Pub Date : 2022-12-16DOI: 10.1109/SMART55829.2022.10047324
S. Pradeep, Yogesh Kumar Sharma, C. Verma, Neagu Bogdan Constantin, Z. Illés, M. Răboacă, Traian Candin Mihaltan
A severe hazard to human homes and forest ecosystems worldwide and many others circumstances are taking place, fires have a variety of detrimental effects. One result of such devastation is the greenhouse effect and changes to the climate. It's interesting to see that based on human activity and natural disasters like forest fires and power Fluctuation are increasing. Therefore, it's important to spot fires early on in order to reduce the damage that fires inflict. In this paper, the path are proposed for leveraging a WSN will initially starts to detect the fires. AI intelligence or deep learning techniques are taking part to give more accurate fire detection. Research on Artificial intelligence approaches like technical search and agents is extremely tempting for catastrophe look over like fire. Using AI approaches, a strategy for responding to fires is created. This is accomplished by combining WSN, CNN and AI agents. This work's outcome analysis is pretty effective.
{"title":"Utilizing WSN and Artificial Intelligence to Detect Fires","authors":"S. Pradeep, Yogesh Kumar Sharma, C. Verma, Neagu Bogdan Constantin, Z. Illés, M. Răboacă, Traian Candin Mihaltan","doi":"10.1109/SMART55829.2022.10047324","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047324","url":null,"abstract":"A severe hazard to human homes and forest ecosystems worldwide and many others circumstances are taking place, fires have a variety of detrimental effects. One result of such devastation is the greenhouse effect and changes to the climate. It's interesting to see that based on human activity and natural disasters like forest fires and power Fluctuation are increasing. Therefore, it's important to spot fires early on in order to reduce the damage that fires inflict. In this paper, the path are proposed for leveraging a WSN will initially starts to detect the fires. AI intelligence or deep learning techniques are taking part to give more accurate fire detection. Research on Artificial intelligence approaches like technical search and agents is extremely tempting for catastrophe look over like fire. Using AI approaches, a strategy for responding to fires is created. This is accomplished by combining WSN, CNN and AI agents. This work's outcome analysis is pretty effective.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122735847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.1109/SMART55829.2022.10046756
Shivani Joshi, B. S, Poonam Rawat, Deepali Deshpande, M. Chakravarthi, Devvret Verma
In order to prevent excessive energy usage and to identify water pollution, alternately, genuine process industry detection and picture categorization are now required. Scientists are looking for a limited and efficient IoT (Iot) device that would detect and assess the real-time state of industrial machinery since implementing automation in economic industries is often an expensive project. Additionally, the IoT technology may be used to classify images in order to find water contamination. This study has compared several picture binary classifiers and described the advantages and price of the IoT that is now accessible. On the basis of the opinions of returned questionnaires, a main numerical survey approach has been used to gather relevant data. After then, the “Normative” selecting method was used to analyse the main data and support a comparative evaluation. Internet of things iot (Sensor Networks) is a less advanced product that can be included into both small- and large-scale industrial businesses, according to research and analysis. For identifying contamination of water, classification IoT has been shown to be effective, and texture analysis is less expensive than spatial analysis.
{"title":"A Framework of Internet of Things (Iot) for the Manufacturing and Image Classification System","authors":"Shivani Joshi, B. S, Poonam Rawat, Deepali Deshpande, M. Chakravarthi, Devvret Verma","doi":"10.1109/SMART55829.2022.10046756","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10046756","url":null,"abstract":"In order to prevent excessive energy usage and to identify water pollution, alternately, genuine process industry detection and picture categorization are now required. Scientists are looking for a limited and efficient IoT (Iot) device that would detect and assess the real-time state of industrial machinery since implementing automation in economic industries is often an expensive project. Additionally, the IoT technology may be used to classify images in order to find water contamination. This study has compared several picture binary classifiers and described the advantages and price of the IoT that is now accessible. On the basis of the opinions of returned questionnaires, a main numerical survey approach has been used to gather relevant data. After then, the “Normative” selecting method was used to analyse the main data and support a comparative evaluation. Internet of things iot (Sensor Networks) is a less advanced product that can be included into both small- and large-scale industrial businesses, according to research and analysis. For identifying contamination of water, classification IoT has been shown to be effective, and texture analysis is less expensive than spatial analysis.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121875817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.1109/SMART55829.2022.10046870
Ramakant Upadhyay, Harinder Kaur
The curve of stock is unexpected. The complexity and unpredictability of stock market predictions make them difficult to make. Predicting the stability of future market stocks is the main goal for persuading the audience. Numerous analysts have conducted their study on how the industry would evolve in the future. Unreliable information is a component of stock, making knowledge a vital source of power. Impact of the prediction's strength on enduring possibilities. Deep learning has incorporated itself into the image for the development and projection of instruction sets and information models as part of the current development of exchange forecasting technology. To forecast and alter things as needed, Machine Learning uses whole distinct components methods and algorithms. The main topic of the paper is the Application of LSTM and regression to forecast stock values.
{"title":"A ML Algorithm was used to Forecast the Gain or Loss of a Shareholder in the Financial Markets","authors":"Ramakant Upadhyay, Harinder Kaur","doi":"10.1109/SMART55829.2022.10046870","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10046870","url":null,"abstract":"The curve of stock is unexpected. The complexity and unpredictability of stock market predictions make them difficult to make. Predicting the stability of future market stocks is the main goal for persuading the audience. Numerous analysts have conducted their study on how the industry would evolve in the future. Unreliable information is a component of stock, making knowledge a vital source of power. Impact of the prediction's strength on enduring possibilities. Deep learning has incorporated itself into the image for the development and projection of instruction sets and information models as part of the current development of exchange forecasting technology. To forecast and alter things as needed, Machine Learning uses whole distinct components methods and algorithms. The main topic of the paper is the Application of LSTM and regression to forecast stock values.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"52 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133337868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.1109/SMART55829.2022.10047018
Garima Sharma, Tanisha
In this article, we investigate how to build an intelligent network unit over a wireless network. To do so, we make use of a resilient routing strategy made available by the Protocol for power (RPL), the definition of which is currently being considered. Our architecture is based on a simple binary web service execution of the RE presentational State Transfer (REST) paradigm and an executing strategy in which every node makes a collection of components (such as atmospheric sensors) available to parties who are concerned with them. We present an evaluation of RPL by means of an experimental inquiry, with the focus being on how well it creates the routing structure to highlight how the efficiency of routing is influenced by the fundamental properties of RPL.
{"title":"Implementing a Smart Monitoring System with Wireless Sensor and Actuator Networks","authors":"Garima Sharma, Tanisha","doi":"10.1109/SMART55829.2022.10047018","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047018","url":null,"abstract":"In this article, we investigate how to build an intelligent network unit over a wireless network. To do so, we make use of a resilient routing strategy made available by the Protocol for power (RPL), the definition of which is currently being considered. Our architecture is based on a simple binary web service execution of the RE presentational State Transfer (REST) paradigm and an executing strategy in which every node makes a collection of components (such as atmospheric sensors) available to parties who are concerned with them. We present an evaluation of RPL by means of an experimental inquiry, with the focus being on how well it creates the routing structure to highlight how the efficiency of routing is influenced by the fundamental properties of RPL.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133497228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.1109/SMART55829.2022.10046896
Ashwini Kshirsagar, S. Pranavan, M. Nomani, V. Srivastav, C. Ramprasad, Surendra Kumar Shukla
Urban dwellers' quality of life may be improved by adopting unified, extensible, yet secure e - services thanks to the ongoing urban growth. Government entities are aware of how useful blockchains can be in addressing community issues. Bitcoin, which was primarily associated with the digital money bitcoins, provides a novel viewpoint as to how cities might be structured as well as a more open economical system for managing resources. This paper examines the potential benefits of ledger tech businesses for the growth of smart communities and suggests a Smart City ecological architecture based on intelligent contract involving firms, residents, or government agencies. It also provides an outline of the possible application areas for this technology. The findings might serve as a springboard for the creation of regional efforts to use the cryptocurrency as a framework for transactions and communications with in government service.
{"title":"Ecosystem Implementations in Smart City Through Block Chain Technology","authors":"Ashwini Kshirsagar, S. Pranavan, M. Nomani, V. Srivastav, C. Ramprasad, Surendra Kumar Shukla","doi":"10.1109/SMART55829.2022.10046896","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10046896","url":null,"abstract":"Urban dwellers' quality of life may be improved by adopting unified, extensible, yet secure e - services thanks to the ongoing urban growth. Government entities are aware of how useful blockchains can be in addressing community issues. Bitcoin, which was primarily associated with the digital money bitcoins, provides a novel viewpoint as to how cities might be structured as well as a more open economical system for managing resources. This paper examines the potential benefits of ledger tech businesses for the growth of smart communities and suggests a Smart City ecological architecture based on intelligent contract involving firms, residents, or government agencies. It also provides an outline of the possible application areas for this technology. The findings might serve as a springboard for the creation of regional efforts to use the cryptocurrency as a framework for transactions and communications with in government service.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"86 22","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131770569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.1109/SMART55829.2022.10047248
Yuvraj Sanjayrao Takey, Sai Gopal Tatikayala, M. U. Patil, Lakshmi Eswari P. R, Satyanadha Sarma Samavedam
Organizations regardless of their size are rapidly transforming, adopting and embracing digitalization amid the COVID pandemic. The pandemic forced organizations to ratio- nalize offline operations and swift towards online operations. Many organizations have digitized their services and have witnessed increasing Multistage cyber-attacks. Further, a lot of organizations have enabled remote access to the enterprise resources and services. As a result, organizations are striving to defend against Multistage cyber-attacks. These multistage attacks often spread across many stages, which is best described by MITRE Adversarial Tactics, Techniques, and Common Knowl- edge (ATT&CK) Framework. There are many research efforts for static detection of malicious binaries but very few or limited research targeting run-time detection of malicious processes in the system. Detection of these malicious processes are key for identifying new variants of multistage attacks or malware in the real world. This paper proposes a system for detecting multistage attacks in real-time or run-time by leveraging Machine learning and MITRE ATT&CK Framework. Machine learning facilitates detecting the malicious process in the system, and the MITRE ATT&CK framework offers insight into adversary techniques. Combination of these two is very effective in detecting multistage attacks and identifying individual stages. The proposed system shows promising results when tested on real-time/latest malware. Test result shows that our system can achieve 95.83% of accuracy. This paper discusses the challenges in detection of runtime malware, dataset generation
{"title":"Real Time Multistage Attack Detection Leveraging Machine Learning and MITRE Framework","authors":"Yuvraj Sanjayrao Takey, Sai Gopal Tatikayala, M. U. Patil, Lakshmi Eswari P. R, Satyanadha Sarma Samavedam","doi":"10.1109/SMART55829.2022.10047248","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047248","url":null,"abstract":"Organizations regardless of their size are rapidly transforming, adopting and embracing digitalization amid the COVID pandemic. The pandemic forced organizations to ratio- nalize offline operations and swift towards online operations. Many organizations have digitized their services and have witnessed increasing Multistage cyber-attacks. Further, a lot of organizations have enabled remote access to the enterprise resources and services. As a result, organizations are striving to defend against Multistage cyber-attacks. These multistage attacks often spread across many stages, which is best described by MITRE Adversarial Tactics, Techniques, and Common Knowl- edge (ATT&CK) Framework. There are many research efforts for static detection of malicious binaries but very few or limited research targeting run-time detection of malicious processes in the system. Detection of these malicious processes are key for identifying new variants of multistage attacks or malware in the real world. This paper proposes a system for detecting multistage attacks in real-time or run-time by leveraging Machine learning and MITRE ATT&CK Framework. Machine learning facilitates detecting the malicious process in the system, and the MITRE ATT&CK framework offers insight into adversary techniques. Combination of these two is very effective in detecting multistage attacks and identifying individual stages. The proposed system shows promising results when tested on real-time/latest malware. Test result shows that our system can achieve 95.83% of accuracy. This paper discusses the challenges in detection of runtime malware, dataset generation","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114731043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.1109/SMART55829.2022.10047440
Suhail Javed Quraishi, Rubina Liyakat Khan, Tanvir Mahmoud Hussein, Vineet Saxena, Sushovan Chaudhury, A. Rastogi
A congestion control mechanism is needed to balance the network load to prevent pack drops and avoid network deadlocks. The main purpose is to analyze efficient and reliable congestion control methods which will reduce the weaknesses in various existing congestion control methods and propose a framework to minimize the gateway congestion in the network. As the demand of heterogeneous users of computer network day by day dynamically and rapidly changing in many aspects, grounded on the application situations our congestion control mechanism functions well in the situations that occur in Internet. The maximum degree of dynamics can be handle efficiently by keeping the generality of its existing end-to-end solution in our congestion control design.
{"title":"A Study of Optimized Proposed Model for Gateway Congestion Control","authors":"Suhail Javed Quraishi, Rubina Liyakat Khan, Tanvir Mahmoud Hussein, Vineet Saxena, Sushovan Chaudhury, A. Rastogi","doi":"10.1109/SMART55829.2022.10047440","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047440","url":null,"abstract":"A congestion control mechanism is needed to balance the network load to prevent pack drops and avoid network deadlocks. The main purpose is to analyze efficient and reliable congestion control methods which will reduce the weaknesses in various existing congestion control methods and propose a framework to minimize the gateway congestion in the network. As the demand of heterogeneous users of computer network day by day dynamically and rapidly changing in many aspects, grounded on the application situations our congestion control mechanism functions well in the situations that occur in Internet. The maximum degree of dynamics can be handle efficiently by keeping the generality of its existing end-to-end solution in our congestion control design.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117156328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.1109/SMART55829.2022.10046727
J. Sahoo, Pooja Gupta
A biometric system can automatically identify a person by using a feature or attribute that is unique to that person. This can be accomplished through the use of a biometric. The system is the one that does this identification. It is generally agreed upon that iris recognition is the most reliable and accurate kind of biometric authentication that is currently available on the market [4], [6]. The eyelid, in conjunction with the eyelashes, can commonly hide a sizeable section of the iris. This is especially noticeable in people with blue eyes. Our method offers an innovative approach to the process of iris detection by making use of curve fitting in the analysis process. Iris recognition has the potential to be used in a broad number of settings, some examples of which include electronic commerce, information security, and door access control systems.
{"title":"Biometric System based on Eyelid Detection Innovation","authors":"J. Sahoo, Pooja Gupta","doi":"10.1109/SMART55829.2022.10046727","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10046727","url":null,"abstract":"A biometric system can automatically identify a person by using a feature or attribute that is unique to that person. This can be accomplished through the use of a biometric. The system is the one that does this identification. It is generally agreed upon that iris recognition is the most reliable and accurate kind of biometric authentication that is currently available on the market [4], [6]. The eyelid, in conjunction with the eyelashes, can commonly hide a sizeable section of the iris. This is especially noticeable in people with blue eyes. Our method offers an innovative approach to the process of iris detection by making use of curve fitting in the analysis process. Iris recognition has the potential to be used in a broad number of settings, some examples of which include electronic commerce, information security, and door access control systems.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117294933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.1109/SMART55829.2022.10046999
L. Poongothai, K. Sharmila
Vision loss can be a permanent disability of a human, that could be attributed to due to Retinal Detachment (RD). This is perilous disorder that could be caused due to dealignment of the layers in a retina. The choroid supplies oxygen and nutrients to the outer segments of the photoreceptors. The retina's photoreceptors will stop working if the choroid separates from the retina. The degree of dependence on the choroid is high, due to its supply of oxygen to the fovea that increases the breathability of the retinal blood vessels. This tapering of the oxygen levels can paramount to macula detachment that can be an irreversible damage to the cones and rods at the posterior pole, thereby leading to blindness. If the retina is quickly reattached, good vision can be preserved even if the macula is not removed. Retinal detachment hitherto has been studied through conceptual data processing and image processing techniques. However, this paper analyzes the retinal detachment for an individual through the various features, and the same is encompassed in an equational form to be termed as the “RDidean” evaluative system. The evaluative model thus explicitly categorizes the retinal database into normal and abnormal images based on the value obtained from the system. The performance of this system is then effectuated through diverse tree classifier models and the deep learning AlexNet classifier in MATLAB to comprehend the precision of classification. While effectively entailing another pool of algorithmic models like the SVM variations and the Naïve Bayesian methods to cognize the accuracy of retinal detachment severity that the evaluative system rendered. This indagation analyzes focusses to establish a corroborative and impeccable prediction system for the classification of normal and abnormal eye through color fundus images. Thereby aiding to improve the ergonomic environment of clinicians to improve the treatment plan, along with delivering complementary clinical decisions, and in institutionalizing affordability for patients through optimal cost for agnizing retinal detachments.
{"title":"Analysis of Retinal Detachment Severity using RDidean Evaluative System and Classifier Assessment Implementation Models","authors":"L. Poongothai, K. Sharmila","doi":"10.1109/SMART55829.2022.10046999","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10046999","url":null,"abstract":"Vision loss can be a permanent disability of a human, that could be attributed to due to Retinal Detachment (RD). This is perilous disorder that could be caused due to dealignment of the layers in a retina. The choroid supplies oxygen and nutrients to the outer segments of the photoreceptors. The retina's photoreceptors will stop working if the choroid separates from the retina. The degree of dependence on the choroid is high, due to its supply of oxygen to the fovea that increases the breathability of the retinal blood vessels. This tapering of the oxygen levels can paramount to macula detachment that can be an irreversible damage to the cones and rods at the posterior pole, thereby leading to blindness. If the retina is quickly reattached, good vision can be preserved even if the macula is not removed. Retinal detachment hitherto has been studied through conceptual data processing and image processing techniques. However, this paper analyzes the retinal detachment for an individual through the various features, and the same is encompassed in an equational form to be termed as the “RDidean” evaluative system. The evaluative model thus explicitly categorizes the retinal database into normal and abnormal images based on the value obtained from the system. The performance of this system is then effectuated through diverse tree classifier models and the deep learning AlexNet classifier in MATLAB to comprehend the precision of classification. While effectively entailing another pool of algorithmic models like the SVM variations and the Naïve Bayesian methods to cognize the accuracy of retinal detachment severity that the evaluative system rendered. This indagation analyzes focusses to establish a corroborative and impeccable prediction system for the classification of normal and abnormal eye through color fundus images. Thereby aiding to improve the ergonomic environment of clinicians to improve the treatment plan, along with delivering complementary clinical decisions, and in institutionalizing affordability for patients through optimal cost for agnizing retinal detachments.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115319143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.1109/SMART55829.2022.10047734
Lakshmaiah Alluri, Hemant Jeevan Magadum
Cycle sharing and vehicle sharing and monitoring system is the solutions for managing and monitoring shared cycles or vehicle remotely for pollution free operation and facility available to public to travel in Smart City. Cycle or vehicle sharing is a kind of personal or public transport. Cycle or vehicle can be parked at the place provided nearer to the network of stations. With an IoT application on mobile phone, a user can find the availability of a Cycle or vehicle from a station, if it is available user can use it for a short ride, later it can be return to the any other nearby station. So developments of Cycle or vehicle sharing stations are more useful for common public transport through which connectivity can be established between the smart stations so that last minute rush can be avoided. Traffic density can be reduced and also provide last-mile connectivity. The paper proposes development of highly efficient integrated Shared cycles or vehicle monitoring system with GPRS remote control and remotely locking and unlocking based on user request. The project proposes usage of solar powered locking system with low carbon footprint.
{"title":"Shared Cycle and Vehicle Sharing and Monitoring System","authors":"Lakshmaiah Alluri, Hemant Jeevan Magadum","doi":"10.1109/SMART55829.2022.10047734","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047734","url":null,"abstract":"Cycle sharing and vehicle sharing and monitoring system is the solutions for managing and monitoring shared cycles or vehicle remotely for pollution free operation and facility available to public to travel in Smart City. Cycle or vehicle sharing is a kind of personal or public transport. Cycle or vehicle can be parked at the place provided nearer to the network of stations. With an IoT application on mobile phone, a user can find the availability of a Cycle or vehicle from a station, if it is available user can use it for a short ride, later it can be return to the any other nearby station. So developments of Cycle or vehicle sharing stations are more useful for common public transport through which connectivity can be established between the smart stations so that last minute rush can be avoided. Traffic density can be reduced and also provide last-mile connectivity. The paper proposes development of highly efficient integrated Shared cycles or vehicle monitoring system with GPRS remote control and remotely locking and unlocking based on user request. The project proposes usage of solar powered locking system with low carbon footprint.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114081835","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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