Pub Date : 2021-06-03DOI: 10.1109/ICOEI51242.2021.9452946
Kamlesh Kalbande, Swapna Choudhary, Anushka Singru, I. Mukherjee, Prachi Bakshi
Indian Agriculture conflates IoT for precision farming with the advent of ultra-low-power and advanced technologies. Assisting farmers in dealing with the problems of unorganized process automation, non-efficient products, non-available resources leading to machine damage, so on is a basic identification to vanquish. The concern discerning is monitoring and control systems, quality improvement, automation of devices, etc. Instead of controlling the level of water, the control of pump handling is given to the farmer so that it prevents the regulation of irrigation virtually being on the agricultural field at that time so to calculate water availability as a feedback oriented system. This paper proposes an IoT-based Smart Agriculture System assisting farmers to deal with the problems by getting Live Data (Temperature, Soil Moisture, Water level) for environment monitoring which enables to increase overall yield and quality of products. Updating each respective requires personal smart devices and controls to handle by enabling notifications of Application, this can be performed multi-way by merging both manual and automation to monitor. In such an occurrence, the farmer perhaps might also desire to forestall the machine without physical contact or routinely. The ultimate farming results need coordination for the sustainability of each vital living or nonliving substance, for which notifying an impetuous person will lead to an infusion. This system has been designed in an IoT environment with sensors like Soil Moisture Sensor, PIR Sensor, DHT11 Temperature and Humidity Sensor, Ultrasonic Sensor with a novel approach. The design methodology, hardware, and software implementations result with IoT cloud interface, sensor, and device controlling Application are discussed in this paper.
{"title":"Multi-Way Controlled Feedback Oriented Smart System for Agricultural Application using Internet of Things","authors":"Kamlesh Kalbande, Swapna Choudhary, Anushka Singru, I. Mukherjee, Prachi Bakshi","doi":"10.1109/ICOEI51242.2021.9452946","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9452946","url":null,"abstract":"Indian Agriculture conflates IoT for precision farming with the advent of ultra-low-power and advanced technologies. Assisting farmers in dealing with the problems of unorganized process automation, non-efficient products, non-available resources leading to machine damage, so on is a basic identification to vanquish. The concern discerning is monitoring and control systems, quality improvement, automation of devices, etc. Instead of controlling the level of water, the control of pump handling is given to the farmer so that it prevents the regulation of irrigation virtually being on the agricultural field at that time so to calculate water availability as a feedback oriented system. This paper proposes an IoT-based Smart Agriculture System assisting farmers to deal with the problems by getting Live Data (Temperature, Soil Moisture, Water level) for environment monitoring which enables to increase overall yield and quality of products. Updating each respective requires personal smart devices and controls to handle by enabling notifications of Application, this can be performed multi-way by merging both manual and automation to monitor. In such an occurrence, the farmer perhaps might also desire to forestall the machine without physical contact or routinely. The ultimate farming results need coordination for the sustainability of each vital living or nonliving substance, for which notifying an impetuous person will lead to an infusion. This system has been designed in an IoT environment with sensors like Soil Moisture Sensor, PIR Sensor, DHT11 Temperature and Humidity Sensor, Ultrasonic Sensor with a novel approach. The design methodology, hardware, and software implementations result with IoT cloud interface, sensor, and device controlling Application are discussed in this paper.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123914474","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 : 2021-06-03DOI: 10.1109/ICOEI51242.2021.9452864
Jithina Jose, J. Vimali, P. Ajitha, S. Gowri, A. Sivasangari, Bevish Y. Jinila
These days, drowsy driving plays a significant role in a lot of road incidents. Car accidents can be avoided by implementing a system with alarm to alert drowsy drivers in order to focus on the road and help them to stay focused. This paper has developed to detect driver drowsiness and trigger them with an alarm to alert drivers in order to prevent accidents, and reduce loss of lives and sufferings. Several techniques have been studied and analyzed to conclude the best technique with highest accuracy to detect the driver drowsiness. The proposed method utilizes Python, dlib, and OpenCV to build a real-time framework that uses a computerized camera to monitor and process the driver's eye and yawn. A camera will be utilized so that it concentrates towards monitoring the driver's eye and yawn. A trigger is issued to alert the driver. The proposed system acknowledges whether thedriver is sleepy and it gives a caution alert, when his eyes and yawn are discovered close together for a particular measure of casing.
{"title":"Drowsiness Detection System for Drivers Using Image Processing Technique","authors":"Jithina Jose, J. Vimali, P. Ajitha, S. Gowri, A. Sivasangari, Bevish Y. Jinila","doi":"10.1109/ICOEI51242.2021.9452864","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9452864","url":null,"abstract":"These days, drowsy driving plays a significant role in a lot of road incidents. Car accidents can be avoided by implementing a system with alarm to alert drowsy drivers in order to focus on the road and help them to stay focused. This paper has developed to detect driver drowsiness and trigger them with an alarm to alert drivers in order to prevent accidents, and reduce loss of lives and sufferings. Several techniques have been studied and analyzed to conclude the best technique with highest accuracy to detect the driver drowsiness. The proposed method utilizes Python, dlib, and OpenCV to build a real-time framework that uses a computerized camera to monitor and process the driver's eye and yawn. A camera will be utilized so that it concentrates towards monitoring the driver's eye and yawn. A trigger is issued to alert the driver. The proposed system acknowledges whether thedriver is sleepy and it gives a caution alert, when his eyes and yawn are discovered close together for a particular measure of casing.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124002033","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 : 2021-06-03DOI: 10.1109/ICOEI51242.2021.9453068
Anjali Anil Kumar, Navya Lal, R. N. Kumar
Image processing is a fast growing area of active research. It comprises methods to perform several useful operations on images, to modify/enhance the image or to tease out useful information from it. A very basic application of image processing is image filtering. Filtering is a technique of image modification or enhancement. We filter an image to enhance some features or to get rid of other features - the techniques include smoothing, sharpening, edge enhancement. Here we apply different smoothing and edge enhancement filtering methods to an image and evaluate the quality of the image in both cases using an image quality assessment technique called BRISQUE and by calculating the PSNR ratio of images.
{"title":"A Comparative Study of Various Filtering Techniques","authors":"Anjali Anil Kumar, Navya Lal, R. N. Kumar","doi":"10.1109/ICOEI51242.2021.9453068","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9453068","url":null,"abstract":"Image processing is a fast growing area of active research. It comprises methods to perform several useful operations on images, to modify/enhance the image or to tease out useful information from it. A very basic application of image processing is image filtering. Filtering is a technique of image modification or enhancement. We filter an image to enhance some features or to get rid of other features - the techniques include smoothing, sharpening, edge enhancement. Here we apply different smoothing and edge enhancement filtering methods to an image and evaluate the quality of the image in both cases using an image quality assessment technique called BRISQUE and by calculating the PSNR ratio of images.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"1933 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128779164","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 : 2021-06-03DOI: 10.1109/ICOEI51242.2021.9452739
Guojing Zhang
Intelligent system construction and data analysis of social service platform in vocational colleges is studied. There are many theories and methods related to data preprocessing, and they have been applied in many fields. In the process of data collection, it will be affected by the environment, usage and other aspects, resulting in the collected data can not be directly processed as an ideal sample. Hence, the PCA is applied for the data dimensional reduction, and the data distribution pattern is then considered for the comprehensive modelling. The application scenario is selected as the social service platform. The data is studied based on the integration of the theoretical model. The accuracy and efficiency are both improved.
{"title":"Intelligent System Construction and Data Analysis of Social Service Platform in Vocational Colleges","authors":"Guojing Zhang","doi":"10.1109/ICOEI51242.2021.9452739","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9452739","url":null,"abstract":"Intelligent system construction and data analysis of social service platform in vocational colleges is studied. There are many theories and methods related to data preprocessing, and they have been applied in many fields. In the process of data collection, it will be affected by the environment, usage and other aspects, resulting in the collected data can not be directly processed as an ideal sample. Hence, the PCA is applied for the data dimensional reduction, and the data distribution pattern is then considered for the comprehensive modelling. The application scenario is selected as the social service platform. The data is studied based on the integration of the theoretical model. The accuracy and efficiency are both improved.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130629715","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 : 2021-06-03DOI: 10.1109/ICOEI51242.2021.9452967
Jinpeng Guo, Ting Xu
Effectiveness evaluation of air pollution intelligent control based on AI guided haze image identification algorithm is conducted in this paper. Firstly, we choose median filter to denoise the image, choose the global fog image enhancement method to enhance the image, and segment the image through the Gaussian mixture model algorithm based on spatio-temporal information. Secondly, the novel AI system is designed for the implementations of the environment sensing framework that can collect the data, pre-process the data and finally extract the overall information for analysis. Lastly, the intelligent control system is desinged and implemented. Reflecting from the simulation results, the proposed monitoring system can comprehensively analysis the data well.
{"title":"Effectiveness Evaluation of Air Pollution Intelligent Control Based on AI Guided Haze Image Identification Algorithm","authors":"Jinpeng Guo, Ting Xu","doi":"10.1109/ICOEI51242.2021.9452967","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9452967","url":null,"abstract":"Effectiveness evaluation of air pollution intelligent control based on AI guided haze image identification algorithm is conducted in this paper. Firstly, we choose median filter to denoise the image, choose the global fog image enhancement method to enhance the image, and segment the image through the Gaussian mixture model algorithm based on spatio-temporal information. Secondly, the novel AI system is designed for the implementations of the environment sensing framework that can collect the data, pre-process the data and finally extract the overall information for analysis. Lastly, the intelligent control system is desinged and implemented. Reflecting from the simulation results, the proposed monitoring system can comprehensively analysis the data well.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130060148","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 : 2021-06-03DOI: 10.1109/ICOEI51242.2021.9452924
R. Krishnan, K. Narayanan, S. Murali, A. Sangeetha, C. R. Sankar Ram, Y. H. Robinson
Nearly 286 million people in the world are visually impaired as of 2021. India stands first in the world for containing large number of visually impaired people. 22% of the world's visually impaired population resides in India. There are also numerous visually impaired care homes in India to take care of those visually impaired people. These people are facing numerous difficulties in their day-to-day life. Visually impaired people find it hard to locate the hindrance in their route when they are moving from one location to another. This may sometimes lead to life intimidating activities if proper alert information is not passed to them at the correct time. In order to alert about such activities, we propose this blind people monitoring system. This system alerts the visually impaired people by identifying the various hinderances in their pathway in advance and alert them to travel with utmost precaution. Our system also sends the exact location details of the visually impaired people to thevisually impaired care homes whenever they are in need of immediate assistance. All the activity of the visually impaired people are monitored and maintained in a database.
{"title":"IoT based Blind People Monitoring System for Visually Impaired Care Homes","authors":"R. Krishnan, K. Narayanan, S. Murali, A. Sangeetha, C. R. Sankar Ram, Y. H. Robinson","doi":"10.1109/ICOEI51242.2021.9452924","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9452924","url":null,"abstract":"Nearly 286 million people in the world are visually impaired as of 2021. India stands first in the world for containing large number of visually impaired people. 22% of the world's visually impaired population resides in India. There are also numerous visually impaired care homes in India to take care of those visually impaired people. These people are facing numerous difficulties in their day-to-day life. Visually impaired people find it hard to locate the hindrance in their route when they are moving from one location to another. This may sometimes lead to life intimidating activities if proper alert information is not passed to them at the correct time. In order to alert about such activities, we propose this blind people monitoring system. This system alerts the visually impaired people by identifying the various hinderances in their pathway in advance and alert them to travel with utmost precaution. Our system also sends the exact location details of the visually impaired people to thevisually impaired care homes whenever they are in need of immediate assistance. All the activity of the visually impaired people are monitored and maintained in a database.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129439447","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 : 2021-06-03DOI: 10.1109/ICOEI51242.2021.9452945
Qiankun Li
Strengthening education has always been an important national policy of our country. Especially in the era of knowledge economy, a country's education level has a direct impact on the comprehensive national strength and the sustainable development of the country. Because of the hierarchical education system implemented in China, only a small number of people can receive high-quality higher education. The development of the Internet has provided better conditions for the expansion of teaching scope, and the country has put forward the plan of network distance education since the late 1990s of last century. The plan calls for universities to use their teaching resources to set up teaching websites on the Internet and provide educational services to the public.
{"title":"Application and Development of Computer Technology in Network Guiding","authors":"Qiankun Li","doi":"10.1109/ICOEI51242.2021.9452945","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9452945","url":null,"abstract":"Strengthening education has always been an important national policy of our country. Especially in the era of knowledge economy, a country's education level has a direct impact on the comprehensive national strength and the sustainable development of the country. Because of the hierarchical education system implemented in China, only a small number of people can receive high-quality higher education. The development of the Internet has provided better conditions for the expansion of teaching scope, and the country has put forward the plan of network distance education since the late 1990s of last century. The plan calls for universities to use their teaching resources to set up teaching websites on the Internet and provide educational services to the public.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129862055","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 : 2021-06-03DOI: 10.1109/ICOEI51242.2021.9452811
S. Venkatachalam
One of the most common issues that new graduates experience is the insufficient understanding of basic concepts. Major skill gaps in this area include a lack of deep comprehension on technical information, lack of customer management abilities, and insufficient knowledge of numerous disciplines. The study has attributed a lack of English communication skills, which they found in 73.63% of applicants, and poor analytical and quantitative skills, which they found in 57.96% of applicants, as a major cause of unemployment. Aptitude tests are conducted to analyze the problem-solving skills of the candidate; this evaluation helps to solve a problem at a given point in time. The proposed study has collected data on students, who had different information about their previous and current academic records, and then different classification algorithms along with the Data Mining Tool (VEKA) are used to analyze academic performance in training and accommodation. This study presents a proposed model based on a classification approach to find a better evaluation method in order to predict the student accommodation. There are many basic classification algorithms and statistical methods that can be used as good resources for classifying student datasets in education. In this article, a fuzzy inference system was used to predict the student performance and improve academic performance. This model can determine the relationship between student achievement and campus placement.
{"title":"Data Mining Classification and analytical model of prediction for Job Placements using Fuzzy Logic","authors":"S. Venkatachalam","doi":"10.1109/ICOEI51242.2021.9452811","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9452811","url":null,"abstract":"One of the most common issues that new graduates experience is the insufficient understanding of basic concepts. Major skill gaps in this area include a lack of deep comprehension on technical information, lack of customer management abilities, and insufficient knowledge of numerous disciplines. The study has attributed a lack of English communication skills, which they found in 73.63% of applicants, and poor analytical and quantitative skills, which they found in 57.96% of applicants, as a major cause of unemployment. Aptitude tests are conducted to analyze the problem-solving skills of the candidate; this evaluation helps to solve a problem at a given point in time. The proposed study has collected data on students, who had different information about their previous and current academic records, and then different classification algorithms along with the Data Mining Tool (VEKA) are used to analyze academic performance in training and accommodation. This study presents a proposed model based on a classification approach to find a better evaluation method in order to predict the student accommodation. There are many basic classification algorithms and statistical methods that can be used as good resources for classifying student datasets in education. In this article, a fuzzy inference system was used to predict the student performance and improve academic performance. This model can determine the relationship between student achievement and campus placement.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130297993","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 : 2021-06-03DOI: 10.1109/ICOEI51242.2021.9453079
M.V. Sowmya Lakshmi, P. L. Saisreeja, L. Chandana, P. Mounika, P. U
Brain Tumor identification has been regarded as a critical topic. Meanwhile, it is complicated to spot the tumor in MRI images manually from a large amount of MRI images generated is difficult and time-consuming due to unpredictable shapes and sizes of the tumor. Image Segmentation techniques make a massive impact here and help in obtaining more significant results by dividing the image into segments for prior identification of tumors. U-Net with LeakyReLu can be used for faster and precise segmentation of medical images. Thresholding is applied to identify the ROI of the tumor for better identification of the abnormality of the tumor. Identifying the tumor region from the segmented MRI image is lesser time-consuming. Therefore, our model developed using neural networks can help the doctors in precisely identifying the tumor region from the segmented images and thereby assisting them to help the patients.
{"title":"A LeakyReLU based Effective Brain MRI Segmentation using U-NET","authors":"M.V. Sowmya Lakshmi, P. L. Saisreeja, L. Chandana, P. Mounika, P. U","doi":"10.1109/ICOEI51242.2021.9453079","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9453079","url":null,"abstract":"Brain Tumor identification has been regarded as a critical topic. Meanwhile, it is complicated to spot the tumor in MRI images manually from a large amount of MRI images generated is difficult and time-consuming due to unpredictable shapes and sizes of the tumor. Image Segmentation techniques make a massive impact here and help in obtaining more significant results by dividing the image into segments for prior identification of tumors. U-Net with LeakyReLu can be used for faster and precise segmentation of medical images. Thresholding is applied to identify the ROI of the tumor for better identification of the abnormality of the tumor. Identifying the tumor region from the segmented MRI image is lesser time-consuming. Therefore, our model developed using neural networks can help the doctors in precisely identifying the tumor region from the segmented images and thereby assisting them to help the patients.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124409931","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 : 2021-06-03DOI: 10.1109/ICOEI51242.2021.9453041
D. Manikanta, Katakam Ramakrishna, Maturi Giridhar, Narlapati Avinash, Talupula Srujan, R. R.
VLSI experiences a key position in many of the signal processing applications. Multiply and Accumulation process is one among the mostly used operation. Power, area and speed are the metrics used to determine the efficiency of a MAC unit. For certain cases each of these metrics plays a key role. In some cases, speed is only concentrated, so the other parameters are not given much priority in that case. This work focuses on two metrics. The power and area is concentrated for the better efficiency in this work. Through the deep analysis of adders, Ripple Carry Adder has shown less area and power consumption than other adders. The processes that are involved in MAC are multiplication, addition and accumulation. The addition of Vedic techniques in a MAC is always an added advantage. So, this work includes development of a 32-bit multiply and accumulate unit using Vedic sutra (Urdhva Tiryakbhyam sutra), accumulation unit involving ripple carry adder (RCA) and its implementation in a 4-tap FIR filter. The results show an efficiency of 5% in area improvement and 9% in power.
{"title":"Hardware Realization of Low power and Area Efficient Vedic MAC in DSP Filters","authors":"D. Manikanta, Katakam Ramakrishna, Maturi Giridhar, Narlapati Avinash, Talupula Srujan, R. R.","doi":"10.1109/ICOEI51242.2021.9453041","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9453041","url":null,"abstract":"VLSI experiences a key position in many of the signal processing applications. Multiply and Accumulation process is one among the mostly used operation. Power, area and speed are the metrics used to determine the efficiency of a MAC unit. For certain cases each of these metrics plays a key role. In some cases, speed is only concentrated, so the other parameters are not given much priority in that case. This work focuses on two metrics. The power and area is concentrated for the better efficiency in this work. Through the deep analysis of adders, Ripple Carry Adder has shown less area and power consumption than other adders. The processes that are involved in MAC are multiplication, addition and accumulation. The addition of Vedic techniques in a MAC is always an added advantage. So, this work includes development of a 32-bit multiply and accumulate unit using Vedic sutra (Urdhva Tiryakbhyam sutra), accumulation unit involving ripple carry adder (RCA) and its implementation in a 4-tap FIR filter. The results show an efficiency of 5% in area improvement and 9% in power.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128054618","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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