Pub Date : 2022-02-12DOI: 10.1109/AISP53593.2022.9760586
D. Monisha, N. Nelson
Lungs being an important organ in the respiratory system, it is prone to many chronic diseases involving tumor cells. These lung tumors are treatable, if diagnosed at early stage. Among lung tumors, the non-small cell category is irresponsive even for chemotherapy treatment when diagnosed at later stage. This work concentrates on improving the diagnosis of non-small tumor cells at early stage through image processing techniques. The CT image of lungs is used for discriminating the tumor cells from healthy non-tumor cells. Upon using computer aided image processing techniques, the level of accuracy in assessing the tumor cells can be improved. Initially, the noise present in the CT image is removed using Wiener filter by improving the signal to noise ratio. The vascular structures in the image are removed and possible tumor cells are segmented from other healthy cells using region growing technique. After extracting the features, the Support Vector Machine and Naïve Bayesian techniques are used for classifying the tumor cells and healthy cells.
{"title":"Detection of lung tumor using SVM and Bayesian classification","authors":"D. Monisha, N. Nelson","doi":"10.1109/AISP53593.2022.9760586","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760586","url":null,"abstract":"Lungs being an important organ in the respiratory system, it is prone to many chronic diseases involving tumor cells. These lung tumors are treatable, if diagnosed at early stage. Among lung tumors, the non-small cell category is irresponsive even for chemotherapy treatment when diagnosed at later stage. This work concentrates on improving the diagnosis of non-small tumor cells at early stage through image processing techniques. The CT image of lungs is used for discriminating the tumor cells from healthy non-tumor cells. Upon using computer aided image processing techniques, the level of accuracy in assessing the tumor cells can be improved. Initially, the noise present in the CT image is removed using Wiener filter by improving the signal to noise ratio. The vascular structures in the image are removed and possible tumor cells are segmented from other healthy cells using region growing technique. After extracting the features, the Support Vector Machine and Naïve Bayesian techniques are used for classifying the tumor cells and healthy cells.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"1 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88318246","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 : 2022-02-12DOI: 10.1109/AISP53593.2022.9760616
Harshit Harsh, Akhil Indraganti, S. Vanambathina, Bharat Siva Yaswanth Ramanam, V. S. Chandu, Hari Kishan Kondaveeti
Toned voice study is gaining importance due to advancement in the music industry. The breaking down of toned voice and its backtracking is similar to carrying images from the source domain to the target domain while preserving its content representation. For our case, the mixed voice prints were transformed into their constituent component. The drawback of U-Net convolutional architecture is that the learning rate may come down in the middle layers for deeper models, so there is some risk if the network learning is ignored in some cases where the abstract features are represented in those layers. In this work, we proclaim the methodology CGRUN for the task of singing voice division. It leads to a causal system that is naturally suitable for real-time processing applications. The speech processing application is the segregation of toned voices for voice mixing. Through software evaluation, this experiment confirms the use of CGRUN for toned voice separation. The technical term used for toned voice segregation and its backtracking is Music Information Retrieval (MIR).
{"title":"Convolutional GRU Networks based Singing Voice Separation","authors":"Harshit Harsh, Akhil Indraganti, S. Vanambathina, Bharat Siva Yaswanth Ramanam, V. S. Chandu, Hari Kishan Kondaveeti","doi":"10.1109/AISP53593.2022.9760616","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760616","url":null,"abstract":"Toned voice study is gaining importance due to advancement in the music industry. The breaking down of toned voice and its backtracking is similar to carrying images from the source domain to the target domain while preserving its content representation. For our case, the mixed voice prints were transformed into their constituent component. The drawback of U-Net convolutional architecture is that the learning rate may come down in the middle layers for deeper models, so there is some risk if the network learning is ignored in some cases where the abstract features are represented in those layers. In this work, we proclaim the methodology CGRUN for the task of singing voice division. It leads to a causal system that is naturally suitable for real-time processing applications. The speech processing application is the segregation of toned voices for voice mixing. Through software evaluation, this experiment confirms the use of CGRUN for toned voice separation. The technical term used for toned voice segregation and its backtracking is Music Information Retrieval (MIR).","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"1 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89218479","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 : 2022-02-12DOI: 10.1109/AISP53593.2022.9760576
Amogh Sawant, Shahid Shaikh, Dharmesh Sharma
Artificial Intelligence (AI) is the way into the future. Many undertakings are currently overseen by an AI rather than a human; nonetheless, many tasks that are as yet overseen by people can be better done utilizing an AI. However, since the AI innovation isn’t cutting edge as yet, it is unimaginable for now. Thus, we desire to foster an AI prepared through computer games, and for it to master intricate and pragmatic abilities playing them. This is conceivable through the intellectual abilities needed to play computer games and their dynamic and tangled climate. Video games are exceptionally valuable since we can promptly investigate how the specialist performs by contrasting its score with different players. We can imagine video games as a microcosm of human capacity since they are so various and pervasive across human culture. In this way, they are extraordinarily significant to evaluate and demonstrate AI.
{"title":"Game AI using Reinforcement Learning","authors":"Amogh Sawant, Shahid Shaikh, Dharmesh Sharma","doi":"10.1109/AISP53593.2022.9760576","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760576","url":null,"abstract":"Artificial Intelligence (AI) is the way into the future. Many undertakings are currently overseen by an AI rather than a human; nonetheless, many tasks that are as yet overseen by people can be better done utilizing an AI. However, since the AI innovation isn’t cutting edge as yet, it is unimaginable for now. Thus, we desire to foster an AI prepared through computer games, and for it to master intricate and pragmatic abilities playing them. This is conceivable through the intellectual abilities needed to play computer games and their dynamic and tangled climate. Video games are exceptionally valuable since we can promptly investigate how the specialist performs by contrasting its score with different players. We can imagine video games as a microcosm of human capacity since they are so various and pervasive across human culture. In this way, they are extraordinarily significant to evaluate and demonstrate AI.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"95 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90622149","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 : 2022-02-12DOI: 10.1109/AISP53593.2022.9760657
J. Karthiyayini, Arpita Chowdary Vantipalli, Darshana Sailu Tanti, K. Malvika Ravi, Krtin Kannan
This paper is propelled from the generally existing project which is undertaking under the smart water quality management, which addresses an IoT (Internet of things) based brilliant water quality observing (SWQM) framework which we call it AquaSwach that guides in proper estimation of water condition dependent on five actual parameters i.e., temperature, pH, electric conductivity and turbidity properties and water purity estimation each time you drink water. Six sensors relate to Arduino-Mega in discrete way to detect the water parameters. Extracted data from the sensors are transmitted to a desktop application developed in NET platform and compared with the WHO (World Health Organization) standard values. The system consist of several sensors is used to measuring physical and chemical parameters of the water. The parameters such as temperature, PH, turbidity, flow sensor of the water can be measured. The measured values from the sensors can be processed by the core controller. The Arduino mega model can be used as a core controller. Finally, the sensor data can be viewed on internet using WI-FI system. With the help of a wireless GSM (Global System for Mobile communication), the customer will be informed about the condition of the filter, and the service provider is immediately informed of replacing the filter.
{"title":"IOT based AquaSwach","authors":"J. Karthiyayini, Arpita Chowdary Vantipalli, Darshana Sailu Tanti, K. Malvika Ravi, Krtin Kannan","doi":"10.1109/AISP53593.2022.9760657","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760657","url":null,"abstract":"This paper is propelled from the generally existing project which is undertaking under the smart water quality management, which addresses an IoT (Internet of things) based brilliant water quality observing (SWQM) framework which we call it AquaSwach that guides in proper estimation of water condition dependent on five actual parameters i.e., temperature, pH, electric conductivity and turbidity properties and water purity estimation each time you drink water. Six sensors relate to Arduino-Mega in discrete way to detect the water parameters. Extracted data from the sensors are transmitted to a desktop application developed in NET platform and compared with the WHO (World Health Organization) standard values. The system consist of several sensors is used to measuring physical and chemical parameters of the water. The parameters such as temperature, PH, turbidity, flow sensor of the water can be measured. The measured values from the sensors can be processed by the core controller. The Arduino mega model can be used as a core controller. Finally, the sensor data can be viewed on internet using WI-FI system. With the help of a wireless GSM (Global System for Mobile communication), the customer will be informed about the condition of the filter, and the service provider is immediately informed of replacing the filter.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"60 1","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90726117","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 : 2022-02-12DOI: 10.1109/AISP53593.2022.9760663
A. Patil, Rama Bansidhar Dan, N. Priya
Flower Species recognition has been a major field in image processing. Recognition fails many times the reason behind this is lack of knowledge about medicinal flower among the normal ones. Vision based technique has been used to create automated system which helps even common man to identify flowers around them. The main goal is to extract certain features from the input image by applying different techniques like machine learning and computer vision in order to classify image. In this paper, it is analyzed that flowers recognition has given success rate using image processing.
{"title":"Flower Identification System Using Vision Based Technique","authors":"A. Patil, Rama Bansidhar Dan, N. Priya","doi":"10.1109/AISP53593.2022.9760663","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760663","url":null,"abstract":"Flower Species recognition has been a major field in image processing. Recognition fails many times the reason behind this is lack of knowledge about medicinal flower among the normal ones. Vision based technique has been used to create automated system which helps even common man to identify flowers around them. The main goal is to extract certain features from the input image by applying different techniques like machine learning and computer vision in order to classify image. In this paper, it is analyzed that flowers recognition has given success rate using image processing.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"229 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79691247","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 : 2022-02-12DOI: 10.1109/AISP53593.2022.9760584
Pratikhya Raut, U. Nanda, D. Panda, H. Nguyen
Double gate junction-less tunnel field effect transistor (DGJL-TFET) is investigated in this paper. The presence of double gate enhances high control over the channel for current conduction and the performance analysis of various parameters like input and output characteristics have been carried out by varying its dielectric materials with different dielectric constant and changing the thickness of oxide material. The complete device simulation and analysis are made using TCAD simulator. The simulation results depicting that the dielectric materials with high dielectric constant yields good electrical characteristics and the oxide with the least thickness value helps in better current conduction with good Ion/Ioff ratio. So this device is a promising device for low power application. Also by using dielectric with high dielectric constant increases the ON current which makes the device more flexible in nature.
{"title":"Performance Analysis of Double Gate Junctionless TFET with respect to different high-k materials and oxide thickness","authors":"Pratikhya Raut, U. Nanda, D. Panda, H. Nguyen","doi":"10.1109/AISP53593.2022.9760584","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760584","url":null,"abstract":"Double gate junction-less tunnel field effect transistor (DGJL-TFET) is investigated in this paper. The presence of double gate enhances high control over the channel for current conduction and the performance analysis of various parameters like input and output characteristics have been carried out by varying its dielectric materials with different dielectric constant and changing the thickness of oxide material. The complete device simulation and analysis are made using TCAD simulator. The simulation results depicting that the dielectric materials with high dielectric constant yields good electrical characteristics and the oxide with the least thickness value helps in better current conduction with good Ion/Ioff ratio. So this device is a promising device for low power application. Also by using dielectric with high dielectric constant increases the ON current which makes the device more flexible in nature.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"136 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89757028","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 : 2022-02-12DOI: 10.1109/AISP53593.2022.9760655
I. Berrada, Fatimazahra Barramou, O. B. Alami
Every day, each bank around the world has to analyze many credit applications from its customers and prospects, individuals, professionals, or companies. Banks develop their rating system based on different parameters but most of them do not take benefit of the tremendous set of Big Data available and gathered continuously. To extract valuable information, Big Data analysis (BDA) and artificial intelligence (AI) lead to interesting applications for the banking industry such as segmentation, customized service, customer relationship management, fraud detection, credit risk assessment, and in all back, middle, and front office missions. This article presents the benefit of artificial intelligence for credit risk assessment. A state of art for the actual research advance is discussed concerning this specific item. To handle this review, we first focused on the keywords to capture and analyze the available articles of experts. We limited the period from 2016 to 2021 to skim the recent advances. Researchers have explored different methods with feature selection, classification, and prediction. Algorithms of Data mining, machine learning (supervised and unsupervised), and deep learning (artificial neural networks) are very different and tackle various aspects to be explored. With these advances, banks can become smart and propose a better and quicker service while preserving themselves from losses due to credit defaulters. Support vector machine, Catboost, decision tree, and logistic regression have delivered interesting results according to the studied researches.
{"title":"A review of Artificial Intelligence approach for credit risk assessment","authors":"I. Berrada, Fatimazahra Barramou, O. B. Alami","doi":"10.1109/AISP53593.2022.9760655","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760655","url":null,"abstract":"Every day, each bank around the world has to analyze many credit applications from its customers and prospects, individuals, professionals, or companies. Banks develop their rating system based on different parameters but most of them do not take benefit of the tremendous set of Big Data available and gathered continuously. To extract valuable information, Big Data analysis (BDA) and artificial intelligence (AI) lead to interesting applications for the banking industry such as segmentation, customized service, customer relationship management, fraud detection, credit risk assessment, and in all back, middle, and front office missions. This article presents the benefit of artificial intelligence for credit risk assessment. A state of art for the actual research advance is discussed concerning this specific item. To handle this review, we first focused on the keywords to capture and analyze the available articles of experts. We limited the period from 2016 to 2021 to skim the recent advances. Researchers have explored different methods with feature selection, classification, and prediction. Algorithms of Data mining, machine learning (supervised and unsupervised), and deep learning (artificial neural networks) are very different and tackle various aspects to be explored. With these advances, banks can become smart and propose a better and quicker service while preserving themselves from losses due to credit defaulters. Support vector machine, Catboost, decision tree, and logistic regression have delivered interesting results according to the studied researches.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"1987 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82260305","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 : 2022-02-12DOI: 10.1109/AISP53593.2022.9760650
U. Pattapu, Suneel Miriyala
In this paper, a simple structure based hexagonal microstrip-patch antenna has designed for wireless energy transmission. In this proposed structure, spurious harmonic suppression has achieved by using H shaped slot, defected ground structure (DGS) and open stub. Spurious frequencies has suppressed up to fourth harmonics. Designed antenna is compact size, operating frequency is 5.8 GHz and 10 dB return loss impedance bandwidth of 5.48-6.08 GHz (10.38%) simulated gain of 3.8 dB and radiation efficiency of more than 79% have also been achieved from the designed structure. Because of its fruitful properties, this antenna is well suited for wireless energy transfer applications.
{"title":"A 5.80 GHz Harmonic Suppression Antenna for Wireless Energy Transfer Application","authors":"U. Pattapu, Suneel Miriyala","doi":"10.1109/AISP53593.2022.9760650","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760650","url":null,"abstract":"In this paper, a simple structure based hexagonal microstrip-patch antenna has designed for wireless energy transmission. In this proposed structure, spurious harmonic suppression has achieved by using H shaped slot, defected ground structure (DGS) and open stub. Spurious frequencies has suppressed up to fourth harmonics. Designed antenna is compact size, operating frequency is 5.8 GHz and 10 dB return loss impedance bandwidth of 5.48-6.08 GHz (10.38%) simulated gain of 3.8 dB and radiation efficiency of more than 79% have also been achieved from the designed structure. Because of its fruitful properties, this antenna is well suited for wireless energy transfer applications.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"80 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72851311","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 : 2022-02-12DOI: 10.1109/AISP53593.2022.9760547
Reva Nagi, S. S. Tripathy
Reliable and accurate identification of disease is required for protecting the plant from pathogens and obviating the yield loss. The advent of computer vision and image processing techniques has encouraged contribution in disease identification systems in plants. This paper proposes a fuzzy feature extraction technique and Probabilistic Neural Network (PNN) for the identification of grapevine diseases using leaf images. The color features are extracted using fuzzy color histogram. Then, the extracted features are fed to a PNN classifier for grapevine disease classification. The proposed technique achieves a maximum recognition accuracy of 95.54% on the test dataset. On comparing the proposed system with upcoming deep learning techniques, the former is found to be more efficient for small training data.
{"title":"Disease identification in grapevine leaf images using fuzzy-PNN","authors":"Reva Nagi, S. S. Tripathy","doi":"10.1109/AISP53593.2022.9760547","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760547","url":null,"abstract":"Reliable and accurate identification of disease is required for protecting the plant from pathogens and obviating the yield loss. The advent of computer vision and image processing techniques has encouraged contribution in disease identification systems in plants. This paper proposes a fuzzy feature extraction technique and Probabilistic Neural Network (PNN) for the identification of grapevine diseases using leaf images. The color features are extracted using fuzzy color histogram. Then, the extracted features are fed to a PNN classifier for grapevine disease classification. The proposed technique achieves a maximum recognition accuracy of 95.54% on the test dataset. On comparing the proposed system with upcoming deep learning techniques, the former is found to be more efficient for small training data.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"1 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87289311","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 : 2022-02-12DOI: 10.1109/AISP53593.2022.9760673
D. K. Rout, Pihu Ranjan, Disha Mukherjee, Sananda Kumar, Deepa Das
Internet-of-Things (IoT) is technology that promises to connect every thing. IoT for human health monitoring is particularly of interest as it promises to revolutionize health care. And that is possible with the integration of wireless body area network (BAN) with IoT. Radio channel play an important role in designing efficient transceivers for IoT capable BAN sensors. Recently, multiple researchers have worked on modeling the radio propagation in and around the human body. Such measurements not only help understand the signal propagation, which is the obvious outcome, they also help researchers design efficient and optimized transceivers. Thus, in this paper, we measure the path loss in a body surface to external scenario for the 900 MHz band in indoor scenarios and model it into a simple pathloss model. The results in the article have been compiled from more than 15000 measurements in typical real-life scenario.
{"title":"Radio Propagation Modeling for Body Surface to External Communication Scenario","authors":"D. K. Rout, Pihu Ranjan, Disha Mukherjee, Sananda Kumar, Deepa Das","doi":"10.1109/AISP53593.2022.9760673","DOIUrl":"https://doi.org/10.1109/AISP53593.2022.9760673","url":null,"abstract":"Internet-of-Things (IoT) is technology that promises to connect every thing. IoT for human health monitoring is particularly of interest as it promises to revolutionize health care. And that is possible with the integration of wireless body area network (BAN) with IoT. Radio channel play an important role in designing efficient transceivers for IoT capable BAN sensors. Recently, multiple researchers have worked on modeling the radio propagation in and around the human body. Such measurements not only help understand the signal propagation, which is the obvious outcome, they also help researchers design efficient and optimized transceivers. Thus, in this paper, we measure the path loss in a body surface to external scenario for the 900 MHz band in indoor scenarios and model it into a simple pathloss model. The results in the article have been compiled from more than 15000 measurements in typical real-life scenario.","PeriodicalId":6793,"journal":{"name":"2022 2nd International Conference on Artificial Intelligence and Signal Processing (AISP)","volume":"42 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90838962","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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