Pub Date : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653701
M. Gayathri Devi, S. Manjula
This paper is about study of comparative analysis of Spatial and Transform domain fusion techniques under Compressive Sensing or Compressive Sampling principle. The compressive measurements of two source images are obtained using star shaped sampling pattern and fuse the measurements. The output image is reconstructed from 25% of samples using Minimum Total Variation method with equality constraints and with reduced computational time. Finally, for different fusion techniques under Compressive Sensing are performed and compared. Multi focus and Multi modal images are used for simulation and no prior knowledge of source images is required for reconstruction. Based on fusion evaluation metric with reference and without reference image conclude that in spatial domain, simple average & principal component analysis and in transform domain, DCTav and Laplacian Pyramid are performed well.
{"title":"A Comparative Analysis on Image Fusion Algorithms based on Compressive Sensing","authors":"M. Gayathri Devi, S. Manjula","doi":"10.1109/I-SMAC.2018.8653701","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653701","url":null,"abstract":"This paper is about study of comparative analysis of Spatial and Transform domain fusion techniques under Compressive Sensing or Compressive Sampling principle. The compressive measurements of two source images are obtained using star shaped sampling pattern and fuse the measurements. The output image is reconstructed from 25% of samples using Minimum Total Variation method with equality constraints and with reduced computational time. Finally, for different fusion techniques under Compressive Sensing are performed and compared. Multi focus and Multi modal images are used for simulation and no prior knowledge of source images is required for reconstruction. Based on fusion evaluation metric with reference and without reference image conclude that in spatial domain, simple average & principal component analysis and in transform domain, DCTav and Laplacian Pyramid are performed well.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"2012 1","pages":"295-301"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86399877","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 : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653686
P. Rajarapollu, V. Mankar
Video have a basic and non basic features, where basic features includes e. g. color, shape, size and non basic features include orientation of a image. Whereas Video Sequences is a series of shots/frames on a subject that are edited together to tell a story. Visual features describes the details about the image contents, which are used in various applications like, visual search, object recognition, image registration and object tracking. Many visual analysis task requires the features to be transmitted, thus it calls for the different coding algorithms to attain a target level of efficiency. Here an effort has been taken to implement a coding algorithm for local features extraction such as SIFT (Scale Invariant Feature Transform). The first stage comprises of using the SIFT algorithm property to find the ‘point of interest’ of an image. Further the use Kalman Filter algorithm is done as an application purpose of motion based single or multiple object detection and tracking.
{"title":"Extraction of Visual Features from Video Sequences for Better Visual Analysis","authors":"P. Rajarapollu, V. Mankar","doi":"10.1109/I-SMAC.2018.8653686","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653686","url":null,"abstract":"Video have a basic and non basic features, where basic features includes e. g. color, shape, size and non basic features include orientation of a image. Whereas Video Sequences is a series of shots/frames on a subject that are edited together to tell a story. Visual features describes the details about the image contents, which are used in various applications like, visual search, object recognition, image registration and object tracking. Many visual analysis task requires the features to be transmitted, thus it calls for the different coding algorithms to attain a target level of efficiency. Here an effort has been taken to implement a coding algorithm for local features extraction such as SIFT (Scale Invariant Feature Transform). The first stage comprises of using the SIFT algorithm property to find the ‘point of interest’ of an image. Further the use Kalman Filter algorithm is done as an application purpose of motion based single or multiple object detection and tracking.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"16 1","pages":"220-223"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80073098","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 : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653742
S. Poorna, S. Anjana, P. Varma, Anjana Sajeev, K. Arya, S. Renjith, G. Nair
Recognizing emotions from facial images has become one of the major fields in affective computing arena since it has wide spread applications in robotics, medicine, surveillance, defense, e-learning, gaming, customer services etc. The study used Ekman model with 7 basic emotions- anger, happy, disgust, sad, fear, surprise and neutral acquired from subjects of Indian ethnicity. The acquired data base, Amritaemo consisted of 700 still images of Indian male and female subjects in seven emotions. The images were then cropped manually to obtain the region of analysis i.e. the face and converted to grayscale for further processing. Preprocessing techniques, histogram equalization and median filtering were applied to these after resizing. Discrete Wavelet Transform (DWT) was applied to these pre-processed images. The 2 D Haar wavelet coefficients (WC) were used to obtain the feature parameters. The maximum 2D correlation of mean value of one specific emotion versus all others was considered as the similarity feature. The squared difference of the emotional and neutral images in the transformed domain was considered as the difference feature. Supervised learning methods, K-Nearest Neighbor (KNN) and Artificial Neural Networks (ANN) were used to classify these features separately as well as together. The performance of these parameters were evaluated based on the measures accuracy, sensitivity and specificity.
{"title":"Facial Emotion Recognition using DWT based Similarity and Difference features","authors":"S. Poorna, S. Anjana, P. Varma, Anjana Sajeev, K. Arya, S. Renjith, G. Nair","doi":"10.1109/I-SMAC.2018.8653742","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653742","url":null,"abstract":"Recognizing emotions from facial images has become one of the major fields in affective computing arena since it has wide spread applications in robotics, medicine, surveillance, defense, e-learning, gaming, customer services etc. The study used Ekman model with 7 basic emotions- anger, happy, disgust, sad, fear, surprise and neutral acquired from subjects of Indian ethnicity. The acquired data base, Amritaemo consisted of 700 still images of Indian male and female subjects in seven emotions. The images were then cropped manually to obtain the region of analysis i.e. the face and converted to grayscale for further processing. Preprocessing techniques, histogram equalization and median filtering were applied to these after resizing. Discrete Wavelet Transform (DWT) was applied to these pre-processed images. The 2 D Haar wavelet coefficients (WC) were used to obtain the feature parameters. The maximum 2D correlation of mean value of one specific emotion versus all others was considered as the similarity feature. The squared difference of the emotional and neutral images in the transformed domain was considered as the difference feature. Supervised learning methods, K-Nearest Neighbor (KNN) and Artificial Neural Networks (ANN) were used to classify these features separately as well as together. The performance of these parameters were evaluated based on the measures accuracy, sensitivity and specificity.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"35 12 1","pages":"524-527"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77080863","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 : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653600
Niranjan R Pandeshwar, Preeti Jagadev
The splitting of data using DFSORT utility contributes hugely to MIPS which is an acronym for "Million Instructions Per Second". The MIPS has evolved to determine the processing power and CPU resource consumption. This study investigates and provides an optimized way of performing a balanced splitting of data and makes an effort to reduce the CPU consumption by decreasing the number of instructions needed to perform the same task. The three methods that are used for the same are the SUM FIELDS method, the EASYTRIEVE method and the ORD-MIN functions method. The three data split methods mentioned above have been compared for a large amount of input data and it has been shown that the ORD-MIN function aids MIPS reduction.
{"title":"MIPS reduction using ORD-MIN function in COBOL","authors":"Niranjan R Pandeshwar, Preeti Jagadev","doi":"10.1109/I-SMAC.2018.8653600","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653600","url":null,"abstract":"The splitting of data using DFSORT utility contributes hugely to MIPS which is an acronym for \"Million Instructions Per Second\". The MIPS has evolved to determine the processing power and CPU resource consumption. This study investigates and provides an optimized way of performing a balanced splitting of data and makes an effort to reduce the CPU consumption by decreasing the number of instructions needed to perform the same task. The three methods that are used for the same are the SUM FIELDS method, the EASYTRIEVE method and the ORD-MIN functions method. The three data split methods mentioned above have been compared for a large amount of input data and it has been shown that the ORD-MIN function aids MIPS reduction.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"45 1","pages":"196-199"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87553371","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 : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653722
P. M. Salunke, Vishal. V. Mahale
In this paper we proposed a novel technique to store the data authentically in the cloud. Since because of elastic property from the point of view of storage space cloud is most popular to store data. Cloud is inquiring about stores data on it. Therefore, security is must for store data for preserving it from malicious attackers as well as there may be leakage in stored data security. Many times there is necessary condition for hiding the user or data owner identity from cloud. A technique use in this paper shows anonymous authentication for stored data on cloud. This system preserves the identity of the users before storing it on cloud. The main aim of this paper is only valid user have ability to encrypt stored data with help of accessing its control features. The basic idea behind this scenario is to prevent stored data of cloud as well as its creation, modification etc. In this approach, cloud is familiar with access policies of every stored data also several KDCs are used for key management. Expensive operations are carried out easily in decentralized cloud system than centralized cloud system approach. The proposed system is implemented and tested in java with mysql database.
{"title":"Secure Data sharing in Distributed Cloud Environment","authors":"P. M. Salunke, Vishal. V. Mahale","doi":"10.1109/I-SMAC.2018.8653722","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653722","url":null,"abstract":"In this paper we proposed a novel technique to store the data authentically in the cloud. Since because of elastic property from the point of view of storage space cloud is most popular to store data. Cloud is inquiring about stores data on it. Therefore, security is must for store data for preserving it from malicious attackers as well as there may be leakage in stored data security. Many times there is necessary condition for hiding the user or data owner identity from cloud. A technique use in this paper shows anonymous authentication for stored data on cloud. This system preserves the identity of the users before storing it on cloud. The main aim of this paper is only valid user have ability to encrypt stored data with help of accessing its control features. The basic idea behind this scenario is to prevent stored data of cloud as well as its creation, modification etc. In this approach, cloud is familiar with access policies of every stored data also several KDCs are used for key management. Expensive operations are carried out easily in decentralized cloud system than centralized cloud system approach. The proposed system is implemented and tested in java with mysql database.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"119 1","pages":"262-266"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/I-SMAC.2018.8653722","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72522988","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 : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653782
K. Kumar, K. Krishna, K. Raghavendra, K. Harish
This paper presents the design and implementation of a 4-b Flash Analog to Digital Converter (ADC) in 180nm digital CMOS technology. The proposed flash ADC utilizes resistive ladder logic network, high speed comparators and a encoder logic to convert the given continuous input signal into output binary code. The flash ADC utilizes a novel encoder realized using pseudo dynamic CMOS logic which has been implemented with fewer transistors compared to the previous other techniques. Without the need of time interleaving technique, the proposed ADC is capable of operating at its full sampling rate. The designed flash ADC consumes 0.686mW when operated from a power supply voltage of 1.8V. The operating speed of this circuit is 10GHz and the simulated integral non-linearity error (INL) and differential non-linearity error (DNL) are between 0.1/-0.02LSB and 0.33/-0.12LSB respectively. It occupies an effective area of 0.32mm2.
{"title":"A High Speed Flash Analog to Digital Converter","authors":"K. Kumar, K. Krishna, K. Raghavendra, K. Harish","doi":"10.1109/I-SMAC.2018.8653782","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653782","url":null,"abstract":"This paper presents the design and implementation of a 4-b Flash Analog to Digital Converter (ADC) in 180nm digital CMOS technology. The proposed flash ADC utilizes resistive ladder logic network, high speed comparators and a encoder logic to convert the given continuous input signal into output binary code. The flash ADC utilizes a novel encoder realized using pseudo dynamic CMOS logic which has been implemented with fewer transistors compared to the previous other techniques. Without the need of time interleaving technique, the proposed ADC is capable of operating at its full sampling rate. The designed flash ADC consumes 0.686mW when operated from a power supply voltage of 1.8V. The operating speed of this circuit is 10GHz and the simulated integral non-linearity error (INL) and differential non-linearity error (DNL) are between 0.1/-0.02LSB and 0.33/-0.12LSB respectively. It occupies an effective area of 0.32mm2.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"49 1","pages":"283-288"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74986381","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 : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653763
A. Misra, D. S. Yadav
In this paper we have proposed a novel cluster based data sharing scheme that tries to employ the advantages of both clustering as well as proactive routing. Our clustering algorithm divides the MANET into clusters forming cluster heads, cluster gateways and cluster members during the cluster formation phase. We restrict the use of DSDV routing protocol within the cluster thereby reducing the control overhead and routing table size. Cluster maintenance and file index distribution within the cluster is done by adding extra fields in the DSDV control messages. Routing is done using the DSDV routing table. Unlike existing data lookup schemes, where a data lookup query is flooded in the entire MANET or in the cluster backbone, here it is forwarded to the nearest gateway node thereby completely eliminating flooding.
{"title":"Effective data lookup scheme for Cluster based Data Sharing in MANET","authors":"A. Misra, D. S. Yadav","doi":"10.1109/I-SMAC.2018.8653763","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653763","url":null,"abstract":"In this paper we have proposed a novel cluster based data sharing scheme that tries to employ the advantages of both clustering as well as proactive routing. Our clustering algorithm divides the MANET into clusters forming cluster heads, cluster gateways and cluster members during the cluster formation phase. We restrict the use of DSDV routing protocol within the cluster thereby reducing the control overhead and routing table size. Cluster maintenance and file index distribution within the cluster is done by adding extra fields in the DSDV control messages. Routing is done using the DSDV routing table. Unlike existing data lookup schemes, where a data lookup query is flooded in the entire MANET or in the cluster backbone, here it is forwarded to the nearest gateway node thereby completely eliminating flooding.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"51 1","pages":"367-372"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77925041","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 : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653748
S. Priya, Dr. R. Manavalan
Weighted Extreme Learning Machine (WELM) is one among the machine learning algorithms with extremely learning and good generalization capabilities. WELM handles the imbalanced dataset efficiently for assigning less weight to majority class and more weight to minority class. In general, the classification performance of WELM extremely depends on the parameters such as the input weight matrix, the value of bias and the number of hidden neurons and the weights associated with majority and minority classes. The arbitrary selection of hidden biases and the input weight, WELM produces inconsistent result. In this paper, hybridization of WELM with Invasive Weed optimization and WELM with BAT algorithm are proposed to tune the parameters for WELM such as initial weight and hidden bias values. The proposed methodologies are called as WELM- IWO and WELM-BAT. The proposed methods are evaluated over three real world medical diagnosis problems such as Hepatitis, Diabetes and Thyroid diseases. The experimental results proved that one of the proposed methods WELM-IWO outperforms well on all three datasets.
{"title":"Tuning the Parameters of Weighted ELM using IWO and BAT Algorithm to Improve the Classification Performance","authors":"S. Priya, Dr. R. Manavalan","doi":"10.1109/I-SMAC.2018.8653748","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653748","url":null,"abstract":"Weighted Extreme Learning Machine (WELM) is one among the machine learning algorithms with extremely learning and good generalization capabilities. WELM handles the imbalanced dataset efficiently for assigning less weight to majority class and more weight to minority class. In general, the classification performance of WELM extremely depends on the parameters such as the input weight matrix, the value of bias and the number of hidden neurons and the weights associated with majority and minority classes. The arbitrary selection of hidden biases and the input weight, WELM produces inconsistent result. In this paper, hybridization of WELM with Invasive Weed optimization and WELM with BAT algorithm are proposed to tune the parameters for WELM such as initial weight and hidden bias values. The proposed methodologies are called as WELM- IWO and WELM-BAT. The proposed methods are evaluated over three real world medical diagnosis problems such as Hepatitis, Diabetes and Thyroid diseases. The experimental results proved that one of the proposed methods WELM-IWO outperforms well on all three datasets.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"35 1","pages":"547-552"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78078402","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 : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653761
Richa Jain, Prof. Deepa Gianchandani
Detection and Recognition in traffic sign pictures or common pictures has applications in Computer vision frameworks like enlistment number plate identification, programmed movement sign location, picture recovery and help for outwardly disabled individuals. In this paper a hybrid approach based on MSER and OCR, utilizing clamor expulsion strategy, i.e. Lucy-Richardson calculation. After clamor evacuation, content district location stage begins with complexity upgraded edge improved MSER area discovery system is utilized there after morphological division is utilized to section content locale in the picture. After location stage acknowledgment stage begins in which content applicants are separated utilizing geometric filtration utilizing properties, for example, viewpoint proportion, unusualness, solidicity, and so forth. At that point Bounding box strategy is utilized to distinguish letter competitors and shape word out of them. At long last, Optical Character Recognition (OCR) instrument is utilized to concentrate message out of picture. The framework displayed beats best in class techniques on the dataset of the movement content sign information that were gotten from Jaguar Land Rover Research.
{"title":"A Hybrid Approach for Detection and Recognition of Traffic Text Sign using MSER and OCR","authors":"Richa Jain, Prof. Deepa Gianchandani","doi":"10.1109/I-SMAC.2018.8653761","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653761","url":null,"abstract":"Detection and Recognition in traffic sign pictures or common pictures has applications in Computer vision frameworks like enlistment number plate identification, programmed movement sign location, picture recovery and help for outwardly disabled individuals. In this paper a hybrid approach based on MSER and OCR, utilizing clamor expulsion strategy, i.e. Lucy-Richardson calculation. After clamor evacuation, content district location stage begins with complexity upgraded edge improved MSER area discovery system is utilized there after morphological division is utilized to section content locale in the picture. After location stage acknowledgment stage begins in which content applicants are separated utilizing geometric filtration utilizing properties, for example, viewpoint proportion, unusualness, solidicity, and so forth. At that point Bounding box strategy is utilized to distinguish letter competitors and shape word out of them. At long last, Optical Character Recognition (OCR) instrument is utilized to concentrate message out of picture. The framework displayed beats best in class techniques on the dataset of the movement content sign information that were gotten from Jaguar Land Rover Research.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"24 1","pages":"775-778"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78217691","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 : 2018-08-01DOI: 10.1109/I-SMAC.2018.8653718
Manish Nair, Samineni Rohith Kumar, N. A, Nihal Mohan, Anudev J
Physical activity is closely related to one’s health status. Man has always maintained a good health, improved blood circulation and has often come across through some superlative ideas while ambulating. Movement, meditation, health of blood pumping and rhythm of footsteps has been a primeval way of connecting with one’s deeper self. However, this seldom explains the importance of walking and tracking our health parameters. This paper is an attempt in the development of a prototype of a wearable fitness band with advance pedometer applications. Usually, pedometers are just designed to calculate the number of steps taken by the user or calculate the number of calories burnt. The prototype illustrated in the paper is an extension to the very same. Along with the above mentioned features, it also calculates the walking speed of the user and gives a vibration feedback if the current speed is below a certain threshold level.This system also contains a heart rate monitoring system along with a GPS and Bluetooth module. An Android app was also developed using MIT app inventor. The Bluetooth module is paired with the user’s smart phone. If the user experiences a sudden cardiac emergency, an SMS alert and call is made to his relatives with the app. The text message consists the latitude and longitude value where user is present. This band is not just a fitness tracker, but also an effort to contribute something towards a humanitarian cause.
{"title":"INSTANTANEOUS FEEDBACK PEDOMETER WITH EMERGENCY GPS TRACKER","authors":"Manish Nair, Samineni Rohith Kumar, N. A, Nihal Mohan, Anudev J","doi":"10.1109/I-SMAC.2018.8653718","DOIUrl":"https://doi.org/10.1109/I-SMAC.2018.8653718","url":null,"abstract":"Physical activity is closely related to one’s health status. Man has always maintained a good health, improved blood circulation and has often come across through some superlative ideas while ambulating. Movement, meditation, health of blood pumping and rhythm of footsteps has been a primeval way of connecting with one’s deeper self. However, this seldom explains the importance of walking and tracking our health parameters. This paper is an attempt in the development of a prototype of a wearable fitness band with advance pedometer applications. Usually, pedometers are just designed to calculate the number of steps taken by the user or calculate the number of calories burnt. The prototype illustrated in the paper is an extension to the very same. Along with the above mentioned features, it also calculates the walking speed of the user and gives a vibration feedback if the current speed is below a certain threshold level.This system also contains a heart rate monitoring system along with a GPS and Bluetooth module. An Android app was also developed using MIT app inventor. The Bluetooth module is paired with the user’s smart phone. If the user experiences a sudden cardiac emergency, an SMS alert and call is made to his relatives with the app. The text message consists the latitude and longitude value where user is present. This band is not just a fitness tracker, but also an effort to contribute something towards a humanitarian cause.","PeriodicalId":53631,"journal":{"name":"Koomesh","volume":"78 1","pages":"122-126"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79744255","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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