a broad spectrum of patient medical parameter selection (survival time, vital signs, etc.) made available for each medical service. The data related to each patient can be effortlessly updated in real-time. The services will predict and evaluate the accuracy of the visualized output along with the patient clinical information. To verify the feasibility of the proposed architecture, we implemented it with different AI medical services, such as 5 year lung cancer survival prediction, survival analysis with lung tumor segmentation and rapid response analysis. We observed that the architecture showed excellent performance. The architecture for this comprehensive precision medicine web-service platform (Comp-Med) is highly efficient and flexible. It is easily extensible to the new features, services, and updates that may get accommodated in the future.
{"title":"Design of Precision Medicine Web-service Platform Towards Health Care Digital Twin","authors":"Shivani Sanjay Kolekar, Haoyu Chen, Kyungbaek Kim","doi":"10.1109/ICUFN57995.2023.10199942","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10199942","url":null,"abstract":"Recently, there has been a growing interest in researching and developing personalized medical AI services. The previous AI medical systems rarely provided model output compared to multiple datasets and AI models. Currently, only few medical AI systems offer integrated platforms for multidisciplinary precision medicine services. Most existing medical AI systems include AI prognosis with a singular discipline in focus, such as elderly healthcare. This paper proposes a novel digital twin-based integrated precision medicine web-services platform. Our proposed system architecture can be easily implemented in hospital organization interfaces because of the ensured platform independence. Based on the prognostic requirements, we design the service interface with a broad spectrum of patient medical parameter selection (survival time, vital signs, etc.) made available for each medical service. The data related to each patient can be effortlessly updated in real-time. The services will predict and evaluate the accuracy of the visualized output along with the patient clinical information. To verify the feasibility of the proposed architecture, we implemented it with different AI medical services, such as 5 year lung cancer survival prediction, survival analysis with lung tumor segmentation and rapid response analysis. We observed that the architecture showed excellent performance. The architecture for this comprehensive precision medicine web-service platform (Comp-Med) is highly efficient and flexible. It is easily extensible to the new features, services, and updates that may get accommodated in the future.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"2 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":"127032856","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/ICUFN57995.2023.10200815
Ryunosuke Masaoka, G. Tran
In today’s society, wireless communications are available anytime, anywhere. However, there are times when communication may become unavailable. This is when access is concentrated during a large-scale event, a major disaster, or when a base station goes out of service. Therefore, constructing a temporary network that can provide high-capacity communications and flexibly change its service location is being considered. In this paper, we examine the feasibility of combining UAVs, which can be remotely operated and flown unmanned regardless of ground conditions, with a millimeter wave signaling system that can achieve high-speed transmission.
{"title":"Construction and Demonstration of Access Link for Millimeter Wave UAV Base Station Network","authors":"Ryunosuke Masaoka, G. Tran","doi":"10.1109/ICUFN57995.2023.10200815","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200815","url":null,"abstract":"In today’s society, wireless communications are available anytime, anywhere. However, there are times when communication may become unavailable. This is when access is concentrated during a large-scale event, a major disaster, or when a base station goes out of service. Therefore, constructing a temporary network that can provide high-capacity communications and flexibly change its service location is being considered. In this paper, we examine the feasibility of combining UAVs, which can be remotely operated and flown unmanned regardless of ground conditions, with a millimeter wave signaling system that can achieve high-speed transmission.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"29 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":"125244345","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/ICUFN57995.2023.10200550
Young-Jun Cho, Hyeon-Min Yoo, Yu-Vin Kim, E. Hong
Ultra-dense network (UDN) plays a key role in 5G networks to provide ultra-high speed, ultra-low latency data services by densely deploying multiple small cells in specific areas. Numerous small cells can increase network capacity and improve quality of service (QoS), while the network structure has become more complex. Due to the large number of mobile users and frequent handover in these areas, the traffic demand varies rapidly over time. It induces a severe imbalance of mobile traffic load among small cells. The users suffering from load imbalance require frequent handover, which implies a significant increment in energy consumption. In this paper, we propose the cell range adjustment by biasing reference signal received power (RSRP) to achieve load balancing and higher energy efficiency. The values of bias are determined by considering the amount of cell traffic and cell range inversely proportional to the amount of cell traffic. To estimate the amount of cell traffic, the traffic prediction is performed based on long short-term memory (LSTM) algorithm. Simulation results show that our proposed cell range adjustment algorithm increases the throughput of edge users at the cost of a slight decrease in average signal-to-noise ratio (SNR).
{"title":"An Energy-Efficient Ultra-Dense Network Cell Coverage Adjustment Algorithm","authors":"Young-Jun Cho, Hyeon-Min Yoo, Yu-Vin Kim, E. Hong","doi":"10.1109/ICUFN57995.2023.10200550","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200550","url":null,"abstract":"Ultra-dense network (UDN) plays a key role in 5G networks to provide ultra-high speed, ultra-low latency data services by densely deploying multiple small cells in specific areas. Numerous small cells can increase network capacity and improve quality of service (QoS), while the network structure has become more complex. Due to the large number of mobile users and frequent handover in these areas, the traffic demand varies rapidly over time. It induces a severe imbalance of mobile traffic load among small cells. The users suffering from load imbalance require frequent handover, which implies a significant increment in energy consumption. In this paper, we propose the cell range adjustment by biasing reference signal received power (RSRP) to achieve load balancing and higher energy efficiency. The values of bias are determined by considering the amount of cell traffic and cell range inversely proportional to the amount of cell traffic. To estimate the amount of cell traffic, the traffic prediction is performed based on long short-term memory (LSTM) algorithm. Simulation results show that our proposed cell range adjustment algorithm increases the throughput of edge users at the cost of a slight decrease in average signal-to-noise ratio (SNR).","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"111 2 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":"128767892","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}
Pub Date : 2023-07-04DOI: 10.1109/ICUFN57995.2023.10201098
Jaehong Kim, J. Joung, Eui-Rim Jeong
This study proposes a transmit antenna selection (TAS) method. The proposed TAS selects a transmit antenna based on the predicted channel quality by using a convolutional neural network (CNN)-based multi-class classification. The designed CNN directly determines the transmit antenna index based on the past signal-to-noise ratio (SNR), which is obtained through the received signals before the transmission. Since the channel states vary over time, the future SNRs are implicitly predicted through the CNN, and the predictive antenna index is explicitly determined. Here, the channels in the receiving and transmitting periods are symmetric, i.e., a time-division duplex (TDD) system is assumed. Further, various interpolation methods are examined to fill the missing received SNRs. Based on numerical results, it is verified that the proposed CNN-based TAS outperforms two conventional benchmarking methods: i) a TAS method based on the previous SNR and ii) a TAS method based on the average SNR.
{"title":"Transmit Antenna Selection Using CNN-Based Multiclass Classification with Linear Interpolation of Wideband Channels","authors":"Jaehong Kim, J. Joung, Eui-Rim Jeong","doi":"10.1109/ICUFN57995.2023.10201098","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10201098","url":null,"abstract":"This study proposes a transmit antenna selection (TAS) method. The proposed TAS selects a transmit antenna based on the predicted channel quality by using a convolutional neural network (CNN)-based multi-class classification. The designed CNN directly determines the transmit antenna index based on the past signal-to-noise ratio (SNR), which is obtained through the received signals before the transmission. Since the channel states vary over time, the future SNRs are implicitly predicted through the CNN, and the predictive antenna index is explicitly determined. Here, the channels in the receiving and transmitting periods are symmetric, i.e., a time-division duplex (TDD) system is assumed. Further, various interpolation methods are examined to fill the missing received SNRs. Based on numerical results, it is verified that the proposed CNN-based TAS outperforms two conventional benchmarking methods: i) a TAS method based on the previous SNR and ii) a TAS method based on the average SNR.","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":"132996223","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/ICUFN57995.2023.10200629
Rémi Bouchayer, Jae-Yun Jun, H. Chaouchi, Philippe Millet
Expectations of detection systems have risen with the increase in cyber-attacks. In order to detect the latest and future attacks, systems capable of detecting unknown attacks are needed. Among the various approaches offered by machine learning models, anomaly detection methods can address this need. It is possible to use the autoencoder to detect anomalies and therefore attacks. An autoencoder trained on data from normal use is able to detect attacks, unknown to the model. The attack detection is possible by observing the reconstruction error, which is the distance between the input and the reconstructed input resulting from the model. We considered different distance functions to improve the separation between attacks and normal events, and thus, to improve the performance of the autoencoder. We propose to use the cosine function of the angle formed between the actual input vector and the reconstructed input vector, as a distance function to address the problem of overlapping between normal events and attacks. In addition, we used Tree-structured Parzen Estimator algorithm for the optimization of the hyperparameters of the model. We ran our method on the NSL-KDD dataset and compared the obtained results to those of other methods that exist in the literature.
{"title":"In Search of Distance Functions That Improve Autoencoder Performance for Intrusion Detection","authors":"Rémi Bouchayer, Jae-Yun Jun, H. Chaouchi, Philippe Millet","doi":"10.1109/ICUFN57995.2023.10200629","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200629","url":null,"abstract":"Expectations of detection systems have risen with the increase in cyber-attacks. In order to detect the latest and future attacks, systems capable of detecting unknown attacks are needed. Among the various approaches offered by machine learning models, anomaly detection methods can address this need. It is possible to use the autoencoder to detect anomalies and therefore attacks. An autoencoder trained on data from normal use is able to detect attacks, unknown to the model. The attack detection is possible by observing the reconstruction error, which is the distance between the input and the reconstructed input resulting from the model. We considered different distance functions to improve the separation between attacks and normal events, and thus, to improve the performance of the autoencoder. We propose to use the cosine function of the angle formed between the actual input vector and the reconstructed input vector, as a distance function to address the problem of overlapping between normal events and attacks. In addition, we used Tree-structured Parzen Estimator algorithm for the optimization of the hyperparameters of the model. We ran our method on the NSL-KDD dataset and compared the obtained results to those of other methods that exist in the literature.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"11 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114036003","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/ICUFN57995.2023.10199770
S. Yamada, T. Fujii, Katsuya Suto, Koya Sato
Toward next-generation mobile communication systems such as beyond 5G and 6G, non-terrestrial networks (NTNs) have attracted much attention as they extend the coverage of wireless communication services. In NTNs, drones have multiple roles, such as delivery service and transportation, while providing communication services. Therefore, radio environment estimation in three-dimensional (3D) space is crucial for stable drone operations. However, the impact of the surrounding structures and terrain on the radio environment is not well investigated. In this paper, we propose a method to estimate the received power in the direction of altitude by fusing observed signal data and a 3D map that records the geometry of terrain and structures. The proposed method divides the estimation area into a line-of-sight (LOS) altitude and a non-line-of-sight (NLOS) altitude, the estimation values for each range, and then integrates them to obtain the overall estimation values. Through the simulation using the actual measurement dataset, it is demonstrated that the proposed method outperforms the conventional empirical propagation model, i.e., Hata model.
{"title":"Observation Data and 3D Map-based Radio Environment Estimation for Drone Wireless Communications","authors":"S. Yamada, T. Fujii, Katsuya Suto, Koya Sato","doi":"10.1109/ICUFN57995.2023.10199770","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10199770","url":null,"abstract":"Toward next-generation mobile communication systems such as beyond 5G and 6G, non-terrestrial networks (NTNs) have attracted much attention as they extend the coverage of wireless communication services. In NTNs, drones have multiple roles, such as delivery service and transportation, while providing communication services. Therefore, radio environment estimation in three-dimensional (3D) space is crucial for stable drone operations. However, the impact of the surrounding structures and terrain on the radio environment is not well investigated. In this paper, we propose a method to estimate the received power in the direction of altitude by fusing observed signal data and a 3D map that records the geometry of terrain and structures. The proposed method divides the estimation area into a line-of-sight (LOS) altitude and a non-line-of-sight (NLOS) altitude, the estimation values for each range, and then integrates them to obtain the overall estimation values. Through the simulation using the actual measurement dataset, it is demonstrated that the proposed method outperforms the conventional empirical propagation model, i.e., Hata model.","PeriodicalId":341881,"journal":{"name":"2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)","volume":"245 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":"124035161","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/ICUFN57995.2023.10200144
Junhyek Jang, Ki-Taeg Lim, Sanghun Yoon, Daewon Chae, Soo Hyun Jang
In recent years, there are collaborative efforts in establishing protocols between autonomous vehicles(AV) and infrastructures to provide safety and traffic efficiency on the road. Majority of recently proposed cooperative protocols are done using vehicle to vehicle(V2V) based cooperative driving protocol where AVs communicate with each other to negotiate its actions. However, V2V based cooperative protocols has its limitations in environments with obstructions such as buildings. To overcome such shortages, our team previously proposed a vehicle to infrastructure(V2I) based cooperative driving protocol using common surveillance cameras. To maximize V2I efficiency, the visible range of surveillance cameras needs to be extended. Our team present a developed re-identification algorithm between multi-cameras that can extend visible range of surveillance cameras and support real-time applications.
{"title":"Re-ID Technology for V2I based Cooperative Driving Protocol","authors":"Junhyek Jang, Ki-Taeg Lim, Sanghun Yoon, Daewon Chae, Soo Hyun Jang","doi":"10.1109/ICUFN57995.2023.10200144","DOIUrl":"https://doi.org/10.1109/ICUFN57995.2023.10200144","url":null,"abstract":"In recent years, there are collaborative efforts in establishing protocols between autonomous vehicles(AV) and infrastructures to provide safety and traffic efficiency on the road. Majority of recently proposed cooperative protocols are done using vehicle to vehicle(V2V) based cooperative driving protocol where AVs communicate with each other to negotiate its actions. However, V2V based cooperative protocols has its limitations in environments with obstructions such as buildings. To overcome such shortages, our team previously proposed a vehicle to infrastructure(V2I) based cooperative driving protocol using common surveillance cameras. To maximize V2I efficiency, the visible range of surveillance cameras needs to be extended. Our team present a developed re-identification algorithm between multi-cameras that can extend visible range of surveillance cameras and support real-time applications.","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":"128820728","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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