Pub Date : 2022-03-24DOI: 10.1109/wispnet54241.2022.9767171
Anjali Manoj, A. H, Keshav Varma, Naveen P. Nair, V. A, A. D, N. M
Commercial fishing has been made more effective with the use of devices based on Sound Navigation and Ranging (SONAR) technology, across the years. FishFinder is one such device, the first of its kind. It is a very trivial device and is used as the basis for all devices that are available in the market today. This device has a lot of drawbacks; it detect objects that have densities different from water, making it hard to identify whether the waves have hit a pool of fish or not. There is no mechanism to identify the type of fish as well, hence purely depending upon the experience of the fisherman. To overcome these drawbacks, certain modifications that could be incorporated into this device is proposed in this paper. The proposed modifications include a Stabilization mechanism, a Real-time tracking mechanism, and a Machine Learning (ML) model that identifies the type of fish with reference to its unique swim bladder size. These modifications, along with future work ideas, could enhance the effectiveness of the FishFinder device, thereby creating pathways to new advancements in the field.
{"title":"Sonar for Commercial Fishing","authors":"Anjali Manoj, A. H, Keshav Varma, Naveen P. Nair, V. A, A. D, N. M","doi":"10.1109/wispnet54241.2022.9767171","DOIUrl":"https://doi.org/10.1109/wispnet54241.2022.9767171","url":null,"abstract":"Commercial fishing has been made more effective with the use of devices based on Sound Navigation and Ranging (SONAR) technology, across the years. FishFinder is one such device, the first of its kind. It is a very trivial device and is used as the basis for all devices that are available in the market today. This device has a lot of drawbacks; it detect objects that have densities different from water, making it hard to identify whether the waves have hit a pool of fish or not. There is no mechanism to identify the type of fish as well, hence purely depending upon the experience of the fisherman. To overcome these drawbacks, certain modifications that could be incorporated into this device is proposed in this paper. The proposed modifications include a Stabilization mechanism, a Real-time tracking mechanism, and a Machine Learning (ML) model that identifies the type of fish with reference to its unique swim bladder size. These modifications, along with future work ideas, could enhance the effectiveness of the FishFinder device, thereby creating pathways to new advancements in the field.","PeriodicalId":432794,"journal":{"name":"2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121716976","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 : 2022-03-24DOI: 10.1109/wispnet54241.2022.9767108
R. P., R. P.
The antenna in the current study is an attempt to break the available radiation pattern into multiple beams in order to reduce energy waste. To achieve this, a hybrid substrate integrated waveguide (SIW) is generated by combining a cylindrical cavity with a rectangular cavity. A cross-shaped slot is engraved on the top and bottom face of the cylindrical cavity to allow the antenna to generate six major lobes. At the operating frequency of 5 GHz, the return loss of the antenna is around 21.34 dB. Six major beams with each one having a gain around 6.4 dB and 7.1 dB are generated by the antenna in the current study. The antenna is having a bandwidth of 20 MHz and is linearly polarised.
{"title":"A Hybrid Substrate Integrated Waveguide Cavity based Leaky Wave Antenna Capable of Generating Six Major Beams","authors":"R. P., R. P.","doi":"10.1109/wispnet54241.2022.9767108","DOIUrl":"https://doi.org/10.1109/wispnet54241.2022.9767108","url":null,"abstract":"The antenna in the current study is an attempt to break the available radiation pattern into multiple beams in order to reduce energy waste. To achieve this, a hybrid substrate integrated waveguide (SIW) is generated by combining a cylindrical cavity with a rectangular cavity. A cross-shaped slot is engraved on the top and bottom face of the cylindrical cavity to allow the antenna to generate six major lobes. At the operating frequency of 5 GHz, the return loss of the antenna is around 21.34 dB. Six major beams with each one having a gain around 6.4 dB and 7.1 dB are generated by the antenna in the current study. The antenna is having a bandwidth of 20 MHz and is linearly polarised.","PeriodicalId":432794,"journal":{"name":"2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128910088","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 : 2022-03-24DOI: 10.1109/wispnet54241.2022.9767115
T. Kumar, Adithya Jayan, Shreenidhi Bhat, M. Anvith, A. V. Narasimhadhan
The automatic Speech Recognition system (ASR) is the most widely used application in the speech domain. ASR systems generate text data from spoken utterances without manual intervention. In this work, we build an ASR system for the Kannada language. For building the proposed system, we extract Mel Frequency Cepstral Coefficients (MFCC) features from the audio data, and the Kannada language model is developed using corresponding labels. The dictionary generation and phonetic labelings are automated. Recognition performance is compared for both monophonic and triphone models. The word error rate of 15.73 % and the sentence error rate of 55.5 % are achieved for the triphone model. Comparatively, the triphone model gives a better performance than the monophonic model.
{"title":"Monophone and Triphone Acoustic Phonetic Model for Kannada Speech Recognition System","authors":"T. Kumar, Adithya Jayan, Shreenidhi Bhat, M. Anvith, A. V. Narasimhadhan","doi":"10.1109/wispnet54241.2022.9767115","DOIUrl":"https://doi.org/10.1109/wispnet54241.2022.9767115","url":null,"abstract":"The automatic Speech Recognition system (ASR) is the most widely used application in the speech domain. ASR systems generate text data from spoken utterances without manual intervention. In this work, we build an ASR system for the Kannada language. For building the proposed system, we extract Mel Frequency Cepstral Coefficients (MFCC) features from the audio data, and the Kannada language model is developed using corresponding labels. The dictionary generation and phonetic labelings are automated. Recognition performance is compared for both monophonic and triphone models. The word error rate of 15.73 % and the sentence error rate of 55.5 % are achieved for the triphone model. Comparatively, the triphone model gives a better performance than the monophonic model.","PeriodicalId":432794,"journal":{"name":"2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET)","volume":"4 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120885678","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 : 2022-03-24DOI: 10.1109/wispnet54241.2022.9767142
M. Prabhu, Aravind Hanumanthaiah
Telemedicine has the potential to bridge the huge urban-rural health divide that exists in many developing economies in the fastest and the most affordable way. Cloud Computing holds promise for providing an efficient, cost-effective, and pervasive telemedicine paradigm. With cloud computing, biomedical sensor data can be stored and analyzed remotely by remotely distributed servers. However, a huge volume of data is generated by smart medical devices [1]. Thus, there is a need to leverage the Edge Computing paradigm to process data closer to the source of data generation. This paper presents a healthcare framework that incorporates a promising Edge-IoT ecosystem - the EdgeX Foundry for the telehealth use case of Blood Pressure monitoring. The end-to-end system is broadly divided into three parts: the User subsystem, the Edge subsystem, and the Cloud subsystem. This paper presents the use of EdgeX Foundry for a telehealth application.
{"title":"Edge Computing-Enabled Healthcare Framework to Provide Telehealth Services","authors":"M. Prabhu, Aravind Hanumanthaiah","doi":"10.1109/wispnet54241.2022.9767142","DOIUrl":"https://doi.org/10.1109/wispnet54241.2022.9767142","url":null,"abstract":"Telemedicine has the potential to bridge the huge urban-rural health divide that exists in many developing economies in the fastest and the most affordable way. Cloud Computing holds promise for providing an efficient, cost-effective, and pervasive telemedicine paradigm. With cloud computing, biomedical sensor data can be stored and analyzed remotely by remotely distributed servers. However, a huge volume of data is generated by smart medical devices [1]. Thus, there is a need to leverage the Edge Computing paradigm to process data closer to the source of data generation. This paper presents a healthcare framework that incorporates a promising Edge-IoT ecosystem - the EdgeX Foundry for the telehealth use case of Blood Pressure monitoring. The end-to-end system is broadly divided into three parts: the User subsystem, the Edge subsystem, and the Cloud subsystem. This paper presents the use of EdgeX Foundry for a telehealth application.","PeriodicalId":432794,"journal":{"name":"2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122738441","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 : 2022-03-24DOI: 10.1109/wispnet54241.2022.9767172
Aditya Narayan S., Hareesh Kumaar, Sathya Narayanan D., S. S., V. S.
Big tech companies like Amazon, Netflix and Google have tons of data and are still successful in providing specific products and services correctly as per user requirements. This is made possible by the recommendation algorithms that feed on the data we provide, in turn, enabling them to produce accurate results. Movie recommendation systems aspire to help cinema geeks by proposing movies of their penchant, devoid of them needing to do the standard long and arduous method of selecting from huge sets of movies that go up to millions and is onerous and frustrating. In this paper, we aspire to diminish human endeavor by recommending them movies based on their interests. To resolve such troubles, we have built a model using a content-based approach. The idea behind this model is to recommend a movie based on descriptions of movies. Using the movie “GoldenEye” as an example, we obtained the result as “Skyfall” with a similarity score of 66.73% using CountVectorizer, 13.14% using Jaccard Recommender, 14.34% using TF-IDF Keywords, 9.87% using TF-IDF Plot Overview and 71.9% using Google Form responses.
像亚马逊、Netflix和谷歌这样的大型科技公司拥有大量数据，并且仍然成功地根据用户需求提供特定的产品和服务。这是通过推荐算法实现的，这些算法以我们提供的数据为基础，反过来使它们能够产生准确的结果。电影推荐系统希望通过推荐他们喜欢的电影来帮助电影爱好者，而不需要他们从大量的电影中进行标准的、漫长而艰苦的选择，这些电影多达数百万部，这是一项繁重而令人沮丧的工作。在本文中，我们希望通过根据他们的兴趣推荐电影来减少人类的努力。为了解决这些问题，我们使用基于内容的方法构建了一个模型。这个模型背后的想法是根据电影的描述来推荐电影。以电影“GoldenEye”为例，我们得到的结果是“Skyfall”，使用CountVectorizer的相似度为66.73%，使用Jaccard Recommender的相似度为13.14%，使用TF-IDF Keywords的相似度为14.34%，使用TF-IDF Plot Overview的相似度为9.87%，使用Google Form responses的相似度为71.9%。
{"title":"Content-based Movie Recommender System Using Keywords and Plot Overview","authors":"Aditya Narayan S., Hareesh Kumaar, Sathya Narayanan D., S. S., V. S.","doi":"10.1109/wispnet54241.2022.9767172","DOIUrl":"https://doi.org/10.1109/wispnet54241.2022.9767172","url":null,"abstract":"Big tech companies like Amazon, Netflix and Google have tons of data and are still successful in providing specific products and services correctly as per user requirements. This is made possible by the recommendation algorithms that feed on the data we provide, in turn, enabling them to produce accurate results. Movie recommendation systems aspire to help cinema geeks by proposing movies of their penchant, devoid of them needing to do the standard long and arduous method of selecting from huge sets of movies that go up to millions and is onerous and frustrating. In this paper, we aspire to diminish human endeavor by recommending them movies based on their interests. To resolve such troubles, we have built a model using a content-based approach. The idea behind this model is to recommend a movie based on descriptions of movies. Using the movie “GoldenEye” as an example, we obtained the result as “Skyfall” with a similarity score of 66.73% using CountVectorizer, 13.14% using Jaccard Recommender, 14.34% using TF-IDF Keywords, 9.87% using TF-IDF Plot Overview and 71.9% using Google Form responses.","PeriodicalId":432794,"journal":{"name":"2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130925574","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 : 2022-03-24DOI: 10.1109/wispnet54241.2022.9767099
P. S., J. K.
Image segmentation is a well-known topic in image processing, and it remains as a hotspot and focal point for image processing techniques. In this paper, we propose a hybrid segmentation method, combining an Adaptive K-Means clustering algorithm and a novel automatic GrabCut segmentation algorithm to improve the performance of the object segmentation from the scene image. The proposed method is divided into six steps: Firstly, the RGB image normalization step is introduced to eliminate light variation and remove bright and shaded regions. Secondly, RGB colour space is converted to L⃰a⃰b⃰ colour space to maintain accurate colour balance. Thirdly, we propose a novel automatic GrabCut segmentation algorithm to eliminate user interaction and make the segmentation process faster. Fourthly, the Adaptive K-Means clustering algorithm and the proposed automatic GrabCut segmentation algorithm are combined to segment foreground objects from the background. Fifthly, the shape refinement step is used to eliminate occlusion, noise, and smear issues from the segmented image. Finally, morphological operations are carried out to enhance the segmentation performance. The performance of the hybrid segmentation method is assessed using the MSRA benchmark dataset.
{"title":"Object Segmentation Based on the Integration of Adaptive K-means and GrabCut Algorithm","authors":"P. S., J. K.","doi":"10.1109/wispnet54241.2022.9767099","DOIUrl":"https://doi.org/10.1109/wispnet54241.2022.9767099","url":null,"abstract":"Image segmentation is a well-known topic in image processing, and it remains as a hotspot and focal point for image processing techniques. In this paper, we propose a hybrid segmentation method, combining an Adaptive K-Means clustering algorithm and a novel automatic GrabCut segmentation algorithm to improve the performance of the object segmentation from the scene image. The proposed method is divided into six steps: Firstly, the RGB image normalization step is introduced to eliminate light variation and remove bright and shaded regions. Secondly, RGB colour space is converted to L⃰a⃰b⃰ colour space to maintain accurate colour balance. Thirdly, we propose a novel automatic GrabCut segmentation algorithm to eliminate user interaction and make the segmentation process faster. Fourthly, the Adaptive K-Means clustering algorithm and the proposed automatic GrabCut segmentation algorithm are combined to segment foreground objects from the background. Fifthly, the shape refinement step is used to eliminate occlusion, noise, and smear issues from the segmented image. Finally, morphological operations are carried out to enhance the segmentation performance. The performance of the hybrid segmentation method is assessed using the MSRA benchmark dataset.","PeriodicalId":432794,"journal":{"name":"2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116527094","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 : 2022-03-24DOI: 10.1109/wispnet54241.2022.9767153
Ajjey S. B., S. S., Sowmeeya S. R., Ajin R. Nair, M. Raju
The proper monitoring of ECG will help to identify patients with cardiac problems. In the last two decades, many lives have been saved due to the automated prediction of heart diseases with the help of ECG signals. This article proposes a hybrid CNN-Naive Bayes classifier for classifying Normal Sinus Rhythm, Abnormal Arrhythmia, and Congestive Heart Failure from the MIT-BIH arrhythmia database. The one-dimensional ECG signals are converted to two-dimensional scalogram images using continuous wavelet transform. The scalogram images eliminate noise filtering and conventional feature extraction steps that may lead to loss of beats. The proposed architecture uses GoogLeNet to extract independent and discriminating features, which aids the Naive Bayes classifier to attain a high accuracy of 98.76%.
{"title":"Scalogram Based Heart Disease Classification using Hybrid CNN-Naive Bayes Classifier","authors":"Ajjey S. B., S. S., Sowmeeya S. R., Ajin R. Nair, M. Raju","doi":"10.1109/wispnet54241.2022.9767153","DOIUrl":"https://doi.org/10.1109/wispnet54241.2022.9767153","url":null,"abstract":"The proper monitoring of ECG will help to identify patients with cardiac problems. In the last two decades, many lives have been saved due to the automated prediction of heart diseases with the help of ECG signals. This article proposes a hybrid CNN-Naive Bayes classifier for classifying Normal Sinus Rhythm, Abnormal Arrhythmia, and Congestive Heart Failure from the MIT-BIH arrhythmia database. The one-dimensional ECG signals are converted to two-dimensional scalogram images using continuous wavelet transform. The scalogram images eliminate noise filtering and conventional feature extraction steps that may lead to loss of beats. The proposed architecture uses GoogLeNet to extract independent and discriminating features, which aids the Naive Bayes classifier to attain a high accuracy of 98.76%.","PeriodicalId":432794,"journal":{"name":"2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128646604","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 : 2022-03-24DOI: 10.1109/wispnet54241.2022.9767165
D. C., Murugesan G., J. M., G. N, S. S., S. K., V. A
Medical and psychological applications are expected to benefit substantially from the use of Wireless Body Area Networks (WBAN). As the enormous amount of healthcare data evolves, it becomes more and more difficult to locate any meaningful information. Because in view of integrating IoT into almost all fields, including healthcare, animal monitoring and tracking in all sectors, In order for the WBAN-enabled IoT technology to optimise the functioning of healthcare applications, there must be sufficient support from all the protocol stack levels. Therefore, the network layer protocol has lately attracted an excellent deal of attention within the field of WBANs due to its capacity to manage and coordinate the info packets with minimum energy and avoid congestion. This study is to determine the optimum approach, fitness functions for simulated WBAN routing algorithms are evaluated using routing metrics such as PDR and energy under various optimization approaches. Finally, certain open research issues and early research objectives in the domain are identified and compared across various optimization techniques for WBAN routing protocols.
{"title":"Analysis of Optimization Based Routing Protocol for WBAN","authors":"D. C., Murugesan G., J. M., G. N, S. S., S. K., V. A","doi":"10.1109/wispnet54241.2022.9767165","DOIUrl":"https://doi.org/10.1109/wispnet54241.2022.9767165","url":null,"abstract":"Medical and psychological applications are expected to benefit substantially from the use of Wireless Body Area Networks (WBAN). As the enormous amount of healthcare data evolves, it becomes more and more difficult to locate any meaningful information. Because in view of integrating IoT into almost all fields, including healthcare, animal monitoring and tracking in all sectors, In order for the WBAN-enabled IoT technology to optimise the functioning of healthcare applications, there must be sufficient support from all the protocol stack levels. Therefore, the network layer protocol has lately attracted an excellent deal of attention within the field of WBANs due to its capacity to manage and coordinate the info packets with minimum energy and avoid congestion. This study is to determine the optimum approach, fitness functions for simulated WBAN routing algorithms are evaluated using routing metrics such as PDR and energy under various optimization approaches. Finally, certain open research issues and early research objectives in the domain are identified and compared across various optimization techniques for WBAN routing protocols.","PeriodicalId":432794,"journal":{"name":"2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125140223","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 : 2022-03-24DOI: 10.1109/wispnet54241.2022.9767163
C. V., C. P, H. M., A. S
Rainfall Prediction is an integral part of research these days with its applications ranging from Disaster Management to Agricultural Technologies. Coastal cities like Chennai are extremely prone to irregular and incessant bursts of rainfall. Prior knowledge of such events is necessary to avoid wastage of resources and reduce damage to livelihood. In this paper, we have investigated several state-of-art algorithms such as SARIMA, LSTM, BiLSTM, RNN, RNN-LSTM that are used for rainfall forecasting. The investigations show that the state-of-art algorithms have reduced error rates in predictions, however fail to handle extreme rainfall events. To overcome this, an Ensemble Model of CNN, RNN-LSTM, and Bidirectional LSTM are proposed to forecast the daily rainfall statistics of Chennai. The proposed model is compared with the baseline models to analyze its performance. The features considered for model implementation are Rainfall, Relative Humidity, and Temperature that is collected on a daily scale. The evaluation result shows that the proposed model provides improved prediction results for Rainfall when compared to the baseline approaches.
{"title":"A Deep Learning Ensemble Model for Short-Term Rainfall Prediction","authors":"C. V., C. P, H. M., A. S","doi":"10.1109/wispnet54241.2022.9767163","DOIUrl":"https://doi.org/10.1109/wispnet54241.2022.9767163","url":null,"abstract":"Rainfall Prediction is an integral part of research these days with its applications ranging from Disaster Management to Agricultural Technologies. Coastal cities like Chennai are extremely prone to irregular and incessant bursts of rainfall. Prior knowledge of such events is necessary to avoid wastage of resources and reduce damage to livelihood. In this paper, we have investigated several state-of-art algorithms such as SARIMA, LSTM, BiLSTM, RNN, RNN-LSTM that are used for rainfall forecasting. The investigations show that the state-of-art algorithms have reduced error rates in predictions, however fail to handle extreme rainfall events. To overcome this, an Ensemble Model of CNN, RNN-LSTM, and Bidirectional LSTM are proposed to forecast the daily rainfall statistics of Chennai. The proposed model is compared with the baseline models to analyze its performance. The features considered for model implementation are Rainfall, Relative Humidity, and Temperature that is collected on a daily scale. The evaluation result shows that the proposed model provides improved prediction results for Rainfall when compared to the baseline approaches.","PeriodicalId":432794,"journal":{"name":"2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126206032","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 : 2022-03-24DOI: 10.1109/wispnet54241.2022.9767136
Jegadish Kumar K. J., K. P., K. A., Gopalakrishnan N., Dinesh J., J. M.
Designing an antenna is always challenging because there is a tradeoff between the gain and the size. More specifically to design an antenna for wireless data communication in ISM band with less interference, low power consumption. To address these issues, this paper proposes a twin-slot radiator for beam-forming with high gain. The antenna operating at 2.4GHz consists of a two-layer stack with a twin-slot radiator and a superstrate separated by air medium. The metamaterial structure is excited with different phase delays through the twin-slot fed radiator to radiate the antenna beam in a specific direction. The performance analysis of the designed antenna is studied by simulation and measurement setups.
{"title":"Design of Twin-slot Radiator Beam-Forming Antenna Using Metasurface","authors":"Jegadish Kumar K. J., K. P., K. A., Gopalakrishnan N., Dinesh J., J. M.","doi":"10.1109/wispnet54241.2022.9767136","DOIUrl":"https://doi.org/10.1109/wispnet54241.2022.9767136","url":null,"abstract":"Designing an antenna is always challenging because there is a tradeoff between the gain and the size. More specifically to design an antenna for wireless data communication in ISM band with less interference, low power consumption. To address these issues, this paper proposes a twin-slot radiator for beam-forming with high gain. The antenna operating at 2.4GHz consists of a two-layer stack with a twin-slot radiator and a superstrate separated by air medium. The metamaterial structure is excited with different phase delays through the twin-slot fed radiator to radiate the antenna beam in a specific direction. The performance analysis of the designed antenna is studied by simulation and measurement setups.","PeriodicalId":432794,"journal":{"name":"2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121810130","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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