Pub Date : 2021-03-17DOI: 10.1109/INDIACom51348.2021.00111
Anup Palsokar, Yogesh Kurane, Pankai Raibagkar
With the help of active sensory organs viz. eyes, ears, nose, tongue and skin, living beings perceive the environment around them. Humans exhibit a sense of self learning since birth and the sensory organs play a vital role in the learning process. For those unfortunate, who lose any of the sensory capability, try to sense the environment through other sensory organs available. Such persons are called differently-abled. Those with loss of sight are called visually impaired. There are a few passive devices to augment the partially defunct senses such as spectacles, hearing aids etc. While these devices help boost existing senses they do very little for those with complete absence of the sense. Present day technological advances have opened a galore of possibilities in designing solutions to provide learning support to perceptually disabled. Multimedia computers and hand held devices can be effectively used to find new solutions. This paper presents a novel approach for the use of vibrations of a hand held mobile phone, as an alternative to vision in helping the visually impaired persons in perceiving things especially colours. The authors have developed an android mobile phone application to prototype the methodology to use mobile phone's motor as the source for vibration and mapping a vibratory pattern with colours. With mobile phones being widely used, the authors find this approach as a potential solution in designing applications to assist the visually impaired in their learning process.
{"title":"Methodology for Use of Mobile Phone Vibration as an Alternative to Vision in Perceiving Colours","authors":"Anup Palsokar, Yogesh Kurane, Pankai Raibagkar","doi":"10.1109/INDIACom51348.2021.00111","DOIUrl":"https://doi.org/10.1109/INDIACom51348.2021.00111","url":null,"abstract":"With the help of active sensory organs viz. eyes, ears, nose, tongue and skin, living beings perceive the environment around them. Humans exhibit a sense of self learning since birth and the sensory organs play a vital role in the learning process. For those unfortunate, who lose any of the sensory capability, try to sense the environment through other sensory organs available. Such persons are called differently-abled. Those with loss of sight are called visually impaired. There are a few passive devices to augment the partially defunct senses such as spectacles, hearing aids etc. While these devices help boost existing senses they do very little for those with complete absence of the sense. Present day technological advances have opened a galore of possibilities in designing solutions to provide learning support to perceptually disabled. Multimedia computers and hand held devices can be effectively used to find new solutions. This paper presents a novel approach for the use of vibrations of a hand held mobile phone, as an alternative to vision in helping the visually impaired persons in perceiving things especially colours. The authors have developed an android mobile phone application to prototype the methodology to use mobile phone's motor as the source for vibration and mapping a vibratory pattern with colours. With mobile phones being widely used, the authors find this approach as a potential solution in designing applications to assist the visually impaired in their learning process.","PeriodicalId":415594,"journal":{"name":"2021 8th International Conference on Computing for Sustainable Global Development (INDIACom)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127113026","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 : 2021-03-17DOI: 10.1109/INDIACom51348.2021.00146
Sachin Aggarwal, A. Shal
Today we are living in a world where technology is dominating every sector. The need of automation is increasing day by day and the way of working of the whole world is moving towards the automation of different tasks, which can be done with expert knowledge without any need for human efforts. Due to this, the electricity demand is increasing, but this includes a lot of wastage of electricity that can be saved. The problem which we have identified here is wastage of electricity and to solve this problem we simply need a system which can be used for monitoring the usage of electricity. At first place, this problem looks very simple, and it seems it can be solved easily by some manual work done by a human but, this problem is very complex in reality as the consumer is not able to identify the exact point where electricity is being wasted or else it will be identified once electricity is already wasted which is of no use. These traditional systems are not efficient enough as they cannot identify a potential electricity wastage in advance, for example, if we charge mobile and we forget to turn it off then the charger will consume electricity for several hours and the wastage of electricity will be identified when we turn off charging. To solve these problems many models have been proposed by so many researchers that are BP Neural Network model, EPSO-BP neural network model and there are many more models that were used to solve this problem. The working and drawbacks of previously proposed models will be discussed further in the related work section of this paper. To solve this problem in this paper we have proposed a model that includes 3 sections. In the first section, we have created an IoT based device to measure and store the electricity usage of each appliance. In the second section, we have used the LSTM version of RNN which is very accurate and efficient to create a model that can work in real-time with very high accuracy. In the last section, this paper includes a web app as the frontend of this whole work done in previous sections.
{"title":"Automated Monitoring of Electricity Consumption Using LSTM-RNN and IoT","authors":"Sachin Aggarwal, A. Shal","doi":"10.1109/INDIACom51348.2021.00146","DOIUrl":"https://doi.org/10.1109/INDIACom51348.2021.00146","url":null,"abstract":"Today we are living in a world where technology is dominating every sector. The need of automation is increasing day by day and the way of working of the whole world is moving towards the automation of different tasks, which can be done with expert knowledge without any need for human efforts. Due to this, the electricity demand is increasing, but this includes a lot of wastage of electricity that can be saved. The problem which we have identified here is wastage of electricity and to solve this problem we simply need a system which can be used for monitoring the usage of electricity. At first place, this problem looks very simple, and it seems it can be solved easily by some manual work done by a human but, this problem is very complex in reality as the consumer is not able to identify the exact point where electricity is being wasted or else it will be identified once electricity is already wasted which is of no use. These traditional systems are not efficient enough as they cannot identify a potential electricity wastage in advance, for example, if we charge mobile and we forget to turn it off then the charger will consume electricity for several hours and the wastage of electricity will be identified when we turn off charging. To solve these problems many models have been proposed by so many researchers that are BP Neural Network model, EPSO-BP neural network model and there are many more models that were used to solve this problem. The working and drawbacks of previously proposed models will be discussed further in the related work section of this paper. To solve this problem in this paper we have proposed a model that includes 3 sections. In the first section, we have created an IoT based device to measure and store the electricity usage of each appliance. In the second section, we have used the LSTM version of RNN which is very accurate and efficient to create a model that can work in real-time with very high accuracy. In the last section, this paper includes a web app as the frontend of this whole work done in previous sections.","PeriodicalId":415594,"journal":{"name":"2021 8th International Conference on Computing for Sustainable Global Development (INDIACom)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132281143","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 : 2021-03-17DOI: 10.1109/INDIACom51348.2021.00121
Aman Malhotra, V. Jagannath, Prabhat Kumar, Sahil Sanil, J. Vighneswar, Advay S Pethakar, M. Sangeetha
Soft robots being one of the most diverse fields in robotics, these robots are robust, flexible and allow for a highly diverse field of implementation and movement. The property to withstand force and to perform actions The major problem with wheeled bots and bipeds is that they are not versatile enough to adapt and work. The major problem with other soft robots is that they require external supply and external wiring which strains the motion and strains the path of the robot while functioning. This not only makes the robot bounded but also makes it restrained to a standard structure. The motion and path planning of the robot is constrained because of the wires. like walking and moving are one of the key features that can be seen in all these robots. The major advantage of these robots includes versatile design and multi-terrain property. The motion and movement of these robots are usually actuated using actuators and motion controllers. Major design implementation and major functionality added to all these actuators is related with the type of motion it needs to perform. The proposed design is solving the problem of linear motion and linear motion underwater and on the ground.
{"title":"Design, Fabrication & Control of 4-Arm Soft Robot for Terrestrial and Underwater Locomotion","authors":"Aman Malhotra, V. Jagannath, Prabhat Kumar, Sahil Sanil, J. Vighneswar, Advay S Pethakar, M. Sangeetha","doi":"10.1109/INDIACom51348.2021.00121","DOIUrl":"https://doi.org/10.1109/INDIACom51348.2021.00121","url":null,"abstract":"Soft robots being one of the most diverse fields in robotics, these robots are robust, flexible and allow for a highly diverse field of implementation and movement. The property to withstand force and to perform actions The major problem with wheeled bots and bipeds is that they are not versatile enough to adapt and work. The major problem with other soft robots is that they require external supply and external wiring which strains the motion and strains the path of the robot while functioning. This not only makes the robot bounded but also makes it restrained to a standard structure. The motion and path planning of the robot is constrained because of the wires. like walking and moving are one of the key features that can be seen in all these robots. The major advantage of these robots includes versatile design and multi-terrain property. The motion and movement of these robots are usually actuated using actuators and motion controllers. Major design implementation and major functionality added to all these actuators is related with the type of motion it needs to perform. The proposed design is solving the problem of linear motion and linear motion underwater and on the ground.","PeriodicalId":415594,"journal":{"name":"2021 8th International Conference on Computing for Sustainable Global Development (INDIACom)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130530853","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 : 2021-03-17DOI: 10.1109/INDIACom51348.2021.00040
Z. Haq, Z. Jaffery
The classification of fruits into various classes is becoming inherent to the food processing industry. This paper presents a simulation analysis of effect of activation functions: ReLu, Softmax, sigmoid, and Softplus on the accuracy and latency of the CNN algorithm for classification of fruits: apple, banana and orange. The paper presents the comparative increase of accuracy of different activation functions over the ReLu activation function. The algorithm is trained and tested over a database created by downloading fruit images from the online sources. Also, this paper presents the effect of increasing the number of convolutional layers of the CNN algorithm on the Accuracy and latency of the model. The software used for simulation of the model is Python implemented using Jupyter Notebook over the Anaconda platform.
{"title":"Impact of Activation Functions and Number of Layers on the Classification of Fruits using CNN","authors":"Z. Haq, Z. Jaffery","doi":"10.1109/INDIACom51348.2021.00040","DOIUrl":"https://doi.org/10.1109/INDIACom51348.2021.00040","url":null,"abstract":"The classification of fruits into various classes is becoming inherent to the food processing industry. This paper presents a simulation analysis of effect of activation functions: ReLu, Softmax, sigmoid, and Softplus on the accuracy and latency of the CNN algorithm for classification of fruits: apple, banana and orange. The paper presents the comparative increase of accuracy of different activation functions over the ReLu activation function. The algorithm is trained and tested over a database created by downloading fruit images from the online sources. Also, this paper presents the effect of increasing the number of convolutional layers of the CNN algorithm on the Accuracy and latency of the model. The software used for simulation of the model is Python implemented using Jupyter Notebook over the Anaconda platform.","PeriodicalId":415594,"journal":{"name":"2021 8th International Conference on Computing for Sustainable Global Development (INDIACom)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116559948","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 : 2021-03-17DOI: 10.1109/INDIACom51348.2021.00163
Geetanjali Surange, P. Khatri
IoT has become inevitable in current scenario of due to idea of smart living. Every aspect of human civilization is being converged to IoT systems, may it be smart homes, personal grooming, organization, smart city, health care, business, manufacturing, etc. IoT systems are not only contributing to improving the quality of service but also to effectively use resources. But, due to exposure of all sensitive data of a person/organization to the cyber community through IoT systems, which majorly exploits cloud platforms for implementing them, the people and organization are at more risk, and no. of cyber-crimes are also increasing day by day. Cyber-crime investigation involves digital forensic which is a typical task for IoT environments due to its heterogeneous nature. This work compiles a survey done on the current developments in the field of IoT forensic and tried to identify gaps, challenges, and scope of research in the field.
{"title":"IoT Forensics: A Review on Current Trends, Approaches and Foreseen Challenges","authors":"Geetanjali Surange, P. Khatri","doi":"10.1109/INDIACom51348.2021.00163","DOIUrl":"https://doi.org/10.1109/INDIACom51348.2021.00163","url":null,"abstract":"IoT has become inevitable in current scenario of due to idea of smart living. Every aspect of human civilization is being converged to IoT systems, may it be smart homes, personal grooming, organization, smart city, health care, business, manufacturing, etc. IoT systems are not only contributing to improving the quality of service but also to effectively use resources. But, due to exposure of all sensitive data of a person/organization to the cyber community through IoT systems, which majorly exploits cloud platforms for implementing them, the people and organization are at more risk, and no. of cyber-crimes are also increasing day by day. Cyber-crime investigation involves digital forensic which is a typical task for IoT environments due to its heterogeneous nature. This work compiles a survey done on the current developments in the field of IoT forensic and tried to identify gaps, challenges, and scope of research in the field.","PeriodicalId":415594,"journal":{"name":"2021 8th International Conference on Computing for Sustainable Global Development (INDIACom)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131441331","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 : 2021-03-17DOI: 10.1109/INDIACom51348.2021.00118
Kashvi Taunk, Pulkit Singh, Rajat Kumar Behera
Suicide analysis is an area of vital importance to the National Institute of Mental Health and various other agencies working in the field of suicide prevention. Studying on this aspect helps to analyze the suicide pattern and trends that suicides follow over the years. This paper explores time-series data of the suicides that occurred in India to find whether there is a notable change in trend after a certain time point. A predictive approach is applied to forecast into the future of the suicide trend. The paper applies Facebook Prophet, a time-series prediction algorithm for drawing inferences and conclusions. The paper also suggests an inflection point algorithm that highlights the suicide trend between two points in time. Additionally, the model is also capable of predicting the trend for “n” number of years to come. We have used MAPE and SMAPE error techniques for accurate measurement. The mean absolute percentage error (MAPE) is a predictive accuracy measure while the symmetric mean absolute percentage error (SMAPE) is a percentage (or relative) error-dependent accuracy measure. The values of MAPE and SMAPE were found to be in the range of 0.1-0.2 and less than 12 respectively. The conclusion derived is that the result is an increasing nature in the current year and there is a need for utmost attention.
{"title":"Suicide Trend Analysis and Prediction in India using Facebook Prophet","authors":"Kashvi Taunk, Pulkit Singh, Rajat Kumar Behera","doi":"10.1109/INDIACom51348.2021.00118","DOIUrl":"https://doi.org/10.1109/INDIACom51348.2021.00118","url":null,"abstract":"Suicide analysis is an area of vital importance to the National Institute of Mental Health and various other agencies working in the field of suicide prevention. Studying on this aspect helps to analyze the suicide pattern and trends that suicides follow over the years. This paper explores time-series data of the suicides that occurred in India to find whether there is a notable change in trend after a certain time point. A predictive approach is applied to forecast into the future of the suicide trend. The paper applies Facebook Prophet, a time-series prediction algorithm for drawing inferences and conclusions. The paper also suggests an inflection point algorithm that highlights the suicide trend between two points in time. Additionally, the model is also capable of predicting the trend for “n” number of years to come. We have used MAPE and SMAPE error techniques for accurate measurement. The mean absolute percentage error (MAPE) is a predictive accuracy measure while the symmetric mean absolute percentage error (SMAPE) is a percentage (or relative) error-dependent accuracy measure. The values of MAPE and SMAPE were found to be in the range of 0.1-0.2 and less than 12 respectively. The conclusion derived is that the result is an increasing nature in the current year and there is a need for utmost attention.","PeriodicalId":415594,"journal":{"name":"2021 8th International Conference on Computing for Sustainable Global Development (INDIACom)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128318853","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 : 2021-03-17DOI: 10.1109/INDIACom51348.2021.00137
Rudrajit Choudhuri, Amit Paul
A Novel Coronavirus (Sars-Cov-2) struck the world in December, 2019. First Detected in Wuhan, China: this acute respiratory syndrome has spread all over the world at the present moment and has been officially declared as a global pandemic. A massive detrimental effect on global health and economy has been noticed. While researchers are continuously in search of vaccines - detection and proper diagnosis of the virus is as important to limit the spread of the virus. Chest X-Rays (CXRs) is one of the most common types of radiology examination and CXRs of the infected patients can serve as a crucial step in detection of the virus. Having a computer aided automatic diagnosis can minimize human interactions, errors, and workload and maximize efficiency. Various studies have shown that use of artificial intelligence in detection of Covid-19 patients through their CXRs is strongly optimistic. In this paper, a robust and efficient computer aided detection system has been proposed for multiclass image classification of diseases like Covid-19 and Pneumonia using the CXRs of patients. The algorithms have currently achieved desired results which can be further improved when more CXR images are available. The proposed method has outperformed current state of the art algorithms and has achieved 98.3% accuracy with a precision metric of 0.94, and can be used as a fast and reliable preliminary test for detection of the virus.
{"title":"Multi Class Image Classification for Detection Of Diseases Using Chest X Ray Images","authors":"Rudrajit Choudhuri, Amit Paul","doi":"10.1109/INDIACom51348.2021.00137","DOIUrl":"https://doi.org/10.1109/INDIACom51348.2021.00137","url":null,"abstract":"A Novel Coronavirus (Sars-Cov-2) struck the world in December, 2019. First Detected in Wuhan, China: this acute respiratory syndrome has spread all over the world at the present moment and has been officially declared as a global pandemic. A massive detrimental effect on global health and economy has been noticed. While researchers are continuously in search of vaccines - detection and proper diagnosis of the virus is as important to limit the spread of the virus. Chest X-Rays (CXRs) is one of the most common types of radiology examination and CXRs of the infected patients can serve as a crucial step in detection of the virus. Having a computer aided automatic diagnosis can minimize human interactions, errors, and workload and maximize efficiency. Various studies have shown that use of artificial intelligence in detection of Covid-19 patients through their CXRs is strongly optimistic. In this paper, a robust and efficient computer aided detection system has been proposed for multiclass image classification of diseases like Covid-19 and Pneumonia using the CXRs of patients. The algorithms have currently achieved desired results which can be further improved when more CXR images are available. The proposed method has outperformed current state of the art algorithms and has achieved 98.3% accuracy with a precision metric of 0.94, and can be used as a fast and reliable preliminary test for detection of the virus.","PeriodicalId":415594,"journal":{"name":"2021 8th International Conference on Computing for Sustainable Global Development (INDIACom)","volume":"365 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131764175","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 : 2021-03-17DOI: 10.1109/INDIACom51348.2021.00127
Suchandana Mishra, P. Sharan, Sushma P Kamath, S. K
In today's era, monitoring train speed is an important factor in structural health monitoring of trains in railways. In this work, finite element analysis has been done for rail wheel model using ANSYS15.0 software. Simulation of Fiber Bragg Grating sensor is done by GratingMOD. Here train speed varies from 20 to 80kmph to observe the stress and strain response on the rail, with maximum stress, 190.96 MPa, strain of 111.89e-5mm and total deformation of 697.4mm, at constant wagon weight 57.3tons. Shift in Bragg's wavelength is 1551.4845nm at maximum speed, 80 kmph.
{"title":"Monitoring of Rail Wheel Impact for Various Train Speeds","authors":"Suchandana Mishra, P. Sharan, Sushma P Kamath, S. K","doi":"10.1109/INDIACom51348.2021.00127","DOIUrl":"https://doi.org/10.1109/INDIACom51348.2021.00127","url":null,"abstract":"In today's era, monitoring train speed is an important factor in structural health monitoring of trains in railways. In this work, finite element analysis has been done for rail wheel model using ANSYS15.0 software. Simulation of Fiber Bragg Grating sensor is done by GratingMOD. Here train speed varies from 20 to 80kmph to observe the stress and strain response on the rail, with maximum stress, 190.96 MPa, strain of 111.89e-5mm and total deformation of 697.4mm, at constant wagon weight 57.3tons. Shift in Bragg's wavelength is 1551.4845nm at maximum speed, 80 kmph.","PeriodicalId":415594,"journal":{"name":"2021 8th International Conference on Computing for Sustainable Global Development (INDIACom)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127815003","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 : 2021-03-17DOI: 10.1109/INDIACom51348.2021.00019
T. Mujtaba, M. ArifWani
This study explores a supervised deep learning fully convolutional segmentation model for photovoltaic solar array mapping from aerial imagery. The deep learning imaging techniques present a fast and an inexpensive way for detecting distributed photovoltaic arrays installed on ground and building rooftops. The identification of correct photovoltaic array shapes and sizes is a necessary requirement for the estimation of energy from photovoltaic arrays within an area or city. This study proposes a modified and efficient UNet deep learning segmentation model by using depthwise-separable convolution for automated photovoltaic array detection from orthorectified RGB imagery with a resolution of less or equal to 0.3m. The result shows our model has better segmentation accuracy than various state of the art models and other previous studies on solar panel detection and is efficient in terms of parameters and complexity.
{"title":"Photovoltaic Solar Array Mapping using Supervised Fully Convolutional Neural Networks","authors":"T. Mujtaba, M. ArifWani","doi":"10.1109/INDIACom51348.2021.00019","DOIUrl":"https://doi.org/10.1109/INDIACom51348.2021.00019","url":null,"abstract":"This study explores a supervised deep learning fully convolutional segmentation model for photovoltaic solar array mapping from aerial imagery. The deep learning imaging techniques present a fast and an inexpensive way for detecting distributed photovoltaic arrays installed on ground and building rooftops. The identification of correct photovoltaic array shapes and sizes is a necessary requirement for the estimation of energy from photovoltaic arrays within an area or city. This study proposes a modified and efficient UNet deep learning segmentation model by using depthwise-separable convolution for automated photovoltaic array detection from orthorectified RGB imagery with a resolution of less or equal to 0.3m. The result shows our model has better segmentation accuracy than various state of the art models and other previous studies on solar panel detection and is efficient in terms of parameters and complexity.","PeriodicalId":415594,"journal":{"name":"2021 8th International Conference on Computing for Sustainable Global Development (INDIACom)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127945886","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 : 2021-03-17DOI: 10.1109/INDIACom51348.2021.00148
Deepanshu Tanwar, Vaibhav Nijhawan, P. Sinha, Rashi Gupta
In 2019, India recorded an overall 4,05,861 cases of crime against women, it was a rise of 7% from 2018. In 2019 total of 32,033 cases of rape were lodged, which was 7.3% of all crimes against women [18]. Data shows that the crime rate registered per lakh women population increased from 58.8 in 2018 to 62.4 in 2019 [18] [20]. There are many problems like sexual harassment, domestic violence, eve-teasing that are being faced by women. Sometimes victims don't have proof to prove to mishappen [20]. We proposed a device which will send an SMS to the registered mobile numbers when a button is pressed or when the women fall and save voice recording of that situation as proof. There are two separate parts in our proposed model, first is a transmitter which will be on the wrist and the other is a receiver part which contains Arduino UNO interfaced with SIM900A GSM module, NEO6M GPS module [15], RF TRANSMITTER AND RECEIVER module, BUZZER, MPU6050 (accelerometer) and ISD1820 (voice recorder) which will be fit on the jacket. When either a button is pressed from transmitter or MPU6050 (accelerometer) detects any fall, second part got activated and an emergency message will be sent with the current latitude and longitude, the buzzer will make a loud sound to get the attention of nearby people for quick help and ISD1820 (voice recorder) start recording voice as a proof.
{"title":"Design of Low-Cost Women Safety System using GPS and GSM","authors":"Deepanshu Tanwar, Vaibhav Nijhawan, P. Sinha, Rashi Gupta","doi":"10.1109/INDIACom51348.2021.00148","DOIUrl":"https://doi.org/10.1109/INDIACom51348.2021.00148","url":null,"abstract":"In 2019, India recorded an overall 4,05,861 cases of crime against women, it was a rise of 7% from 2018. In 2019 total of 32,033 cases of rape were lodged, which was 7.3% of all crimes against women [18]. Data shows that the crime rate registered per lakh women population increased from 58.8 in 2018 to 62.4 in 2019 [18] [20]. There are many problems like sexual harassment, domestic violence, eve-teasing that are being faced by women. Sometimes victims don't have proof to prove to mishappen [20]. We proposed a device which will send an SMS to the registered mobile numbers when a button is pressed or when the women fall and save voice recording of that situation as proof. There are two separate parts in our proposed model, first is a transmitter which will be on the wrist and the other is a receiver part which contains Arduino UNO interfaced with SIM900A GSM module, NEO6M GPS module [15], RF TRANSMITTER AND RECEIVER module, BUZZER, MPU6050 (accelerometer) and ISD1820 (voice recorder) which will be fit on the jacket. When either a button is pressed from transmitter or MPU6050 (accelerometer) detects any fall, second part got activated and an emergency message will be sent with the current latitude and longitude, the buzzer will make a loud sound to get the attention of nearby people for quick help and ISD1820 (voice recorder) start recording voice as a proof.","PeriodicalId":415594,"journal":{"name":"2021 8th International Conference on Computing for Sustainable Global Development (INDIACom)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128680751","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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