Pub Date : 2023-01-07DOI: 10.1109/ICREST57604.2023.10070055
Muhtasim Firoz, Rethwan Faiz, Nuzat Naury Alam, M. H. Imam
Electrocardiograms, or ECGs, are used by medical professionals to identify whether or not a patient has been experiencing myocardial infarction. In the medical field, myocardial injury detection procedures are not usually automated. A deep learning-based model can automate this manual procedure. The proposed model is a deep learning-based predictive model capable of detecting myocardial infarction from 15 ECG leads. The PTB database was used in this model. This database contains data from 15 ECG leads, which include 12 standard leads and 3 frank leads. The objective of the work is to identify MI with high and stable accuracy, F1 score, precision, and recall using an imbalanced PTB dataset. The proposed model is a combination of the dilated CNN(ConvNetQuake) and an LSTM network. The validation F1 score, precision, recall, and accuracy for the model are 1.0, 1.0, 1.0 and 100%, respectively. Regarding the test set, the F1 score, precision, recall, and accuracy for the model are 0.94, 0.88, 1.0 and 97.7%, respectively.
{"title":"Detection of Myocardial Infarction Using Hybrid CNN-LSTM Model","authors":"Muhtasim Firoz, Rethwan Faiz, Nuzat Naury Alam, M. H. Imam","doi":"10.1109/ICREST57604.2023.10070055","DOIUrl":"https://doi.org/10.1109/ICREST57604.2023.10070055","url":null,"abstract":"Electrocardiograms, or ECGs, are used by medical professionals to identify whether or not a patient has been experiencing myocardial infarction. In the medical field, myocardial injury detection procedures are not usually automated. A deep learning-based model can automate this manual procedure. The proposed model is a deep learning-based predictive model capable of detecting myocardial infarction from 15 ECG leads. The PTB database was used in this model. This database contains data from 15 ECG leads, which include 12 standard leads and 3 frank leads. The objective of the work is to identify MI with high and stable accuracy, F1 score, precision, and recall using an imbalanced PTB dataset. The proposed model is a combination of the dilated CNN(ConvNetQuake) and an LSTM network. The validation F1 score, precision, recall, and accuracy for the model are 1.0, 1.0, 1.0 and 100%, respectively. Regarding the test set, the F1 score, precision, recall, and accuracy for the model are 0.94, 0.88, 1.0 and 97.7%, respectively.","PeriodicalId":389360,"journal":{"name":"2023 3rd International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122775912","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 : 2023-01-07DOI: 10.1109/ICREST57604.2023.10070065
K. M. Rayhan, Shuvo Dip Roy, Md. Fahimul Haque Sadid, Kazi Firoz Ahmed, A. Shatil
The power system's reliability dramatically depends on the high voltage line insulators. However, the surface of these insulators is frequently damaged because of the outdoor environment, which includes complicated landforms and unpredictable weather. Damage to the insulator's surface can lead to short circuits, permanent damage to the transmission line, and even blackouts. To deliver quality service, it is essential to keep track of the condition of these insulators. As traditional fault-detection systems have become more time- and labor-intensive, a YOLOv4-based detection approach is proposed here to achieve fast and precise damage detection and classification of line insulators. YOLOv4 is a Deep Learning (DL) algorithm model that operates on the darknet framework. The research findings show that 97.711% is the maximum average, depending on detecting YOLOv4 for insulators. Insulator damage has a maximum AP value of 98.17%, and discolored Insulator has a maximum AP value of 97.07%. When the system is trained on the insulator data set, the overall m-AP (mean Average Precision) value is 97.65%. The detecting speed in virtual environments for YOLOv4s is 43 FPS, and it has a greater detection rate.
电力系统的可靠性在很大程度上取决于高压线路绝缘子。然而，由于室外环境，包括复杂的地形和不可预测的天气，这些绝缘子的表面经常损坏。绝缘体表面的损坏会导致短路，对输电线路造成永久性损坏，甚至停电。为了提供高质量的服务，跟踪这些绝缘子的状况是至关重要的。针对传统的线路绝缘子故障检测系统耗时耗力大的问题，本文提出了一种基于yolov4的线路绝缘子故障检测方法，以实现线路绝缘子的快速、精确的损伤检测和分类。YOLOv4是一种运行在暗网框架上的深度学习(DL)算法模型。研究结果表明，97.711%为最大平均值，取决于对绝缘子的YOLOv4检测。绝缘子损坏的最大AP值为98.17%，绝缘子变色的最大AP值为97.07%。当系统在绝缘子数据集上进行训练时，总体m-AP (mean Average Precision)值为97.65%。YOLOv4s在虚拟环境下的检测速度为43 FPS，具有更高的检测率。
{"title":"Surface Damage Detection of Line Insulators Using Deep Learning Algorithms to Avoid Insulation Failure","authors":"K. M. Rayhan, Shuvo Dip Roy, Md. Fahimul Haque Sadid, Kazi Firoz Ahmed, A. Shatil","doi":"10.1109/ICREST57604.2023.10070065","DOIUrl":"https://doi.org/10.1109/ICREST57604.2023.10070065","url":null,"abstract":"The power system's reliability dramatically depends on the high voltage line insulators. However, the surface of these insulators is frequently damaged because of the outdoor environment, which includes complicated landforms and unpredictable weather. Damage to the insulator's surface can lead to short circuits, permanent damage to the transmission line, and even blackouts. To deliver quality service, it is essential to keep track of the condition of these insulators. As traditional fault-detection systems have become more time- and labor-intensive, a YOLOv4-based detection approach is proposed here to achieve fast and precise damage detection and classification of line insulators. YOLOv4 is a Deep Learning (DL) algorithm model that operates on the darknet framework. The research findings show that 97.711% is the maximum average, depending on detecting YOLOv4 for insulators. Insulator damage has a maximum AP value of 98.17%, and discolored Insulator has a maximum AP value of 97.07%. When the system is trained on the insulator data set, the overall m-AP (mean Average Precision) value is 97.65%. The detecting speed in virtual environments for YOLOv4s is 43 FPS, and it has a greater detection rate.","PeriodicalId":389360,"journal":{"name":"2023 3rd International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128957524","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 : 2023-01-07DOI: 10.1109/ICREST57604.2023.10070041
M. Hasan, Saikat Ray, Sujana Sarkar, Most. Labonna Akter, M. A. Shawon
The history of the medical robot is not very far from the first experiment in the 1980s. Nowadays robot in the medical sector plays a vital role in monitoring patient's health condition from distance. This paper aimed at developing an auxiliary medical solution that could provide a wide range of non-invasive diagnoses carried out by an automated robot whose motion can also be controlled manually using either a mobile application or voice command. The authors also incorporate modern features of video conferences and automated patient data management systems using the Internet of Things (IoT) which eventually facilitate medical practitioners in proper investigation from distance. The results of the clinical trial among 6 persons indicated that the robot could measure different health parameters properly using the proposed non-invasive method. The non-invasive results are verified by standard testing equipment and conventional clinical investigation and are also presented in this paper. The developed medical robot having a wide range of functionality could play a significant role in reducing human workload and ensuring timely medical assistance during a challenging crisis pandemic period like COVID-19.
{"title":"DESIGN AND DEVELOPMENT OF ROBO MEDICAL ASSISTANT","authors":"M. Hasan, Saikat Ray, Sujana Sarkar, Most. Labonna Akter, M. A. Shawon","doi":"10.1109/ICREST57604.2023.10070041","DOIUrl":"https://doi.org/10.1109/ICREST57604.2023.10070041","url":null,"abstract":"The history of the medical robot is not very far from the first experiment in the 1980s. Nowadays robot in the medical sector plays a vital role in monitoring patient's health condition from distance. This paper aimed at developing an auxiliary medical solution that could provide a wide range of non-invasive diagnoses carried out by an automated robot whose motion can also be controlled manually using either a mobile application or voice command. The authors also incorporate modern features of video conferences and automated patient data management systems using the Internet of Things (IoT) which eventually facilitate medical practitioners in proper investigation from distance. The results of the clinical trial among 6 persons indicated that the robot could measure different health parameters properly using the proposed non-invasive method. The non-invasive results are verified by standard testing equipment and conventional clinical investigation and are also presented in this paper. The developed medical robot having a wide range of functionality could play a significant role in reducing human workload and ensuring timely medical assistance during a challenging crisis pandemic period like COVID-19.","PeriodicalId":389360,"journal":{"name":"2023 3rd International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121361936","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 : 2023-01-07DOI: 10.1109/ICREST57604.2023.10070062
Md. Iftadul Islam Sakib, Mohammad Rejwan Uddin, Khan Farhan Ibne Faruque, Abdullah Al Mamun, K. M. Salim
This article introduces a grid-tied, single-phase, high-frequency-link photovoltaic inverter (GTI). The signal for the sinusoidal pulse width modulation (SPWM) control of a typical GTI must be produced by a highly advanced digital signal processor. In this paper, various boost converter's duties include and analyze to boost the dc voltage and preserving the maximum power point tracking (MPPT) algorithm. The main functions of the inverter are to synchronize the grid and to invert the increased dc voltage at a high switching frequency. The inverter power density is increased by both circuits' high frequency (HF) operation. No bulky interstage transformer is needed for the proposed inverter. As a result, the size and dependability of the system are increased while the magnetizing and copper losses are decreased. Through calculations and prototype trials with a photovoltaic (PV) array, various operational scenarios were examined to confirm the proposed system's performance.
{"title":"Different Converter Integration and Performance Assessment of a Multi-Stage Transformer Less Grid Tie Inverter Using Thin Film PV Array","authors":"Md. Iftadul Islam Sakib, Mohammad Rejwan Uddin, Khan Farhan Ibne Faruque, Abdullah Al Mamun, K. M. Salim","doi":"10.1109/ICREST57604.2023.10070062","DOIUrl":"https://doi.org/10.1109/ICREST57604.2023.10070062","url":null,"abstract":"This article introduces a grid-tied, single-phase, high-frequency-link photovoltaic inverter (GTI). The signal for the sinusoidal pulse width modulation (SPWM) control of a typical GTI must be produced by a highly advanced digital signal processor. In this paper, various boost converter's duties include and analyze to boost the dc voltage and preserving the maximum power point tracking (MPPT) algorithm. The main functions of the inverter are to synchronize the grid and to invert the increased dc voltage at a high switching frequency. The inverter power density is increased by both circuits' high frequency (HF) operation. No bulky interstage transformer is needed for the proposed inverter. As a result, the size and dependability of the system are increased while the magnetizing and copper losses are decreased. Through calculations and prototype trials with a photovoltaic (PV) array, various operational scenarios were examined to confirm the proposed system's performance.","PeriodicalId":389360,"journal":{"name":"2023 3rd International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131181064","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 : 2023-01-07DOI: 10.1109/ICREST57604.2023.10070078
Md. Shahariar Nafiz, S. Das, Md. Kishor Morol, Abdullah Al Juabir, Dipannyta Nandi
Nowadays, proper urban waste management is one the biggest concerns for maintaining a green and clean environment. An automatic waste segregation system can be a viable solution to improve the sustainability of the country and to boost up the circular economy. This paper proposes a machine to segregate the waste into the different parts with the help of smart object detection algorithm using ConvoWaste in the field of Deep Convolutional Neural Network (DCNN), and image processing technique. In this paper, the deep learning and image processing techniques are applied to classify the waste precisely and the detected waste is placed inside the corresponding bins with the help of a servo motor-based system. This machine has the provision to notify the responsible authority regarding the waste level of the bins and the time to trash out the bins filled with garbage by using the ultrasonic sensors placed in each bin and the dual-band GSM-based communication technology. The entire system is controlled remotely through an android app in order to dump the separated waste in a desired place by its automation properties. The use of this system can aid the process of recycling resources that were initially destined to become waste, utilizing natural resources and turning these resources back into the usable products. Thus, the system helps to fulfill the criteria of circular economy through the resource optimization and extraction. Finally, the system is made to provide the services at a low cost with higher accuracy level in terms of the technological advancement in the field of Artificial Intelligence (AI). We have got 98% accuracy for our ConvoWaste deep learning model.
{"title":"ConvoWaste: An Automatic Waste Segregation Machine Using Deep Learning","authors":"Md. Shahariar Nafiz, S. Das, Md. Kishor Morol, Abdullah Al Juabir, Dipannyta Nandi","doi":"10.1109/ICREST57604.2023.10070078","DOIUrl":"https://doi.org/10.1109/ICREST57604.2023.10070078","url":null,"abstract":"Nowadays, proper urban waste management is one the biggest concerns for maintaining a green and clean environment. An automatic waste segregation system can be a viable solution to improve the sustainability of the country and to boost up the circular economy. This paper proposes a machine to segregate the waste into the different parts with the help of smart object detection algorithm using ConvoWaste in the field of Deep Convolutional Neural Network (DCNN), and image processing technique. In this paper, the deep learning and image processing techniques are applied to classify the waste precisely and the detected waste is placed inside the corresponding bins with the help of a servo motor-based system. This machine has the provision to notify the responsible authority regarding the waste level of the bins and the time to trash out the bins filled with garbage by using the ultrasonic sensors placed in each bin and the dual-band GSM-based communication technology. The entire system is controlled remotely through an android app in order to dump the separated waste in a desired place by its automation properties. The use of this system can aid the process of recycling resources that were initially destined to become waste, utilizing natural resources and turning these resources back into the usable products. Thus, the system helps to fulfill the criteria of circular economy through the resource optimization and extraction. Finally, the system is made to provide the services at a low cost with higher accuracy level in terms of the technological advancement in the field of Artificial Intelligence (AI). We have got 98% accuracy for our ConvoWaste deep learning model.","PeriodicalId":389360,"journal":{"name":"2023 3rd International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132705959","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 : 2023-01-07DOI: 10.1109/ICREST57604.2023.10070034
Ahmed Muntasir Anwar, Md. Rifat Hazari, M. Mannan
An essential instrument for the operation of a power system is to monitor and analyze the data to find the fault and rectify it before the System collapses completely. This paper intents to utilize the idea to create a control system that will fulfill three objectives, monitoring of vital parameters controlling the power distribution, outage management by fault detection based on the variation of voltage, frequency, and current & protection of the circuit against any significant incidents by isolating the load from utility and flagging the information through feedback to the utility authority. The method used in this project can provide necessary safety from total system outages by adequately monitoring the instant data and historic data, managing the outage system by detecting faults, and cutting loads required to avoid a widespread blackout of a power system. Implementation of the proposed project can solve the problem of system blackout due to overload, under/over voltage, or under/over frequency. This developed system can supply necessary timestamped monitored data that can be accessed remotely and can also archive to create a proper load profile to ultimately help the modeling of Load Forecasting for a smooth and economic grid operation and can be used for developing the Smart Grid network.
{"title":"Design and Implementation of IoT-Based Load Monitoring and Outage Management System","authors":"Ahmed Muntasir Anwar, Md. Rifat Hazari, M. Mannan","doi":"10.1109/ICREST57604.2023.10070034","DOIUrl":"https://doi.org/10.1109/ICREST57604.2023.10070034","url":null,"abstract":"An essential instrument for the operation of a power system is to monitor and analyze the data to find the fault and rectify it before the System collapses completely. This paper intents to utilize the idea to create a control system that will fulfill three objectives, monitoring of vital parameters controlling the power distribution, outage management by fault detection based on the variation of voltage, frequency, and current & protection of the circuit against any significant incidents by isolating the load from utility and flagging the information through feedback to the utility authority. The method used in this project can provide necessary safety from total system outages by adequately monitoring the instant data and historic data, managing the outage system by detecting faults, and cutting loads required to avoid a widespread blackout of a power system. Implementation of the proposed project can solve the problem of system blackout due to overload, under/over voltage, or under/over frequency. This developed system can supply necessary timestamped monitored data that can be accessed remotely and can also archive to create a proper load profile to ultimately help the modeling of Load Forecasting for a smooth and economic grid operation and can be used for developing the Smart Grid network.","PeriodicalId":389360,"journal":{"name":"2023 3rd International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123625903","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 : 2023-01-07DOI: 10.1109/ICREST57604.2023.10070039
Amit Datta, Md Monjurul Islam, Md. Sabbir Hassan, Kuasha Bosu Aka, Istiaque Ahamed, Abir Ahmed
Air pollution is the presence of contaminants or poisonous substances that interfere with human health or welfare or create destructive natural impacts. With the fast improvement of communication innovations, remote sensing technology, and air pollution monitoring systems, it is possible to check the air concentration and take appropriate action. In this paper, a system is developed that can monitor different parameters, like O3, NO2, CO2, and temperature in real time. The control system converts all the data to human-readable values. With the development of a communication system, all data is stored in a cloud database. A decision-making calculation algorithm is developed using advanced technology like cloud computing. Further, a visual platform was created to allow the user to access the data remotely.
{"title":"IoT Based Air Quality and Noise Pollution Monitoring System","authors":"Amit Datta, Md Monjurul Islam, Md. Sabbir Hassan, Kuasha Bosu Aka, Istiaque Ahamed, Abir Ahmed","doi":"10.1109/ICREST57604.2023.10070039","DOIUrl":"https://doi.org/10.1109/ICREST57604.2023.10070039","url":null,"abstract":"Air pollution is the presence of contaminants or poisonous substances that interfere with human health or welfare or create destructive natural impacts. With the fast improvement of communication innovations, remote sensing technology, and air pollution monitoring systems, it is possible to check the air concentration and take appropriate action. In this paper, a system is developed that can monitor different parameters, like O3, NO2, CO2, and temperature in real time. The control system converts all the data to human-readable values. With the development of a communication system, all data is stored in a cloud database. A decision-making calculation algorithm is developed using advanced technology like cloud computing. Further, a visual platform was created to allow the user to access the data remotely.","PeriodicalId":389360,"journal":{"name":"2023 3rd International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121120044","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 : 2023-01-07DOI: 10.1109/ICREST57604.2023.10070048
Shobhasish Halder Shovo, Sudipta Karmarker
The drinking water crisis is one of the prime issues in all over the world. Almost half of the populations of the world isolated from this blessing. Insufficiency of electricity plays a great role in their situations, as without electricity we cannot run a pump. Renewable energy is one of the suitable answers to solve the problem. The most effective resources of renewable energy are solar energy, which could solve this crisis. This research presents a performance analysis of the solar-based water pump controlling system and water quality measuring system using arduino mega. The main objective of this research is to automatically control the water pump and single-axis tracking for solar. Besides, the pH and turbidity of the reserve tank water show into the liquid crystal display (LCD) by using arduino's command. If the turbidity sensor senses the water is polluted then the automatically send the tank's water to the filter for purifying and if the pH level of the water is high or low, the device automatically stops sending the water to the supply. In both cases turbidity low, pH high, and low), the GSM module sends a warning notification to the selected cellular device by using the arduino's command. This work is divided into two parts hardware and software systems. In the hardware part, four light dependent resistors (LDR) are used to sense the maximum light side from the sun. One linear actuator used to move the solar panel to the maximum light source location perceived by the LDRs. In the software part, the code is written by using C programming language and has targeted to the arduino mega controller. In this idea, arduino mega controls the whole thing. An automatic water pump can reduce the loss of pure water.
{"title":"Solar Based Smart Water Pump Control with Turbidity and pH Measuring System","authors":"Shobhasish Halder Shovo, Sudipta Karmarker","doi":"10.1109/ICREST57604.2023.10070048","DOIUrl":"https://doi.org/10.1109/ICREST57604.2023.10070048","url":null,"abstract":"The drinking water crisis is one of the prime issues in all over the world. Almost half of the populations of the world isolated from this blessing. Insufficiency of electricity plays a great role in their situations, as without electricity we cannot run a pump. Renewable energy is one of the suitable answers to solve the problem. The most effective resources of renewable energy are solar energy, which could solve this crisis. This research presents a performance analysis of the solar-based water pump controlling system and water quality measuring system using arduino mega. The main objective of this research is to automatically control the water pump and single-axis tracking for solar. Besides, the pH and turbidity of the reserve tank water show into the liquid crystal display (LCD) by using arduino's command. If the turbidity sensor senses the water is polluted then the automatically send the tank's water to the filter for purifying and if the pH level of the water is high or low, the device automatically stops sending the water to the supply. In both cases turbidity low, pH high, and low), the GSM module sends a warning notification to the selected cellular device by using the arduino's command. This work is divided into two parts hardware and software systems. In the hardware part, four light dependent resistors (LDR) are used to sense the maximum light side from the sun. One linear actuator used to move the solar panel to the maximum light source location perceived by the LDRs. In the software part, the code is written by using C programming language and has targeted to the arduino mega controller. In this idea, arduino mega controls the whole thing. An automatic water pump can reduce the loss of pure water.","PeriodicalId":389360,"journal":{"name":"2023 3rd International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125839487","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 : 2023-01-07DOI: 10.1109/ICREST57604.2023.10070066
Nurjahan Amin Nuha, Md. Tanbir Siddik Injam, N. Chowdhury
In recent years, power generation based on renewable resources has grown increasingly significant as well as ecologically beneficial. This paper analyzed the viability of a hybrid renewable energy system on the isolated Bangladeshi island of Bhasan Char, which has been selected for the resettling of Rohingyas. The hybrid systems were composed of solar energy, wind energy, biomass, storage, and converter. HOMER software is used to simulate and analyze the proposed system in terms of Net Present Cost, Cost of Energy, annual electricity generation, etc. Among four major combinations of different renewable sources, PV-Biomass-Converter-Battery (PBCB) appeared to be the most reliable system in terms of Net Present Cost, Cost of Energy, and other factors. The proposed PV-Wind-Biomass-Converter-Battery (PWBCB) model generates 21.3% annually, with 51% of total production coming from biogas. It is possible to increase solar production by using a rooftop system. The proposed model can meet the demand of 145 kWh/day with a peak load of 17 kW, indicating the feasibility of power supply in the isolated region.
{"title":"Feasibility Analysis of Off-Grid Hybrid Renewable Energy for Rohingya Refugee in Bhasan Char","authors":"Nurjahan Amin Nuha, Md. Tanbir Siddik Injam, N. Chowdhury","doi":"10.1109/ICREST57604.2023.10070066","DOIUrl":"https://doi.org/10.1109/ICREST57604.2023.10070066","url":null,"abstract":"In recent years, power generation based on renewable resources has grown increasingly significant as well as ecologically beneficial. This paper analyzed the viability of a hybrid renewable energy system on the isolated Bangladeshi island of Bhasan Char, which has been selected for the resettling of Rohingyas. The hybrid systems were composed of solar energy, wind energy, biomass, storage, and converter. HOMER software is used to simulate and analyze the proposed system in terms of Net Present Cost, Cost of Energy, annual electricity generation, etc. Among four major combinations of different renewable sources, PV-Biomass-Converter-Battery (PBCB) appeared to be the most reliable system in terms of Net Present Cost, Cost of Energy, and other factors. The proposed PV-Wind-Biomass-Converter-Battery (PWBCB) model generates 21.3% annually, with 51% of total production coming from biogas. It is possible to increase solar production by using a rooftop system. The proposed model can meet the demand of 145 kWh/day with a peak load of 17 kW, indicating the feasibility of power supply in the isolated region.","PeriodicalId":389360,"journal":{"name":"2023 3rd International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114209473","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 : 2023-01-07DOI: 10.1109/ICREST57604.2023.10070040
Takia Ibnath, Ashim Dey
Face masks are considered protective equipment that has the ability to safeguard humans from vulnerable situations. Although there exists a wide range of masks specifically designed for diverse purposes, there is a terrible lack of concern regarding proper usage. Consequently, the generalization of their usage can cause many life-threatening problems. As a result, a system that can detect the type of face mask can play a life-saving role to ensure the proper usage of these safety gear. With this aim, a custom dataset was built by manually labeling face mask images which include 8 classes. Scratch CNN and four transfer learning models have been implemented and their performance was thoroughly evaluated and assessed on multiple criteria to select the best one. Based on the investigation, it is found that SSD MobNet V2 achieved the highest accuracy of 83%. The developed system takes real-time video stream input from the camera and can detect the type of mask in different conditions.
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