{"title":"Centralized System for Infant Vaccination","authors":"Anshul Bamb, Shreeya Bhonsle","doi":"10.1109/IATMSI56455.2022.10119257","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119257","url":null,"abstract":"In developing nations that are densely populated, the need for a secure centralized portal for tracking infant inoculation and keeping a record of the same is necessary to increase the life expectancy rate of the nation. The paper proposes an architectural model of an infant inoculation tracking system that will eliminate all the discrepancies in the existing system. Eventually, it would help the government bodies, medical institutions, and primarily the parents to keep a paperless digital record of the procured and scheduled vaccines. The proposed system focuses on generating unique QR Codes for all the infants related to the registered parent.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134500656","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}
{"title":"Identification of Various Bamboo Diseases Using Deep Learning Approach","authors":"K. Kumar, Sachin Sharma, P. Pandey, H. Goyal","doi":"10.1109/IATMSI56455.2022.10119353","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119353","url":null,"abstract":"Bamboos with their enormous adaptations according to the environment, are used in almost all parts of the world. People often find these to be recognized as plants but instead, they belong to the family of grass. From ancient cultures to modern customization, they are always used. With that being said, these are the natural habitats that too suffer from diseases. Earlier papers were not available easily to the independent researcher and even there is less research on this field. The sole agenda of this paper is to provide all the answers related to the diseases which occur in bamboos. Firstly, we will check whether there is any disease in the sample taken, and then we will try to come up with some models to detect that disease. Here, we are taking the help of machine learning to determine the kind of disease. The Convolutional Neural Network model is used here for detection. Images have been used here as the data input for the training of the model, which Artificial Intelligence (AI) can easily process. This paper also represents the basic characteristics or properties of the diseases that can occur and how those will be distinguished. After all the citations of the earlier projects under this category, we have tried to come up with a solution that will be implemented accurately and efficiently.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116123644","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}
{"title":"Bayesian Network based Reliability Analysis in Edge Computing enabled Machine Vision System","authors":"Himanshu Gauttam, K.K. Pattanaik, Saumya Bhadauria, Garima Nain","doi":"10.1109/IATMSI56455.2022.10119369","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119369","url":null,"abstract":"Industry 4.0 (I4.0) solutions are realizing the goal of intelligent factories using digital transformation of the manufacturing and production industries. The Machine Vision System (MVS) ensures the required quality measures of vision-based inspection tasks in smart factories. The recent studies fused various trending technologies such as Industrial IoT (IIoT), Edge Computing, Artificial Intelligence, etc., to improve the performance of MVS in terms of reduced latency, improved inspection accuracy, etc. However, these studies did not focus on the reliability aspect and its impact on system performance when component(s) of MVS becomes faulty. Hence, this work proposes a Bayesian network-based framework for identifying defective component(s) in MVS. Analysis reveals that the proposed solution is suitable for reliability analysis and faulty component(s) identification of MVS to ensure the quality control in vision-based industrial applications.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125715565","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}
{"title":"Automated Quality Estimation of Collaboratively Created Content","authors":"Ashok Arora, Aniket Sharma, Pramod Kumar Singh","doi":"10.1109/IATMSI56455.2022.10119314","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119314","url":null,"abstract":"User-generated content (UGC) has garnered much attention as it allows users to consume and produce content at a fast rate. Although such flexibility encourages contribution and knowledge-sharing, it also raises a question about the quality of the content. In this work, we present an automated method to estimate the quality of the collaboratively created content on Web2.0 platforms using the example of wikiHow. We define quality as a collection of independent feature groups, each focusing on a distinct quality aspect. We analyze these quality indicators' contribution to estimating the content's quality.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123554870","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}
{"title":"Multi-Layer Perceptron Based Fuzzy Logic Technique for Detection of Attacks in VANETS","authors":"Shubham Shetty, M. D H","doi":"10.1109/IATMSI56455.2022.10119355","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119355","url":null,"abstract":"Vehicles are imparting messages with other vehicles in ad hoc network, which is referred as VANET communication. Due to the emerging of new technologies as part of industry 4.0 the VANET as frequently used in communication applications. But in this cyber attacks are increased in the VANETS communications. Scholars have proposed different solutions and algorithms to find the attacks. Here we have proposed a method that uses artificial intelligence. The proposed method is the combination of Neural Network based Multilayer Perceptron (MLP) trained Fuzzy Logic System procedure to spot unusual behavior of automobiles in the ad hoc network. To validate the results time of detection, positive rate, and ratio of detection is used. The outcome will giv the better performance existing methods.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"39 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124851388","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}
{"title":"A 3-Lock based Password Hashing Algorithm","authors":"Anuraj Singh, Mehul Jain, Sakshi Goyal","doi":"10.1109/IATMSI56455.2022.10119411","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119411","url":null,"abstract":"Password has become a predominating method for user authentication to gain access to restricted services. Most people use human-memorable passwords that are likely words in dictionaries or certain combinations of these words, which are easy to crack. The biggest problem with passwords is its strength. We introduce a 3-lock based password hashing algorithm which minimizes the fraction of password that would be cracked by an offline attacker without increasing computing time for a legitimate authentication server. It strengthens the user's weak password, by improving the character set from which password is selected. 3-lock based password hashing algorithm uses 3 locks consisting of various printable ASCII characters and an integer provided by the user. This integer is never stored in server's database. Finally, we analyze 3-lock based password hashing algorithm using RockYou password dataset. Our analysis shows that the proposed algorithm can reduce (up to 25%) fraction of password cracked by an offline attacker.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124973073","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}
S. Chiwande, Piyush Meshram, Abhishek Charde, Shreya Bhave, Sushma Nagdeote
{"title":"Machine Monitoring for Industry using Computer Vision","authors":"S. Chiwande, Piyush Meshram, Abhishek Charde, Shreya Bhave, Sushma Nagdeote","doi":"10.1109/IATMSI56455.2022.10119424","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119424","url":null,"abstract":"There are numerous approaches from which computer vision has been investigated. It moves beyond simply recording raw data to incorporate methods and concepts for computer graphics, pattern detection, digital image processing, and machine learning. This paper gives an outline of current technological advancements and theoretical ideas that describe how computer vision, mainly relates to image processing, and how it has evolved through time. It uses a technique for large-scale data analysis and a variety of application domains. The various research papers on computer vision and different techniques on object detection are reviewed in this paper. This paper gives the application of computer vision for factory and machine monitoring which will help to detect the object is moving or stable using YOLO algorithm. We also give a succinct summary of the most recent data regarding the effectiveness of the strategies.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129978772","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}
{"title":"An Empirical Study for Determining and Prioritizing of Enablers and Barriers to Appropriate Technology Management","authors":"Jayshree Patnaik, Ajit Kumar Pasayat","doi":"10.1109/IATMSI56455.2022.10119393","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119393","url":null,"abstract":"The potential of Appropriate Technology (AT) development at the Base of the Pyramid (BoP) for meeting economic, social, and environmental needs is rarely evaluated in various verticals. This study initially identified fourteen critical enablers and eight barriers to appropriate technology management through a systematic literature review and validated through multi-case studies. The ranking of different enablers and barriers and predicting their priorities were determined through Friedman Test. The analysis resulted in six enablers and five barriers critical to appropriate technology practices. ‘Understanding of socio-cultural context,’ ‘Utilization of local resources,’ ‘Understandability of technology,’ ‘Robust design,’ and ‘Technology Acceptance’ were the significant enablers. The significant barriers were ‘Technology Transfer,’ ‘Lack of implementation of local skills and knowledge, ‘Behavior Change,’ ‘Lack of Sensitivity,’ and ‘Weak Institutional Support.’ The findings of this study uncover the importance of enablers and barriers that can help organizations exploit these variables for the effective development and dissemination of appropriate technology in a specific region.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126451399","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}
{"title":"Design and Development of Electronic Speed Controller for Axial Flux BLDC Motor","authors":"V. Mahajan, V. Bhole, Salman Ahmed Shaikh","doi":"10.1109/IATMSI56455.2022.10119310","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119310","url":null,"abstract":"Axial Flux Motors(AFM) are the ultimate future of the EV sector, as AFM have high energy density and provide high torque to weight ratio as compared to radial flux configuration BLDC and Induction motors. In this paper, we propose to build an electronic speed controller for AFM. Currently available electronic speed controllers (ESC) are for drone BLDC motors in radial flux configuration and are of the capacity of 250 watts to 2 kW. This paper presents ESC for Axial flux BLDC for 2 kW to 10 kW capacity for e-bike application and for retrofitting in rickshaws and small pickups. In order to get a high fill factor (up to 90 per cent), a square-shaped copper wire has been used. The yoke-less structure helps us to reduce the stator mass, making the motor light-weight. The Axial flux BLDC can achieve up to 20,000 RPM. High RPM allows the use of axial flux motors in most of the mobility applications. This paper presents the work done for high power electric bikes (2kW-10kW) control using ESC.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128935076","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}
{"title":"A Deep Learning Model Approach Using Feature Engineering To Predict Melanoma Tumour Size","authors":"Trisha Sarkar, Mohit Parekh, S. Shetty, A. Bhise","doi":"10.1109/IATMSI56455.2022.10119334","DOIUrl":"https://doi.org/10.1109/IATMSI56455.2022.10119334","url":null,"abstract":"Melanoma, a lethal ailment, occurs when the melanocytes in our body become cancerous. The fatality rate for early detection of melanoma is relatively low, making early diagnosis critical. While most studies focus on classification techniques to identify the presence of malignant melanoma, this paper suggests a novel deep learning approach to estimate tumour size quantitatively. Initially, the features are pre-processed using a square root transformation function to improve the quality of the dataset, followed by the addition of novel features. These features are fed to an Artificial Neural Network to predict tumour size. This study compares the model performance before and after the addition of handcrafted features for different optimization algorithms. Excellent performance is obtained, with a very low mean square error of 0.0001 and a high coefficient of determination of 0.9976 for an Adam-optimized model using feature construction for the development set of data.","PeriodicalId":221211,"journal":{"name":"2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122459218","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}