Sharnil Pandya - Academia.edu (original) (raw)

Papers by Sharnil Pandya

Research paper thumbnail of Hand Gesture based Home Control Device using IoT

Internet of Things or IoT is nothing but an evolved version of Internet, which includes sensors, ... more Internet of Things or IoT is nothing but an evolved version of Internet, which includes sensors, consumer electronic devices and other embedded systems connected to it besides computers, smart phones and tablets to collect and exchange data with one another. IoT technology can also be applied to create a new concept for smart homes to provide intelligence, comfort to improve the quality of life. Home automation is control appliances using the remote control, internet, voice and gesture. We control the appliances using the hand gesture. A Human Computer Interaction (HCI) between computers and human understands human language and develop a user friendly interface. Gestures a non-verbal form of communication provides the HCI interface. The goal of gesture recognition is to create a system which can identify specific human gestures and use them to convey information or for device control. Hand gesture recognition is relatively complicated since different persons have different speeds an...

Research paper thumbnail of A Survey on Various Issues in Wireless Sensor Networks

Recent developments in micro-electro-mechanical systems (MEMS), wireless communications, and digi... more Recent developments in micro-electro-mechanical systems (MEMS), wireless communications, and digital electronics have enabled development of low cost, low power, multifunctional sensor nodes are small and freedom to communicate in short distances. However, it has still remained an open challenge to deploy sensor nodes in wireless environment as we have to deal with innumerable constraints for their complete implementation. In this paper, a detailed survey has been carried out to analyze various techniques, which could be used to address present unresolved issues in wireless sensor networks.

Research paper thumbnail of Deep Learning Model for Acoustics Signal Based Preventive Healthcare Monitoring and Activity of Daily Living

2nd International Conference on Data, Engineering and Applications (IDEA)

To cope with the increasing healthcare costs and nursing shortages in the Aging Society the care ... more To cope with the increasing healthcare costs and nursing shortages in the Aging Society the care system is transferred, as much as possible, to the home environment, making use of ambient assisted living (AAL) monitoring and communication possibilities and to actively involve informal cares to fill in large part of the care that is needed. The proposed system is the AAL based, acoustics sensing system ready to dissect, recognize, and distinguish specific acoustic events occurring in day-by-day life situations, which empowers not only the individual subjects but also the healthcare professionals to remotely follow the status of each individual continuously. This system only processes the background acoustics related to the activity of daily living (ADL) for preventive healthcare. The novel contribution of the research is based on prototype development, audio signal processing algorithms and deep learning algorithms to satisfy the research gap.

Research paper thumbnail of Harvesting social media sentiment analysis to enhance stock market prediction using deep learning

PeerJ Computer Science

Information gathering has become an integral part of assessing people’s behaviors and actions. Th... more Information gathering has become an integral part of assessing people’s behaviors and actions. The Internet is used as an online learning site for sharing and exchanging ideas. People can actively give their reviews and recommendations for variety of products and services using popular social sites and personal blogs. Social networking sites, including Twitter, Facebook, and Google+, are examples of the sites used to share opinion. The stock market (SM) is an essential area of the economy and plays a significant role in trade and industry development. Predicting SM movements is a well-known and area of interest to researchers. Social networking perfectly reflects the public’s views of current affairs. Financial news stories are thought to have an impact on the return of stock trend prices and many data mining techniques are used address fluctuations in the SM. Machine learning can provide a more accurate and robust approach to handle SM-related predictions. We sought to identify how...

Research paper thumbnail of Wellness Sensor Network for modeling Activity of Daily Livings – Proposal and Off-Line Preliminary Analysis

2018 4th International Conference on Computing Communication and Automation (ICCCA)

Research paper thumbnail of Precision Agriculture: Methodologies, Practices and Applications

Proceedings of Second International Conference on Computing, Communications, and Cyber-Security

Research paper thumbnail of Smart Aging Wellness Sensor Networks: A Near Real-Time Daily Activity Health Monitoring, Anomaly Detection and Alert System

Proceedings of Second International Conference on Computing, Communications, and Cyber-Security

Research paper thumbnail of Pollution Weather Prediction System: Smart Outdoor Pollution Monitoring and Prediction for Healthy Breathing and Living

Sensors

Air pollution has been a looming issue of the 21st century that has also significantly impacted t... more Air pollution has been a looming issue of the 21st century that has also significantly impacted the surrounding environment and societal health. Recently, previous studies have conducted extensive research on air pollution and air quality monitoring. Despite this, the fields of air pollution and air quality monitoring remain plagued with unsolved problems. In this study, the Pollution Weather Prediction System (PWP) is proposed to perform air pollution prediction for outdoor sites for various pollution parameters. In the presented research work, we introduced a PWP system configured with pollution-sensing units, such as SDS021, MQ07-CO, NO2-B43F, and Aeroqual Ozone (O3). These sensing units were utilized to collect and measure various pollutant levels, such as PM2.5, PM10, CO, NO2, and O3, for 90 days at Symbiosis International University, Pune, Maharashtra, India. The data collection was carried out between the duration of December 2019 to February 2020 during the winter. The inves...

Research paper thumbnail of Ambient acoustic event assistive framework for identification, detection, and recognition of unknown acoustic events of a residence

Advanced Engineering Informatics

Research paper thumbnail of New approach for frequent item set generation based on Mirabit hashing algorithm

2016 International Conference on Inventive Computation Technologies (ICICT)

Research paper thumbnail of NXTGeUH: LoRaWAN based NEXT Generation Ubiquitous Healthcare System for Vital Signs Monitoring Falls Detection

Research paper thumbnail of A Novel Multicast Secure MQTT Messaging Protocol Framework for IoT-Related Issues

Proceedings of Second International Conference on Computing, Communications, and Cyber-Security

Research paper thumbnail of Proposal and Preliminary Fall-related Activities Recognition in Indoor Environment

2019 IEEE 19th International Conference on Communication Technology (ICCT)

Research paper thumbnail of ReCognizing SUspect and PredictiNg ThE SpRead of Contagion Based on Mobile Phone LoCation DaTa (COUNTERACT): A system of identifying COVID-19 infectious and hazardous sites, detecting disease outbreaks based on the internet of things, edge computing, and artificial intelligence

Sustainable Cities and Society

Research paper thumbnail of Smart Cardiac Framework for an Early Detection of Cardiac Arrest Condition and Risk

Frontiers in Public Health

Cardiovascular disease (CVD) is considered to be one of the most epidemic diseases in the world t... more Cardiovascular disease (CVD) is considered to be one of the most epidemic diseases in the world today. Predicting CVDs, such as cardiac arrest, is a difficult task in the area of healthcare. The healthcare industry has a vast collection of datasets for analysis and prediction purposes. Somehow, the predictions made on these publicly available datasets may be erroneous. To make the prediction accurate, real-time data need to be collected. This study collected real-time data using sensors and stored it on a cloud computing platform, such as Google Firebase. The acquired data is then classified using six machine-learning algorithms: Artificial Neural Network (ANN), Random Forest Classifier (RFC), Gradient Boost Extreme Gradient Boosting (XGBoost) classifier, Support Vector Machine (SVM), Naïve Bayes (NB), and Decision Tree (DT). Furthermore, we have presented two novel gender-based risk classification and age-wise risk classification approach in the undertaken study. The presented appr...

Research paper thumbnail of CNN Variants for Computer Vision: History, Architecture, Application, Challenges and Future Scope

Electronics

Computer vision is becoming an increasingly trendy word in the area of image processing. With the... more Computer vision is becoming an increasingly trendy word in the area of image processing. With the emergence of computer vision applications, there is a significant demand to recognize objects automatically. Deep CNN (convolution neural network) has benefited the computer vision community by producing excellent results in video processing, object recognition, picture classification and segmentation, natural language processing, speech recognition, and many other fields. Furthermore, the introduction of large amounts of data and readily available hardware has opened new avenues for CNN study. Several inspirational concepts for the progress of CNN have been investigated, including alternative activation functions, regularization, parameter optimization, and architectural advances. Furthermore, achieving innovations in architecture results in a tremendous enhancement in the capacity of the deep CNN. Significant emphasis has been given to leveraging channel and spatial information, with ...

Research paper thumbnail of Implementation of Novel Load Balancing Technique in Cloud Computing Environmen

2018 International Conference on Computer Communication and Informatics (ICCCI)

Research paper thumbnail of i-MsRTRM: Developing an IoT Based Intelligent Medicare System for Real-Time Remote Health Monitoring

2016 8th International Conference on Computational Intelligence and Communication Networks (CICN)

Research paper thumbnail of An integrated approach for sustainable development of wastewater treatment and management system using IoT in smart cities

Research paper thumbnail of Deep learning based respiratory sound analysis for detection of chronic obstructive pulmonary disease

PeerJ Computer Science

In recent times, technologies such as machine learning and deep learning have played a vital role... more In recent times, technologies such as machine learning and deep learning have played a vital role in providing assistive solutions to a medical domain’s challenges. They also improve predictive accuracy for early and timely disease detection using medical imaging and audio analysis. Due to the scarcity of trained human resources, medical practitioners are welcoming such technology assistance as it provides a helping hand to them in coping with more patients. Apart from critical health diseases such as cancer and diabetes, the impact of respiratory diseases is also gradually on the rise and is becoming life-threatening for society. The early diagnosis and immediate treatment are crucial in respiratory diseases, and hence the audio of the respiratory sounds is proving very beneficial along with chest X-rays. The presented research work aims to apply Convolutional Neural Network based deep learning methodologies to assist medical experts by providing a detailed and rigorous analysis of...

Research paper thumbnail of Hand Gesture based Home Control Device using IoT

Internet of Things or IoT is nothing but an evolved version of Internet, which includes sensors, ... more Internet of Things or IoT is nothing but an evolved version of Internet, which includes sensors, consumer electronic devices and other embedded systems connected to it besides computers, smart phones and tablets to collect and exchange data with one another. IoT technology can also be applied to create a new concept for smart homes to provide intelligence, comfort to improve the quality of life. Home automation is control appliances using the remote control, internet, voice and gesture. We control the appliances using the hand gesture. A Human Computer Interaction (HCI) between computers and human understands human language and develop a user friendly interface. Gestures a non-verbal form of communication provides the HCI interface. The goal of gesture recognition is to create a system which can identify specific human gestures and use them to convey information or for device control. Hand gesture recognition is relatively complicated since different persons have different speeds an...

Research paper thumbnail of A Survey on Various Issues in Wireless Sensor Networks

Recent developments in micro-electro-mechanical systems (MEMS), wireless communications, and digi... more Recent developments in micro-electro-mechanical systems (MEMS), wireless communications, and digital electronics have enabled development of low cost, low power, multifunctional sensor nodes are small and freedom to communicate in short distances. However, it has still remained an open challenge to deploy sensor nodes in wireless environment as we have to deal with innumerable constraints for their complete implementation. In this paper, a detailed survey has been carried out to analyze various techniques, which could be used to address present unresolved issues in wireless sensor networks.

Research paper thumbnail of Deep Learning Model for Acoustics Signal Based Preventive Healthcare Monitoring and Activity of Daily Living

2nd International Conference on Data, Engineering and Applications (IDEA)

To cope with the increasing healthcare costs and nursing shortages in the Aging Society the care ... more To cope with the increasing healthcare costs and nursing shortages in the Aging Society the care system is transferred, as much as possible, to the home environment, making use of ambient assisted living (AAL) monitoring and communication possibilities and to actively involve informal cares to fill in large part of the care that is needed. The proposed system is the AAL based, acoustics sensing system ready to dissect, recognize, and distinguish specific acoustic events occurring in day-by-day life situations, which empowers not only the individual subjects but also the healthcare professionals to remotely follow the status of each individual continuously. This system only processes the background acoustics related to the activity of daily living (ADL) for preventive healthcare. The novel contribution of the research is based on prototype development, audio signal processing algorithms and deep learning algorithms to satisfy the research gap.

Research paper thumbnail of Harvesting social media sentiment analysis to enhance stock market prediction using deep learning

PeerJ Computer Science

Information gathering has become an integral part of assessing people’s behaviors and actions. Th... more Information gathering has become an integral part of assessing people’s behaviors and actions. The Internet is used as an online learning site for sharing and exchanging ideas. People can actively give their reviews and recommendations for variety of products and services using popular social sites and personal blogs. Social networking sites, including Twitter, Facebook, and Google+, are examples of the sites used to share opinion. The stock market (SM) is an essential area of the economy and plays a significant role in trade and industry development. Predicting SM movements is a well-known and area of interest to researchers. Social networking perfectly reflects the public’s views of current affairs. Financial news stories are thought to have an impact on the return of stock trend prices and many data mining techniques are used address fluctuations in the SM. Machine learning can provide a more accurate and robust approach to handle SM-related predictions. We sought to identify how...

Research paper thumbnail of Wellness Sensor Network for modeling Activity of Daily Livings – Proposal and Off-Line Preliminary Analysis

2018 4th International Conference on Computing Communication and Automation (ICCCA)

Research paper thumbnail of Precision Agriculture: Methodologies, Practices and Applications

Proceedings of Second International Conference on Computing, Communications, and Cyber-Security

Research paper thumbnail of Smart Aging Wellness Sensor Networks: A Near Real-Time Daily Activity Health Monitoring, Anomaly Detection and Alert System

Proceedings of Second International Conference on Computing, Communications, and Cyber-Security

Research paper thumbnail of Pollution Weather Prediction System: Smart Outdoor Pollution Monitoring and Prediction for Healthy Breathing and Living

Sensors

Air pollution has been a looming issue of the 21st century that has also significantly impacted t... more Air pollution has been a looming issue of the 21st century that has also significantly impacted the surrounding environment and societal health. Recently, previous studies have conducted extensive research on air pollution and air quality monitoring. Despite this, the fields of air pollution and air quality monitoring remain plagued with unsolved problems. In this study, the Pollution Weather Prediction System (PWP) is proposed to perform air pollution prediction for outdoor sites for various pollution parameters. In the presented research work, we introduced a PWP system configured with pollution-sensing units, such as SDS021, MQ07-CO, NO2-B43F, and Aeroqual Ozone (O3). These sensing units were utilized to collect and measure various pollutant levels, such as PM2.5, PM10, CO, NO2, and O3, for 90 days at Symbiosis International University, Pune, Maharashtra, India. The data collection was carried out between the duration of December 2019 to February 2020 during the winter. The inves...

Research paper thumbnail of Ambient acoustic event assistive framework for identification, detection, and recognition of unknown acoustic events of a residence

Advanced Engineering Informatics

Research paper thumbnail of New approach for frequent item set generation based on Mirabit hashing algorithm

2016 International Conference on Inventive Computation Technologies (ICICT)

Research paper thumbnail of NXTGeUH: LoRaWAN based NEXT Generation Ubiquitous Healthcare System for Vital Signs Monitoring Falls Detection

Research paper thumbnail of A Novel Multicast Secure MQTT Messaging Protocol Framework for IoT-Related Issues

Proceedings of Second International Conference on Computing, Communications, and Cyber-Security

Research paper thumbnail of Proposal and Preliminary Fall-related Activities Recognition in Indoor Environment

2019 IEEE 19th International Conference on Communication Technology (ICCT)

Research paper thumbnail of ReCognizing SUspect and PredictiNg ThE SpRead of Contagion Based on Mobile Phone LoCation DaTa (COUNTERACT): A system of identifying COVID-19 infectious and hazardous sites, detecting disease outbreaks based on the internet of things, edge computing, and artificial intelligence

Sustainable Cities and Society

Research paper thumbnail of Smart Cardiac Framework for an Early Detection of Cardiac Arrest Condition and Risk

Frontiers in Public Health

Cardiovascular disease (CVD) is considered to be one of the most epidemic diseases in the world t... more Cardiovascular disease (CVD) is considered to be one of the most epidemic diseases in the world today. Predicting CVDs, such as cardiac arrest, is a difficult task in the area of healthcare. The healthcare industry has a vast collection of datasets for analysis and prediction purposes. Somehow, the predictions made on these publicly available datasets may be erroneous. To make the prediction accurate, real-time data need to be collected. This study collected real-time data using sensors and stored it on a cloud computing platform, such as Google Firebase. The acquired data is then classified using six machine-learning algorithms: Artificial Neural Network (ANN), Random Forest Classifier (RFC), Gradient Boost Extreme Gradient Boosting (XGBoost) classifier, Support Vector Machine (SVM), Naïve Bayes (NB), and Decision Tree (DT). Furthermore, we have presented two novel gender-based risk classification and age-wise risk classification approach in the undertaken study. The presented appr...

Research paper thumbnail of CNN Variants for Computer Vision: History, Architecture, Application, Challenges and Future Scope

Electronics

Computer vision is becoming an increasingly trendy word in the area of image processing. With the... more Computer vision is becoming an increasingly trendy word in the area of image processing. With the emergence of computer vision applications, there is a significant demand to recognize objects automatically. Deep CNN (convolution neural network) has benefited the computer vision community by producing excellent results in video processing, object recognition, picture classification and segmentation, natural language processing, speech recognition, and many other fields. Furthermore, the introduction of large amounts of data and readily available hardware has opened new avenues for CNN study. Several inspirational concepts for the progress of CNN have been investigated, including alternative activation functions, regularization, parameter optimization, and architectural advances. Furthermore, achieving innovations in architecture results in a tremendous enhancement in the capacity of the deep CNN. Significant emphasis has been given to leveraging channel and spatial information, with ...

Research paper thumbnail of Implementation of Novel Load Balancing Technique in Cloud Computing Environmen

2018 International Conference on Computer Communication and Informatics (ICCCI)

Research paper thumbnail of i-MsRTRM: Developing an IoT Based Intelligent Medicare System for Real-Time Remote Health Monitoring

2016 8th International Conference on Computational Intelligence and Communication Networks (CICN)

Research paper thumbnail of An integrated approach for sustainable development of wastewater treatment and management system using IoT in smart cities

Research paper thumbnail of Deep learning based respiratory sound analysis for detection of chronic obstructive pulmonary disease

PeerJ Computer Science

In recent times, technologies such as machine learning and deep learning have played a vital role... more In recent times, technologies such as machine learning and deep learning have played a vital role in providing assistive solutions to a medical domain’s challenges. They also improve predictive accuracy for early and timely disease detection using medical imaging and audio analysis. Due to the scarcity of trained human resources, medical practitioners are welcoming such technology assistance as it provides a helping hand to them in coping with more patients. Apart from critical health diseases such as cancer and diabetes, the impact of respiratory diseases is also gradually on the rise and is becoming life-threatening for society. The early diagnosis and immediate treatment are crucial in respiratory diseases, and hence the audio of the respiratory sounds is proving very beneficial along with chest X-rays. The presented research work aims to apply Convolutional Neural Network based deep learning methodologies to assist medical experts by providing a detailed and rigorous analysis of...