Pub Date : 2023-01-05DOI: 10.1109/IDCIoT56793.2023.10053535
K. Santhosh, KALAGOTLA CHENCHIREDDY, Pulluri Vaishnavi, A. Greeshmanth, V. Kumar, Police Nandakishore Reddy
In this paper, A crystal clear explanation is seen regarding improvement in a power quality distribution system. When the electrical power system appears to be out of phase that is either unbalanced of power on the source side or load side irrespective of any case FACTS (Flexible AC Transmission system) devices are used FACTS is nothing more than a program that uses electronic controllers to boost the effectiveness of current power systems. Over the past few years, research on new developing technologies has also been ongoing. STATCOM is one of the important FACTS controller devices. Overall from a cost point of view, VSI (Voltage source inverter) is preferred. DSTATCOM (Supply static compensator) is placed at PCC (point of the mutual link) to solve the above problem which is to get into the phase of currents and voltages. A DSTATCOM has different theories to explain but here SRFT (Synchronous reference frame theory) and IRPT(Instantaneous reactive power theory) are explored. After processing, the results are simulated by using MATLAB/SIMULINK
{"title":"Time-Domain Control Algorithms of DSTATCOM in a 3-Phase, 3-Wire Distribution System","authors":"K. Santhosh, KALAGOTLA CHENCHIREDDY, Pulluri Vaishnavi, A. Greeshmanth, V. Kumar, Police Nandakishore Reddy","doi":"10.1109/IDCIoT56793.2023.10053535","DOIUrl":"https://doi.org/10.1109/IDCIoT56793.2023.10053535","url":null,"abstract":"In this paper, A crystal clear explanation is seen regarding improvement in a power quality distribution system. When the electrical power system appears to be out of phase that is either unbalanced of power on the source side or load side irrespective of any case FACTS (Flexible AC Transmission system) devices are used FACTS is nothing more than a program that uses electronic controllers to boost the effectiveness of current power systems. Over the past few years, research on new developing technologies has also been ongoing. STATCOM is one of the important FACTS controller devices. Overall from a cost point of view, VSI (Voltage source inverter) is preferred. DSTATCOM (Supply static compensator) is placed at PCC (point of the mutual link) to solve the above problem which is to get into the phase of currents and voltages. A DSTATCOM has different theories to explain but here SRFT (Synchronous reference frame theory) and IRPT(Instantaneous reactive power theory) are explored. After processing, the results are simulated by using MATLAB/SIMULINK","PeriodicalId":60583,"journal":{"name":"物联网技术","volume":"82 1","pages":"781-785"},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75439968","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 : 2023-01-05DOI: 10.1109/IDCIoT56793.2023.10053464
Veena Kumari H M, Suresh D S
According to World Health Organization, heart disease is the principal cause of death. In the medical domain, to improve diagnosis accuracy researchers have introduced several data mining techniques for the prediction of cardiovascular diseases. The aim of the proposed research is that prediction of heart disease more precisely using an ensemble stacking model which is based on the mixing of heterogeneous classifiers. The research article consists of major two parts. First, analysis on choosing of best meta classifier with a different set of base classifiers and secondly, prediction using an ensemble framework. The experimental end prediction compared with other data mining algorithms. Further, the performance analysis is carried out by accuracy, precision, and recall and f1 score. Better analysis was done by ROC, P_R curve, and AUC. Analysis of the ensemble result shows that Ensemble techniques give better accuracy of 90.16% for testing dataset. Precision, Recall and f1 scores for 92%, 85% and 88% for the classification of sick patients, whereas 89%, 94% and 91 % for healthy patients. The AUC is 0.88 for the heart disease dataset.
{"title":"Performance Analysis of Base and Meta Classifiers and the Prediction of Cardiovascular Disease using Ensemble Stacking","authors":"Veena Kumari H M, Suresh D S","doi":"10.1109/IDCIoT56793.2023.10053464","DOIUrl":"https://doi.org/10.1109/IDCIoT56793.2023.10053464","url":null,"abstract":"According to World Health Organization, heart disease is the principal cause of death. In the medical domain, to improve diagnosis accuracy researchers have introduced several data mining techniques for the prediction of cardiovascular diseases. The aim of the proposed research is that prediction of heart disease more precisely using an ensemble stacking model which is based on the mixing of heterogeneous classifiers. The research article consists of major two parts. First, analysis on choosing of best meta classifier with a different set of base classifiers and secondly, prediction using an ensemble framework. The experimental end prediction compared with other data mining algorithms. Further, the performance analysis is carried out by accuracy, precision, and recall and f1 score. Better analysis was done by ROC, P_R curve, and AUC. Analysis of the ensemble result shows that Ensemble techniques give better accuracy of 90.16% for testing dataset. Precision, Recall and f1 scores for 92%, 85% and 88% for the classification of sick patients, whereas 89%, 94% and 91 % for healthy patients. The AUC is 0.88 for the heart disease dataset.","PeriodicalId":60583,"journal":{"name":"物联网技术","volume":"24 1","pages":"584-589"},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74796604","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 : 2023-01-05DOI: 10.1109/IDCIoT56793.2023.10053411
Ramya Palaniappan, S. R, Suseendran Surendran
Hypoglycemia / Hyperglycemia is a long-term metabolic disorder in which the Blood Glucose (BG) level of the patient is low or high than the standard range. High blood glucose level if untreated can cause heart disease, stroke, blindness, kidney failure and amputation of toes, feet or legs. The Internet of Medical Things(IoMT) is the amalgamation of the information from medical devices and medical software applications that connects healthcare IT systems seamlessly. Remote Health Monitoring System (RHMS) is the process of making use of the technology for providing medical services to the patients in non-clinical environment. In situations where the patients cannot reach the clinical environment, RHMS when incorporated will aid the healthcare professionals to deliver personalized treatment for the patients. In this study, IoMT enabled Continuous Glucose Monitoring (CGM) system enables continuous automated monitoring of blood glucose(BG) levels of the patients at regular intervals. This reduces the burden of measuring the BG levels and recording the results manually for further follow up. This continuous monitoring environment can send alerts to the patients and or to the clinicians when the BG levels are out of the normal range. This CGM system will be beneficial for the clinicians to alert Individuals about the upcoming health complications and recommend quality lifestyle for them to stay healthy. Yellow Springs Instrument’s (YSI) BG readings are used to compare the proposed CGM system’s performance in terms of Mean Absolute Relative Difference (MARD). Additionally, the challenges and threats associated with constructing the IoMT ecosystem were highlighted, as well as potential solutions.
{"title":"Implantable Smart Devices for Remote Health Monitoring to Detect Hypo/Hyperglycaemia","authors":"Ramya Palaniappan, S. R, Suseendran Surendran","doi":"10.1109/IDCIoT56793.2023.10053411","DOIUrl":"https://doi.org/10.1109/IDCIoT56793.2023.10053411","url":null,"abstract":"Hypoglycemia / Hyperglycemia is a long-term metabolic disorder in which the Blood Glucose (BG) level of the patient is low or high than the standard range. High blood glucose level if untreated can cause heart disease, stroke, blindness, kidney failure and amputation of toes, feet or legs. The Internet of Medical Things(IoMT) is the amalgamation of the information from medical devices and medical software applications that connects healthcare IT systems seamlessly. Remote Health Monitoring System (RHMS) is the process of making use of the technology for providing medical services to the patients in non-clinical environment. In situations where the patients cannot reach the clinical environment, RHMS when incorporated will aid the healthcare professionals to deliver personalized treatment for the patients. In this study, IoMT enabled Continuous Glucose Monitoring (CGM) system enables continuous automated monitoring of blood glucose(BG) levels of the patients at regular intervals. This reduces the burden of measuring the BG levels and recording the results manually for further follow up. This continuous monitoring environment can send alerts to the patients and or to the clinicians when the BG levels are out of the normal range. This CGM system will be beneficial for the clinicians to alert Individuals about the upcoming health complications and recommend quality lifestyle for them to stay healthy. Yellow Springs Instrument’s (YSI) BG readings are used to compare the proposed CGM system’s performance in terms of Mean Absolute Relative Difference (MARD). Additionally, the challenges and threats associated with constructing the IoMT ecosystem were highlighted, as well as potential solutions.","PeriodicalId":60583,"journal":{"name":"物联网技术","volume":"30 1","pages":"888-896"},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74200316","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}
Earlier, power consumption was very low, and people were also less aware of electronic devices. Most people prefer natural methods for cooking, washing, grinding, ironing clothes, and other tasks. Recently, power consumption is increasing as the number of consumers in the distribution system increases. AC, washing machines, fans, TVs, rice cookers, refrigerators, and other appliances were in high demand. When fans, TVs, cooking, gadgets, and washing machines are used during the day, the load requirement is higher than when they are used at night. As a result of the uncertainty in demand, power losses and low voltage will occur. The primary goal of this research work is to reduce distribution system power losses by optimizing the tapings of the distribution transformer using the PSO algorithm and also achieve power compensation by locating the DG and capacitor banks, and results are analyzed by using MATLAB software. The backward forward sweep technique has been adapted to identify voltage levels of buses in the system, and the proposed approach was then examined on the IEEE 15 bus system.
{"title":"Minimization of Power Losses in the Distribution System by Controlling Tap Changing Transformer using the PSO Algorithm","authors":"Chodagam Srinivas, V. Bhargavi, Nallagangula Srinu Babu, Paluri Harika, Pathula Kranthi","doi":"10.1109/IDCIoT56793.2023.10053479","DOIUrl":"https://doi.org/10.1109/IDCIoT56793.2023.10053479","url":null,"abstract":"Earlier, power consumption was very low, and people were also less aware of electronic devices. Most people prefer natural methods for cooking, washing, grinding, ironing clothes, and other tasks. Recently, power consumption is increasing as the number of consumers in the distribution system increases. AC, washing machines, fans, TVs, rice cookers, refrigerators, and other appliances were in high demand. When fans, TVs, cooking, gadgets, and washing machines are used during the day, the load requirement is higher than when they are used at night. As a result of the uncertainty in demand, power losses and low voltage will occur. The primary goal of this research work is to reduce distribution system power losses by optimizing the tapings of the distribution transformer using the PSO algorithm and also achieve power compensation by locating the DG and capacitor banks, and results are analyzed by using MATLAB software. The backward forward sweep technique has been adapted to identify voltage levels of buses in the system, and the proposed approach was then examined on the IEEE 15 bus system.","PeriodicalId":60583,"journal":{"name":"物联网技术","volume":"182 1","pages":"740-745"},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77588565","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 : 2023-01-05DOI: 10.1109/IDCIoT56793.2023.10053424
Suresh Babu Dasari, V. Vandana, A. Bhharathee
Everybody goes on a vacation to take a break from their busy life but planning for these vacations consumes a lot of time. One of the main reasons for this is the lack of platforms that provide personalized information for vacation planning. Users must individually search for good-reviewed restaurants and hotels and plan an appropriate path to visit top tourist places according to their budget. In this project, a user's distinct preferences will be considered to guide them in recommending the route according to their interests. This study has used a hybrid model as the features planned to include are quite complex. The model built is trained on the basis of features that are derived from the collected data. As a result, the model emerged and can successfully be used to create numerous suggestions for consumers. For this Hybrid model, URLs of different tourist places are gathered from websites like TripAdvisor, and Holidify to gather information about the Point of interest using Web scraping. Here, Gaussian Mixture Model (GMM) algorithm and K-Means algorithm are applied to group the nearby attractions and hotels to understand these algorithms better.
{"title":"Smart Travel Planner using Hybrid Model","authors":"Suresh Babu Dasari, V. Vandana, A. Bhharathee","doi":"10.1109/IDCIoT56793.2023.10053424","DOIUrl":"https://doi.org/10.1109/IDCIoT56793.2023.10053424","url":null,"abstract":"Everybody goes on a vacation to take a break from their busy life but planning for these vacations consumes a lot of time. One of the main reasons for this is the lack of platforms that provide personalized information for vacation planning. Users must individually search for good-reviewed restaurants and hotels and plan an appropriate path to visit top tourist places according to their budget. In this project, a user's distinct preferences will be considered to guide them in recommending the route according to their interests. This study has used a hybrid model as the features planned to include are quite complex. The model built is trained on the basis of features that are derived from the collected data. As a result, the model emerged and can successfully be used to create numerous suggestions for consumers. For this Hybrid model, URLs of different tourist places are gathered from websites like TripAdvisor, and Holidify to gather information about the Point of interest using Web scraping. Here, Gaussian Mixture Model (GMM) algorithm and K-Means algorithm are applied to group the nearby attractions and hotels to understand these algorithms better.","PeriodicalId":60583,"journal":{"name":"物联网技术","volume":"289 1","pages":"647-652"},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77863871","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 : 2023-01-05DOI: 10.1109/IDCIoT56793.2023.10053389
Eman Shaikh, Nazeeruddin Mohammad, Abdulrahman Al-Ali, Shahabuddin Muhammad
Recent years have observed a major rise in the utilization of Digital Twin (DT) technology. In general, a DT is described as a digital counterpart of a given physical entity that is obtained through the different stages of the DT development process: DT data collection, DT data transmission, DT generation, and DT visualization. However, these stages can be susceptible to various security attacks. This paper investigates the major security attacks that can occur throughout the stages of DT development and provides relevant countermeasures to counter these attacks. A use case of DT in the healthcare domain as an in-patient monitoring system is presented to provide a better understanding of the potential DT security attacks. Furthermore, to evaluate the security of DT, a security analysis approach in the form of a probabilistic model checking (PMC) is presented.
{"title":"A Probabilistic Model Checking (PMC) Approach to Solve Security Issues in Digital Twin (DT)","authors":"Eman Shaikh, Nazeeruddin Mohammad, Abdulrahman Al-Ali, Shahabuddin Muhammad","doi":"10.1109/IDCIoT56793.2023.10053389","DOIUrl":"https://doi.org/10.1109/IDCIoT56793.2023.10053389","url":null,"abstract":"Recent years have observed a major rise in the utilization of Digital Twin (DT) technology. In general, a DT is described as a digital counterpart of a given physical entity that is obtained through the different stages of the DT development process: DT data collection, DT data transmission, DT generation, and DT visualization. However, these stages can be susceptible to various security attacks. This paper investigates the major security attacks that can occur throughout the stages of DT development and provides relevant countermeasures to counter these attacks. A use case of DT in the healthcare domain as an in-patient monitoring system is presented to provide a better understanding of the potential DT security attacks. Furthermore, to evaluate the security of DT, a security analysis approach in the form of a probabilistic model checking (PMC) is presented.","PeriodicalId":60583,"journal":{"name":"物联网技术","volume":"79 1","pages":"192-197"},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81423513","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}
This article implemented a hardware structure of a single-phase inverter with Arduino with hybrid energy sources, this inverter generates an Ac square wave using PWM generated by an Arduino microcontroller, and this Arduino helps in generating triggering pulses for MOSFETS switching, thereby AC voltage is developed, taking this as a reference. This paper simulated a renewable energy source fed multilevel inverter, which consists of the windmill, and PV cell as renewable sources, as there is a lot of change in power generation in the current world there is a need of using renewable energy sources for power generation, and a 9-level inverter for power conversation, the 9 level inverter is used for maximizing the output power to a higher extinct when compared to other inverters, the energy generated by the renewable energy source is stored in a battery, and this circuit is parallelly connected to the inverter for the AC power generation.
{"title":"Renewable Energy Source Fed Multilevel Inverter","authors":"Ankanthi Manjula, Manish Palepu, Naveen Karnekanti, Saikiranreddy Gogireddy, Chandan Kumar Chiguru","doi":"10.1109/IDCIoT56793.2023.10053486","DOIUrl":"https://doi.org/10.1109/IDCIoT56793.2023.10053486","url":null,"abstract":"This article implemented a hardware structure of a single-phase inverter with Arduino with hybrid energy sources, this inverter generates an Ac square wave using PWM generated by an Arduino microcontroller, and this Arduino helps in generating triggering pulses for MOSFETS switching, thereby AC voltage is developed, taking this as a reference. This paper simulated a renewable energy source fed multilevel inverter, which consists of the windmill, and PV cell as renewable sources, as there is a lot of change in power generation in the current world there is a need of using renewable energy sources for power generation, and a 9-level inverter for power conversation, the 9 level inverter is used for maximizing the output power to a higher extinct when compared to other inverters, the energy generated by the renewable energy source is stored in a battery, and this circuit is parallelly connected to the inverter for the AC power generation.","PeriodicalId":60583,"journal":{"name":"物联网技术","volume":"114 1","pages":"786-791"},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81521677","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 : 2023-01-05DOI: 10.1109/IDCIoT56793.2023.10053449
Vivek Kumar M, Ram Sundar. G, M. K, K. C, Soumiya. S
The most important prerequisite for providing advanced patient care in hospitals is hydration and electrolyte assessment and management. Electrolyte levels are manually checked in almost all hospitals. The patient's mortality could result from an incorrect bottle replacement. When the nurse failed to notice the notification or forget to replace the bottle once it gets emptied, there will be a high risk of reverse flow of blood. When the air gets locked up or the bottle gets emptier, it may lead to death of the patient. The proposed system monitors the entire process automatically. The setup also intimates the user through alert messages and notification at times. A warning popup notification is sent to the in charge/nurse and the caregivers based on the electrolyte levels with a unique key (room id & patient id). If they failed to notice the message and replace it, the smart tuning mechanism will block the fluid path and eliminates the reverse blood flow and the whole process stops automatically. Hence, there will not be any reverse blood flow or air bubble forming, which leads to death.
{"title":"IoT based Smart Intravenous Fluids (IV) Drip Monitoring and Reverse Blood Flow Prevention System","authors":"Vivek Kumar M, Ram Sundar. G, M. K, K. C, Soumiya. S","doi":"10.1109/IDCIoT56793.2023.10053449","DOIUrl":"https://doi.org/10.1109/IDCIoT56793.2023.10053449","url":null,"abstract":"The most important prerequisite for providing advanced patient care in hospitals is hydration and electrolyte assessment and management. Electrolyte levels are manually checked in almost all hospitals. The patient's mortality could result from an incorrect bottle replacement. When the nurse failed to notice the notification or forget to replace the bottle once it gets emptied, there will be a high risk of reverse flow of blood. When the air gets locked up or the bottle gets emptier, it may lead to death of the patient. The proposed system monitors the entire process automatically. The setup also intimates the user through alert messages and notification at times. A warning popup notification is sent to the in charge/nurse and the caregivers based on the electrolyte levels with a unique key (room id & patient id). If they failed to notice the message and replace it, the smart tuning mechanism will block the fluid path and eliminates the reverse blood flow and the whole process stops automatically. Hence, there will not be any reverse blood flow or air bubble forming, which leads to death.","PeriodicalId":60583,"journal":{"name":"物联网技术","volume":"21 1","pages":"16-20"},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85282172","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 : 2023-01-05DOI: 10.1109/IDCIoT56793.2023.10053452
Harsh B. Thummar, Jijesh M. Jangid, Ashish Patel
Current billing system requires a lot of manpower to monitor energy consumption from home to home. This research work is mainly focused on self-metering and smart monitoring systems with the help of the IoT cloud. The proposed system is designed and implemented on the printed circuit board. The total energy consumption and tariff can be calculated with the help of voltage-current sensors and Arduino. SD card module is also included with Arduino to gather required consumption data and further analysis in .csv format. In addition, the Serial communication protocol is also included to send the calculated energy data and price to Wi-Fi Module ESP8266. This data will be monitored in real-time through the Adafruit IoT cloud platform, which uses MQTT protocol and can be easily programmed into ESP8266. LCD is used to display energy units and prices. Apart from that if energy usage reaches beyond the monthly threshold value, then system will automatically send a warning SMS through the IFTTT protocol which can easily interact with the cloud and actions can be taken by the user.
{"title":"E-Billing System using Smart Energy Meter for Domestic Application","authors":"Harsh B. Thummar, Jijesh M. Jangid, Ashish Patel","doi":"10.1109/IDCIoT56793.2023.10053452","DOIUrl":"https://doi.org/10.1109/IDCIoT56793.2023.10053452","url":null,"abstract":"Current billing system requires a lot of manpower to monitor energy consumption from home to home. This research work is mainly focused on self-metering and smart monitoring systems with the help of the IoT cloud. The proposed system is designed and implemented on the printed circuit board. The total energy consumption and tariff can be calculated with the help of voltage-current sensors and Arduino. SD card module is also included with Arduino to gather required consumption data and further analysis in .csv format. In addition, the Serial communication protocol is also included to send the calculated energy data and price to Wi-Fi Module ESP8266. This data will be monitored in real-time through the Adafruit IoT cloud platform, which uses MQTT protocol and can be easily programmed into ESP8266. LCD is used to display energy units and prices. Apart from that if energy usage reaches beyond the monthly threshold value, then system will automatically send a warning SMS through the IFTTT protocol which can easily interact with the cloud and actions can be taken by the user.","PeriodicalId":60583,"journal":{"name":"物联网技术","volume":"31 1","pages":"695-701"},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80817244","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 : 2023-01-05DOI: 10.1109/IDCIoT56793.2023.10053458
S. Parthasarathy, Vaishnavi Jayaraman, Jane Preetha Princy R
cardiovascular diseases rank among the top causes of death around the world. Anticipating cardiovascular illness is a major challenge for the healthcare industry. It has been demonstrated that the implementation of Machine Learning (ML), Artificial Intelligence (AI), and data science may effectively aid in decision-making and prediction using the huge quantities of data created by the healthcare industry. The medical field has profited immensely from the use of algorithms and correlation approaches for identifying patterns in the vitals. An imbalanced heart failure data set was analyzed using Logistic Regression, Naive Bayes, Decision Tree, AdaBoost, Random Forest, and XGBoost (XGB). The univariate feature selection model f_classif was used to identify the most relevant characteristics after the dataset was normalized using the Z-score method. This dataset was then balanced by oversampling and undersampling with SMOTE-ENN. Compared to the other ML models applied to the balanced dataset, XGBoost achieved higher levels of accuracy (97%), precision (96%), recall (96%), and F1-score (96%) in classifying heart failure.
{"title":"Predicting Heart Failure using SMOTE-ENN-XGBoost","authors":"S. Parthasarathy, Vaishnavi Jayaraman, Jane Preetha Princy R","doi":"10.1109/IDCIoT56793.2023.10053458","DOIUrl":"https://doi.org/10.1109/IDCIoT56793.2023.10053458","url":null,"abstract":"cardiovascular diseases rank among the top causes of death around the world. Anticipating cardiovascular illness is a major challenge for the healthcare industry. It has been demonstrated that the implementation of Machine Learning (ML), Artificial Intelligence (AI), and data science may effectively aid in decision-making and prediction using the huge quantities of data created by the healthcare industry. The medical field has profited immensely from the use of algorithms and correlation approaches for identifying patterns in the vitals. An imbalanced heart failure data set was analyzed using Logistic Regression, Naive Bayes, Decision Tree, AdaBoost, Random Forest, and XGBoost (XGB). The univariate feature selection model f_classif was used to identify the most relevant characteristics after the dataset was normalized using the Z-score method. This dataset was then balanced by oversampling and undersampling with SMOTE-ENN. Compared to the other ML models applied to the balanced dataset, XGBoost achieved higher levels of accuracy (97%), precision (96%), recall (96%), and F1-score (96%) in classifying heart failure.","PeriodicalId":60583,"journal":{"name":"物联网技术","volume":"145 1","pages":"661-666"},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79942158","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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