Pub Date : 2019-04-01DOI: 10.1109/ICOEI.2019.8862567
Meetu Kandpal, Kalyani Patel
Success of any product may depend on the price of product. Demand of a product is one of the factors to be considered for deriving price of the product. As many IT companies have started to move towards the cloud computing and cloud resources are delivered as product over internet. There are many companies providing cloud services like salesforce.com, Amazon AWS, Microsoft azure etc. Different cloud service providers have different pricing policies to enhance the revenue and user satisfaction. The cloud providers have pricing schemes for cloud resources under fixed pricing and dynamic pricing. Some of them favor cloud providers, other cloud consumers. The paper presents a model to predict the price of cloud resource using Recurrent Neural Network(RNN) and auctioning method based on the parameters (as demand). The paper would give insight to researchers and cloud service providers to derive the policies based on the demand and other features.
{"title":"Pricing model for revenue generation using Recurrent Neural Network for Cloud service provider","authors":"Meetu Kandpal, Kalyani Patel","doi":"10.1109/ICOEI.2019.8862567","DOIUrl":"https://doi.org/10.1109/ICOEI.2019.8862567","url":null,"abstract":"Success of any product may depend on the price of product. Demand of a product is one of the factors to be considered for deriving price of the product. As many IT companies have started to move towards the cloud computing and cloud resources are delivered as product over internet. There are many companies providing cloud services like salesforce.com, Amazon AWS, Microsoft azure etc. Different cloud service providers have different pricing policies to enhance the revenue and user satisfaction. The cloud providers have pricing schemes for cloud resources under fixed pricing and dynamic pricing. Some of them favor cloud providers, other cloud consumers. The paper presents a model to predict the price of cloud resource using Recurrent Neural Network(RNN) and auctioning method based on the parameters (as demand). The paper would give insight to researchers and cloud service providers to derive the policies based on the demand and other features.","PeriodicalId":212501,"journal":{"name":"2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134533000","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 : 2019-04-01DOI: 10.1109/ICOEI.2019.8862553
G. Hemanth, M. Janardhan, L. Sujihelen
Nowadays, brain tumor detection has turned upas a general causality in the realm of health care. Brain tumor can be denoted as a malformed mass of tissue wherein the cells multiply abruptly and ceaselessly, that is there is no control over the growth of the cells. The process of Image segmentation is adopted for extracting abnormal tumor region within the brain. In the MRI (magnetic resonance image), segmentation of brain tissue holds very significant in order to identify the presence of outlines concerning the brain tumor. There is abundance of hidden information in stored in the Health care sector. With appropriate use of accurate data mining classification techniques, early prediction of any disease can be effectively performed. In the medical field, the techniques of ML (machine learning) and Data mining holds a significant stand. Majority of which is adopted effectively. The research examines list of risk factors that are being traced out in brain tumor surveillance systems. Also the method proposed assures to be highly efficient and precise for brain tumor detection, classification and segmentation. To achieve this precise automatic or semi-automatic methods are needed. The research proposes an automatic segmentation method that relies upon CNN (Convolution Neural Networks), determining small 3 × 3 kernels. By incorporating this single technique, segmentation and classification is accomplished. CNN (a ML technique) from NN (Neural Networks)wherein it has layer based for results classification. Various levels involved in the proposed mechanisms are: 1. Data collection, 2. Pre-processing, 3. Average filtering, 4. segmentation, 5. feature extraction, 6. CNN via classification and identification. By utilizing the DM (data mining) techniques, significant relations and patterns from the data can be extracted. The techniques of ML (machine learning) and Data mining are being effectively employed for brain tumor detection and prevention at an early stage.
{"title":"Design and Implementing Brain Tumor Detection Using Machine Learning Approach","authors":"G. Hemanth, M. Janardhan, L. Sujihelen","doi":"10.1109/ICOEI.2019.8862553","DOIUrl":"https://doi.org/10.1109/ICOEI.2019.8862553","url":null,"abstract":"Nowadays, brain tumor detection has turned upas a general causality in the realm of health care. Brain tumor can be denoted as a malformed mass of tissue wherein the cells multiply abruptly and ceaselessly, that is there is no control over the growth of the cells. The process of Image segmentation is adopted for extracting abnormal tumor region within the brain. In the MRI (magnetic resonance image), segmentation of brain tissue holds very significant in order to identify the presence of outlines concerning the brain tumor. There is abundance of hidden information in stored in the Health care sector. With appropriate use of accurate data mining classification techniques, early prediction of any disease can be effectively performed. In the medical field, the techniques of ML (machine learning) and Data mining holds a significant stand. Majority of which is adopted effectively. The research examines list of risk factors that are being traced out in brain tumor surveillance systems. Also the method proposed assures to be highly efficient and precise for brain tumor detection, classification and segmentation. To achieve this precise automatic or semi-automatic methods are needed. The research proposes an automatic segmentation method that relies upon CNN (Convolution Neural Networks), determining small 3 × 3 kernels. By incorporating this single technique, segmentation and classification is accomplished. CNN (a ML technique) from NN (Neural Networks)wherein it has layer based for results classification. Various levels involved in the proposed mechanisms are: 1. Data collection, 2. Pre-processing, 3. Average filtering, 4. segmentation, 5. feature extraction, 6. CNN via classification and identification. By utilizing the DM (data mining) techniques, significant relations and patterns from the data can be extracted. The techniques of ML (machine learning) and Data mining are being effectively employed for brain tumor detection and prevention at an early stage.","PeriodicalId":212501,"journal":{"name":"2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133085114","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 : 2019-04-01DOI: 10.1109/ICOEI.2019.8862700
Shambhavi S. Salelkar, Palhavi Kerkar
A Rectangular microsrip patch antenna with a semicircular slot is fabricated which is desirable for ISM band applications. The main objective of this antenna is to have less loss and substantial gain. The resonant frequency of this antenna which is at ISM band is 5.8 GHz. Three antennas are been designed. A patch antenna, an array of 2×1 and 2×2 is plotted on the FR4 substrate with the relative permittivity of 4.4. An amount of air gap is kept between the ground plane and the substrate. The software that is used for designing this antenna is IE3D. The designed antenna at 5.8 GHz provides the outcome that gives return loss of −16 dB, −23 dB and −39.9 dB, gain of 5.4 dB, 7.2 dB and 8.9 db, VSWR of 1.02, 1.1 and 1.2 respectively. The size of the antenna is very compact and hence it is easy to fabricate. WiFi, W-LAN, Bluetooth are the applications of ISM Band that is provide by this antenna.
{"title":"Patch Antenna for ISM Band Application","authors":"Shambhavi S. Salelkar, Palhavi Kerkar","doi":"10.1109/ICOEI.2019.8862700","DOIUrl":"https://doi.org/10.1109/ICOEI.2019.8862700","url":null,"abstract":"A Rectangular microsrip patch antenna with a semicircular slot is fabricated which is desirable for ISM band applications. The main objective of this antenna is to have less loss and substantial gain. The resonant frequency of this antenna which is at ISM band is 5.8 GHz. Three antennas are been designed. A patch antenna, an array of 2×1 and 2×2 is plotted on the FR4 substrate with the relative permittivity of 4.4. An amount of air gap is kept between the ground plane and the substrate. The software that is used for designing this antenna is IE3D. The designed antenna at 5.8 GHz provides the outcome that gives return loss of −16 dB, −23 dB and −39.9 dB, gain of 5.4 dB, 7.2 dB and 8.9 db, VSWR of 1.02, 1.1 and 1.2 respectively. The size of the antenna is very compact and hence it is easy to fabricate. WiFi, W-LAN, Bluetooth are the applications of ISM Band that is provide by this antenna.","PeriodicalId":212501,"journal":{"name":"2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133150865","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 : 2019-04-01DOI: 10.1109/ICOEI.2019.8862655
R. Kingsta, K. Seyatha
The modern wireless communication system requires high performance antenna. To meet this objective, this paper presents the design of Metamaterial Superstrate Antenna mainly used for Dedicated Short Range Communication (DSRC) Applications. This antenna consists of an array of rectangular patches which are connected using microstrip line and fed by a 50 ohm microstrip line. The “I” shaped unit cell slots of different sizes are located above the metamaterial superstrate structure. The enhancement in the gain and directivity of the metamaterial antenna is the prime objective of this work. In order to achieve higher gain and directivity, metamaterial superstrate antenna is designed and optimized using Genetic Algorithm and Pattern Search Algorithm. The proposed antenna is designed and fabricated using the commercially available FR4 material. The gain and directivity obtained before optimization are 8.13 dB and 8.08 dB. In order to further improve the gain and directivity of the antenna, various techniques are incorporated to optimize the parameters such as length and width of the ground plane and length of the patch and the results are compared in terms of gain, directivity, return loss and run time required to find the optimal value. The optimized gain and directivity of the Metamaterial Superstrate Antenna using Pattern Search Optimization method are 9.9386 dB and 9.9350 dB at the operating frequency of 5.9 GHz with the return loss of -21.5133 dB.
{"title":"Design and Performance Comparison of Metamaterial Superstrate Antenna for DSRC Applications","authors":"R. Kingsta, K. Seyatha","doi":"10.1109/ICOEI.2019.8862655","DOIUrl":"https://doi.org/10.1109/ICOEI.2019.8862655","url":null,"abstract":"The modern wireless communication system requires high performance antenna. To meet this objective, this paper presents the design of Metamaterial Superstrate Antenna mainly used for Dedicated Short Range Communication (DSRC) Applications. This antenna consists of an array of rectangular patches which are connected using microstrip line and fed by a 50 ohm microstrip line. The “I” shaped unit cell slots of different sizes are located above the metamaterial superstrate structure. The enhancement in the gain and directivity of the metamaterial antenna is the prime objective of this work. In order to achieve higher gain and directivity, metamaterial superstrate antenna is designed and optimized using Genetic Algorithm and Pattern Search Algorithm. The proposed antenna is designed and fabricated using the commercially available FR4 material. The gain and directivity obtained before optimization are 8.13 dB and 8.08 dB. In order to further improve the gain and directivity of the antenna, various techniques are incorporated to optimize the parameters such as length and width of the ground plane and length of the patch and the results are compared in terms of gain, directivity, return loss and run time required to find the optimal value. The optimized gain and directivity of the Metamaterial Superstrate Antenna using Pattern Search Optimization method are 9.9386 dB and 9.9350 dB at the operating frequency of 5.9 GHz with the return loss of -21.5133 dB.","PeriodicalId":212501,"journal":{"name":"2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"275 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134305314","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 : 2019-04-01DOI: 10.1109/ICOEI.2019.8862762
Sanket Chandrakant Mungale, M. Sankar, D. Mudgal
The present control and management system analysis technique is the most critical work for public life, because traffic management services is programmed to provide smart service to people in their day to day life, .so artificial intelligence and deep learning methodology currently a days preferred technique, in many country has searches that sort resolution, and now more country developed this method victimizes next generation network technology, which enables a lot of reliable sources to manmade hand control.
{"title":"Study the Fundamental Conpect of Traffic Management System Analysis Methodology Victimization Using Image Development Processing","authors":"Sanket Chandrakant Mungale, M. Sankar, D. Mudgal","doi":"10.1109/ICOEI.2019.8862762","DOIUrl":"https://doi.org/10.1109/ICOEI.2019.8862762","url":null,"abstract":"The present control and management system analysis technique is the most critical work for public life, because traffic management services is programmed to provide smart service to people in their day to day life, .so artificial intelligence and deep learning methodology currently a days preferred technique, in many country has searches that sort resolution, and now more country developed this method victimizes next generation network technology, which enables a lot of reliable sources to manmade hand control.","PeriodicalId":212501,"journal":{"name":"2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134416033","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 : 2019-04-01DOI: 10.1109/ICOEI.2019.8862734
Aswathi Balachandran, Ramalakshmi, Venkatesan, M. Lakshmi, K. Jahnavi, V. Jothi
The goal of the proposed work is to minimize the energy consumption in a particular home or a region. The focus of energy consumption for smart home has been sensing depth on collecting as much as data as possible from each home or region. The paper presents have designed and deployed a smart system which leads each person to understand about the importance of intelligent buildings or smart home and their aim in reducing the energy consumption. The essence of this paper is all about collecting the different datasets for different home or different region as much as possible. It contains the information about different home appliances from a hair dryer to a refrigerator and their electricity usage for every second, temperature prediction, humidity and so on. The data that have collected has served as the foundation of this paper. And the datasets have described about those datasets and the tools that has used for implementing. The datasets and the tools are provided below so that it will be useful for further research in future on designing smart homes.
{"title":"Energy Consumption Analysis And Load Management For Smart Home","authors":"Aswathi Balachandran, Ramalakshmi, Venkatesan, M. Lakshmi, K. Jahnavi, V. Jothi","doi":"10.1109/ICOEI.2019.8862734","DOIUrl":"https://doi.org/10.1109/ICOEI.2019.8862734","url":null,"abstract":"The goal of the proposed work is to minimize the energy consumption in a particular home or a region. The focus of energy consumption for smart home has been sensing depth on collecting as much as data as possible from each home or region. The paper presents have designed and deployed a smart system which leads each person to understand about the importance of intelligent buildings or smart home and their aim in reducing the energy consumption. The essence of this paper is all about collecting the different datasets for different home or different region as much as possible. It contains the information about different home appliances from a hair dryer to a refrigerator and their electricity usage for every second, temperature prediction, humidity and so on. The data that have collected has served as the foundation of this paper. And the datasets have described about those datasets and the tools that has used for implementing. The datasets and the tools are provided below so that it will be useful for further research in future on designing smart homes.","PeriodicalId":212501,"journal":{"name":"2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"170 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132060427","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 : 2019-04-01DOI: 10.1109/ICOEI.2019.8862757
N. Andrews, Sherin Jacob, Steffi Thomas, S. Sukumar, Reni K. K Cherian
Vast number of control researches and numerous control applications were displayed amid the most recent years, focused on control of robotic arms. A robotic arm is a kind of mechanical arm, ordinarily programmable, which have similar abilities to a human arm. Building a mechanical arm is certainly not another idea, yet in the meantime, the structure and the determination can fluctuate from various plans. We developed a working prototype of a voice-controlled robotic arm for physically differently abled people. The main aim of the project is to develop a low-cost robot hand that is light and strong. Robotics is an interesting area of research in the field of Engineering. Our project is a voice-controlled robot which does some predefined actions based on the commands we give. We are giving the input speech through the Android phone. The Android operating system widely used in mobile phones, digital cameras are user-friendly and can be controlled by everyone. The Android phone and robotic arm are associated with Bluetooth module. The hand movements are done using circuitry of servo motors which placed and aligned at specific rotations and positions. The movement control is done by a microcontroller. The controller receives a voice command from the smartphone and the nature of the grab will be depending on the voice commands received.
{"title":"Low-Cost Robotic Arm for differently abled using Voice Recognition","authors":"N. Andrews, Sherin Jacob, Steffi Thomas, S. Sukumar, Reni K. K Cherian","doi":"10.1109/ICOEI.2019.8862757","DOIUrl":"https://doi.org/10.1109/ICOEI.2019.8862757","url":null,"abstract":"Vast number of control researches and numerous control applications were displayed amid the most recent years, focused on control of robotic arms. A robotic arm is a kind of mechanical arm, ordinarily programmable, which have similar abilities to a human arm. Building a mechanical arm is certainly not another idea, yet in the meantime, the structure and the determination can fluctuate from various plans. We developed a working prototype of a voice-controlled robotic arm for physically differently abled people. The main aim of the project is to develop a low-cost robot hand that is light and strong. Robotics is an interesting area of research in the field of Engineering. Our project is a voice-controlled robot which does some predefined actions based on the commands we give. We are giving the input speech through the Android phone. The Android operating system widely used in mobile phones, digital cameras are user-friendly and can be controlled by everyone. The Android phone and robotic arm are associated with Bluetooth module. The hand movements are done using circuitry of servo motors which placed and aligned at specific rotations and positions. The movement control is done by a microcontroller. The controller receives a voice command from the smartphone and the nature of the grab will be depending on the voice commands received.","PeriodicalId":212501,"journal":{"name":"2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132141627","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 : 2019-04-01DOI: 10.1109/ICOEI.2019.8862595
A. Jagadale, S. S. Sonavane, D.V. Jadav
Survey done by world health organization for probing causes of blindness indicates that cataract is major cause of blindness. Even age related cataract is most commonly observed, it is serious cause to think because of its appearance in minors and children for both eyes. Detecting cataract at earlier stage is challenge as it has less affecting vision. The three most general types of cataract are nuclear cataract, cortical cataract and post subcapsular cataract. Slit lamp observation with lens opacity classification system (LOCS-III) is used for detection and medical diagnosis by ophthalmologists. Lens replacement surgery is most common treatment suggested on cataract for correcting vision. Literature survey indicates towards the success and correctness of computer added detection and grading is function of correctness of lens localization from cataract eye image. The work presented in this paper uses slit lamp images from ophthalmologist at eye hospital with computer aided image processing to detect cataract at earlier stage. The challenge of detection of cataract at earlier stage is attended in steps like lens detection, lens segmentation, feature extraction and categorization. The overall accuracy is enhanced by use of Hough circle detection transform for lens detection and support vector machine for categorization. The detection and categorization is performed using statistical feature extraction with prior trained support vector machine.
{"title":"Computer Aided System For Early Detection Of Nuclear Cataract Using Circle Hough Transform","authors":"A. Jagadale, S. S. Sonavane, D.V. Jadav","doi":"10.1109/ICOEI.2019.8862595","DOIUrl":"https://doi.org/10.1109/ICOEI.2019.8862595","url":null,"abstract":"Survey done by world health organization for probing causes of blindness indicates that cataract is major cause of blindness. Even age related cataract is most commonly observed, it is serious cause to think because of its appearance in minors and children for both eyes. Detecting cataract at earlier stage is challenge as it has less affecting vision. The three most general types of cataract are nuclear cataract, cortical cataract and post subcapsular cataract. Slit lamp observation with lens opacity classification system (LOCS-III) is used for detection and medical diagnosis by ophthalmologists. Lens replacement surgery is most common treatment suggested on cataract for correcting vision. Literature survey indicates towards the success and correctness of computer added detection and grading is function of correctness of lens localization from cataract eye image. The work presented in this paper uses slit lamp images from ophthalmologist at eye hospital with computer aided image processing to detect cataract at earlier stage. The challenge of detection of cataract at earlier stage is attended in steps like lens detection, lens segmentation, feature extraction and categorization. The overall accuracy is enhanced by use of Hough circle detection transform for lens detection and support vector machine for categorization. The detection and categorization is performed using statistical feature extraction with prior trained support vector machine.","PeriodicalId":212501,"journal":{"name":"2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132272246","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 : 2019-04-01DOI: 10.1109/ICOEI.2019.8862543
C. Rohith, Shilpa A Nair, Parvathi S. Nair, S. Alphonsa, Nithin Prince John
Bike riders have been rapidly increasing amid time in various countries. Motorbikes are favoured by citizens belonging to different classes of the society due to many reasons such as its economic value. Wearing helmets is compulsory according to the standard however the vast majority avoid it. A principal goal of the helmet is to guarantee the safety of the riders. Our research intends to make an automated system to distinguish whether a biker is wearing a helmet or not and to impose fine to defaulters as a part of law enforcement. According to our research, such a system is not currently used by the police or by any other authority. Executing the proposed framework can convey more mindfulness and need to wear a helmet at any rate with the goal that they don't get captured on camera and avoid fine. This project intends to make deep learning based automated detection system for helmet identification using trained models and datasets that would be useful for the police department to enforce the law for the betterment of the society.
{"title":"An Efficient Helmet Detection for MVD using Deep learning","authors":"C. Rohith, Shilpa A Nair, Parvathi S. Nair, S. Alphonsa, Nithin Prince John","doi":"10.1109/ICOEI.2019.8862543","DOIUrl":"https://doi.org/10.1109/ICOEI.2019.8862543","url":null,"abstract":"Bike riders have been rapidly increasing amid time in various countries. Motorbikes are favoured by citizens belonging to different classes of the society due to many reasons such as its economic value. Wearing helmets is compulsory according to the standard however the vast majority avoid it. A principal goal of the helmet is to guarantee the safety of the riders. Our research intends to make an automated system to distinguish whether a biker is wearing a helmet or not and to impose fine to defaulters as a part of law enforcement. According to our research, such a system is not currently used by the police or by any other authority. Executing the proposed framework can convey more mindfulness and need to wear a helmet at any rate with the goal that they don't get captured on camera and avoid fine. This project intends to make deep learning based automated detection system for helmet identification using trained models and datasets that would be useful for the police department to enforce the law for the betterment of the society.","PeriodicalId":212501,"journal":{"name":"2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116595407","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 : 2019-04-01DOI: 10.1109/ICOEI.2019.8862594
V. Harshini, Shreevani Danai, H R Usha, Manjunath R. Kounte
The world is moving towards progress, to achieve the desired progress, the world should have a healthy population and health records are the projections of an individual's health over time. The centralised approach of maintaining the health records lead to data breaches. According to 2017 Ponemon Cost of Data Breach Study, the cost of the data breach for healthcare organizations estimated to be $380 per record. According to 2016 Breach Barometer Report, 27,314,647 patient records were affected. So we moved towards institution-driven approach of record maintenance, which didn't make much difference with the previously existing one. Since the patient have no control over the data, the chances of data being misused is high. So we need a patient-centered approach which is completely decentralised, which can identify data thefts, prevent data manipulation, and patient has the right in access control. Blockchain Technology serves as a best solution to address all the problems and fulfill the needs. Blockchain being a decentralised and distributed ledger it can also impact on billing, record sharing, medical research, identify thefts and financial data crimes in days to come. Implementation of smart contracts in health care can simplify things even better. Where invoking, record creation and validation will be done on Blockchain. This paper highlights on the patient-driven model of record maintenance using Blockchain technology where smart contracts can be incorporated in future days making it more potential in data exchange. Finding its huge scope, hoping that more researches will be carried out and practically implemented.
{"title":"Health Record Management through Blockchain Technology","authors":"V. Harshini, Shreevani Danai, H R Usha, Manjunath R. Kounte","doi":"10.1109/ICOEI.2019.8862594","DOIUrl":"https://doi.org/10.1109/ICOEI.2019.8862594","url":null,"abstract":"The world is moving towards progress, to achieve the desired progress, the world should have a healthy population and health records are the projections of an individual's health over time. The centralised approach of maintaining the health records lead to data breaches. According to 2017 Ponemon Cost of Data Breach Study, the cost of the data breach for healthcare organizations estimated to be $380 per record. According to 2016 Breach Barometer Report, 27,314,647 patient records were affected. So we moved towards institution-driven approach of record maintenance, which didn't make much difference with the previously existing one. Since the patient have no control over the data, the chances of data being misused is high. So we need a patient-centered approach which is completely decentralised, which can identify data thefts, prevent data manipulation, and patient has the right in access control. Blockchain Technology serves as a best solution to address all the problems and fulfill the needs. Blockchain being a decentralised and distributed ledger it can also impact on billing, record sharing, medical research, identify thefts and financial data crimes in days to come. Implementation of smart contracts in health care can simplify things even better. Where invoking, record creation and validation will be done on Blockchain. This paper highlights on the patient-driven model of record maintenance using Blockchain technology where smart contracts can be incorporated in future days making it more potential in data exchange. Finding its huge scope, hoping that more researches will be carried out and practically implemented.","PeriodicalId":212501,"journal":{"name":"2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116237961","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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