Physics & Technology
Apply tech to push the frontiers of physics - transforming energy, motion and the environment into groundbreaking solutions.
Physics & Technology
Apply tech to push the frontiers of physics - transforming energy, motion and the environment into groundbreaking solutions.
Utilizing Digital & Physical Simulations to Investigate Time Measurement with Millisecond Pulsar
This research study explores the use of millisecond pulsars as a novel and reliable timekeeping technique, with a focus on how they may be incorporated into spacecraft to provide accurate time measurement. Although atomic and periodic clocks are extremely accurate, mistakes and structural issues do exist. Unlike pulses that occur every millisecond, millisecond pulses are consistent and have predictable intervals between shots. A computer simulation provides a complete and precise account of the millisecond pulsar's interaction with Earth. This smart simulation demonstrates the possibility of utilizing pulsars and emissions in real time. Examples of animations synchronized with millisecond music and the Earth's rotation provide a complicated knowledge of thinking. In physical simulation, real-time IR signal transmission is achieved utilizing an OLED display, IR communication, and an ESP8266 board. If successful, the receiver uses these signals to calculate the time.
Utilizing Digital & Physical Simulations to Investigate Time Measurement with Millisecond Pulsar
This research study explores the use of millisecond pulsars as a novel and reliable timekeeping technique, with a focus on how they may be incorporated into spacecraft to provide accurate time measurement. Although atomic and periodic clocks are extremely accurate, mistakes and structural issues do exist. Unlike pulses that occur every millisecond, millisecond pulses are consistent and have predictable intervals between shots. A computer simulation provides a complete and precise account of the millisecond pulsar's interaction with Earth. This smart simulation demonstrates the possibility of utilizing pulsars and emissions in real time. Examples of animations synchronized with millisecond music and the Earth's rotation provide a complicated knowledge of thinking. In physical simulation, real-time IR signal transmission is achieved utilizing an OLED display, IR communication, and an ESP8266 board. If successful, the receiver uses these signals to calculate the time.
Utilizing Digital & Physical Simulations to Investigate
This research study explores the use of millisecond pulsars as a novel and reliable timekeeping technique, with a focus on how they may be incorporated into spacecraft to provide accurate time measurement. Although atomic and periodic clocks are extremely accurate, mistakes and structural issues do exist. Unlike pulses that occur every millisecond, millisecond pulses are consistent and have predictable intervals between shots. A computer simulation provides a complete and precise account of the millisecond pulsar's interaction with Earth. This smart simulation demonstrates the possibility of utilizing pulsars and emissions in real time. Examples of animations synchronized with millisecond music and the Earth's rotation provide a complicated knowledge of thinking. In physical simulation, real-time IR signal transmission is achieved utilizing an OLED display, IR communication, and an ESP8266 board. If successful, the receiver uses these signals to calculate the time.
Experimental investigation of a 3D-printed Airless tire for vibration analysis
The research presented here looks into the vibration properties of 3D-printed airless tires, which have the potential to revolutionize tire design and transportation efficiency. Through extensive experimentation and vibration research, three distinct tire constructions were investigated. Because of its good damping and deformation qualities, thermoplastic polyurethane (TPU) was chosen as the 3D printing material. The experimental arrangement was designed to simulate real-world road conditions, and an MPU6050 sensor captured tire vibrations in three axes. The vibrational properties of the tire structures were revealed using Fast Fourier Transform (FFT) analysis, allowing for a comparative assessment of their stability. Structure 1 was found to be the most vibration-stable, followed by Structures 3 and 2.
Experimental investigation of a 3D-printed Airless tire for vibration analysis
The research presented here looks into the vibration properties of 3D-printed airless tires, which have the potential to revolutionize tire design and transportation efficiency. Through extensive experimentation and vibration research, three distinct tire constructions were investigated. Because of its good damping and deformation qualities, thermoplastic polyurethane (TPU) was chosen as the 3D printing material. The experimental arrangement was designed to simulate real-world road conditions, and an MPU6050 sensor captured tire vibrations in three axes. The vibrational properties of the tire structures were revealed using Fast Fourier Transform (FFT) analysis, allowing for a comparative assessment of their stability. Structure 1 was found to be the most vibration-stable, followed by Structures 3 and 2.
Experimental investigation of a 3D-printed Airless tire for vibration analysis
The research presented here looks into the vibration properties of 3D-printed airless tires, which have the potential to revolutionize tire design and transportation efficiency. Through extensive experimentation and vibration research, three distinct tire constructions were investigated. Because of its good damping and deformation qualities, thermoplastic polyurethane (TPU) was chosen as the 3D printing material. The experimental arrangement was designed to simulate real-world road conditions, and an MPU6050 sensor captured tire vibrations in three axes. The vibrational properties of the tire structures were revealed using Fast Fourier Transform (FFT) analysis, allowing for a comparative assessment of their stability. Structure 1 was found to be the most vibration-stable, followed by Structures 3 and 2.
Vacuum Tube-Based Train Waste Collection and Segregation Technique
Proper waste management is critical to ensure a clean environment and public health, and the Indian railways face significant challenges in this area due to inadequate infrastructure, low awareness among commuters, and insufficient recycling facilities. This research paper proposes a solution to these challenges by utilizing vacuum tubes installed along the compartments of each coach and an IoT-based monitoring system to track waste levels. The proposed solution includes the collection, segregation, and storage of waste in designated areas, transportation to processing facilities, and processing in compliance with local regulations while also monitoring and reporting waste management practices. The study evaluates the effectiveness and efficiency of the proposed solution, considering its environmental impact and potential benefits for the economy and society. The research findings provide valuable insights into sustainable train waste management and contribute to the long- term development of the railway industry.
Vacuum Tube-Based Train Waste Collection and Segregation Technique
Proper waste management is critical to ensure a clean environment and public health, and the Indian railways face significant challenges in this area due to inadequate infrastructure, low awareness among commuters, and insufficient recycling facilities. This research paper proposes a solution to these challenges by utilizing vacuum tubes installed along the compartments of each coach and an IoT-based monitoring system to track waste levels. The proposed solution includes the collection, segregation, and storage of waste in designated areas, transportation to processing facilities, and processing in compliance with local regulations while also monitoring and reporting waste management practices. The study evaluates the effectiveness and efficiency of the proposed solution, considering its environmental impact and potential benefits for the economy and society. The research findings provide valuable insights into sustainable train waste management and contribute to the long- term development of the railway industry.
Vacuum Tube-Based Train Waste Collection and Segregation Technique
Proper waste management is critical to ensure a clean environment and public health, and the Indian railways face significant challenges in this area due to inadequate infrastructure, low awareness among commuters, and insufficient recycling facilities. This research paper proposes a solution to these challenges by utilizing vacuum tubes installed along the compartments of each coach and an IoT-based monitoring system to track waste levels. The proposed solution includes the collection, segregation, and storage of waste in designated areas, transportation to processing facilities, and processing in compliance with local regulations while also monitoring and reporting waste management practices. The study evaluates the effectiveness and efficiency of the proposed solution, considering its environmental impact and potential benefits for the economy and society. The research findings provide valuable insights into sustainable train waste management and contribute to the long- term development of the railway industry.
Microplastic Classification and Quantification in Aqueous Systems
This study tackles microplastic contamination in Mumbai's aquatic ecosystems, using advanced analytical techniques and a trained CNN model for accurate identification and quantification. Results, with a high accuracy of 97%, provide vital insights into distribution, and ecological impact, and offer a robust method for responsible environmental monitoring in compliance with evolving global standards. Microplastic contamination in aquatic ecosystems poses a severe threat to environmental health and public well-being. This study addresses the urgent need for accurate identification and quantification of microplastics in water bodies using advanced analytical techniques and machine learning. The pervasive issue of microplastic pollution demands innovative approaches to understanding its extent, sources, and impact on aquatic environments.
Microplastic Classification and Quantification in Aqueous Systems
This study tackles microplastic contamination in Mumbai's aquatic ecosystems, using advanced analytical techniques and a trained CNN model for accurate identification and quantification. Results, with a high accuracy of 97%, provide vital insights into distribution, and ecological impact, and offer a robust method for responsible environmental monitoring in compliance with evolving global standards. Microplastic contamination in aquatic ecosystems poses a severe threat to environmental health and public well-being. This study addresses the urgent need for accurate identification and quantification of microplastics in water bodies using advanced analytical techniques and machine learning. The pervasive issue of microplastic pollution demands innovative approaches to understanding its extent, sources, and impact on aquatic environments.
Microplastic Classification and Quantification in Aqueous Systems
This study tackles microplastic contamination in Mumbai's aquatic ecosystems, using advanced analytical techniques and a trained CNN model for accurate identification and quantification. Results, with a high accuracy of 97%, provide vital insights into distribution, and ecological impact, and offer a robust method for responsible environmental monitoring in compliance with evolving global standards. Microplastic contamination in aquatic ecosystems poses a severe threat to environmental health and public well-being. This study addresses the urgent need for accurate identification and quantification of microplastics in water bodies using advanced analytical techniques and machine learning. The pervasive issue of microplastic pollution demands innovative approaches to understanding its extent, sources, and impact on aquatic environments.
Remote Patient Monitoring - SPO2 MONITORING SYSTEM
Pulmonary Fibrosis, a lung disease which material- izes when the tissue between alveoli and the blood vessels in the lungs start to thicken and harden, disallowing the lungs to function optimally. This in turn damages the lungs and the respiratory system inside the body, affecting the patients’ breathing and their daily activities. Conclusively, it causes a limited amount of oxygen(O2) to flow inside the bloodstream, causing a significant drop in oxygen levels in patients. Since the oxygen levels of a patient and their heart rate are correlated, if the oxygen levels start to drop, so will the heart rate, leading to Bradycardia. Hence, regulating these oxygen levels and the heart rate as well as a person’s body temperature, could solve or attempt to prevent multiple such diseases like pulmonary fibrosis, coronary heart diseases, hypoxemia, hypertension, sleep apnea, and many more diseases and disorders. In order to achieve stability in the oxygen levels, there should be an oxygen concentration.
Remote Patient Monitoring - SPO2 MONITORING SYSTEM
Pulmonary Fibrosis, a lung disease which material- izes when the tissue between alveoli and the blood vessels in the lungs start to thicken and harden, disallowing the lungs to function optimally. This in turn damages the lungs and the respiratory system inside the body, affecting the patients’ breathing and their daily activities. Conclusively, it causes a limited amount of oxygen(O2) to flow inside the bloodstream, causing a significant drop in oxygen levels in patients. Since the oxygen levels of a patient and their heart rate are correlated, if the oxygen levels start to drop, so will the heart rate, leading to Bradycardia. Hence, regulating these oxygen levels and the heart rate as well as a person’s body temperature, could solve or attempt to prevent multiple such diseases like pulmonary fibrosis, coronary heart diseases, hypoxemia, hypertension, sleep apnea, and many more diseases and disorders. In order to achieve stability in the oxygen levels, there should be an oxygen concentration.
Remote Patient Monitoring - SPO2 MONITORING SYSTEM
Pulmonary Fibrosis, a lung disease which material- izes when the tissue between alveoli and the blood vessels in the lungs start to thicken and harden, disallowing the lungs to function optimally. This in turn damages the lungs and the respiratory system inside the body, affecting the patients’ breathing and their daily activities. Conclusively, it causes a limited amount of oxygen(O2) to flow inside the bloodstream, causing a significant drop in oxygen levels in patients. Since the oxygen levels of a patient and their heart rate are correlated, if the oxygen levels start to drop, so will the heart rate, leading to Bradycardia. Hence, regulating these oxygen levels and the heart rate as well as a person’s body temperature, could solve or attempt to prevent multiple such diseases like pulmonary fibrosis, coronary heart diseases, hypoxemia, hypertension, sleep apnea, and many more diseases and disorders. In order to achieve stability in the oxygen levels, there should be an oxygen concentration.
Stress Ball with Embedded Sensor for Exercise and Muscle Strength Assessment in Autistic Children
This study describes the construction and testing of a ball with built-in sensors that are intended to evaluate muscular strength and promote exercise in autistic youngsters. To measure the throwing force and the squeezing strength, the ball has in built accelerometers and force sensors. This research highlights how technology-assisted therapy can benefit autistic children's physical health and development. The data collected by the stress ball included force data from the FSR sensor, timestamps, and acceleration data from the MPU6050 sensor. The stress ball uses the Bluetooth module to transmit data wirelessly to a remote device running Python script which stores the data for later analysis. The pressure data and the acceleration data generated during the squeezing action and the throwing action were collected across 6 weeks. The average of the peak force and the acceleration data were plotted for multiple weeks.
Stress Ball with Embedded Sensor for Exercise and Muscle Strength Assessment in Autistic Children
This study describes the construction and testing of a ball with built-in sensors that are intended to evaluate muscular strength and promote exercise in autistic youngsters. To measure the throwing force and the squeezing strength, the ball has in built accelerometers and force sensors. This research highlights how technology-assisted therapy can benefit autistic children's physical health and development. The data collected by the stress ball included force data from the FSR sensor, timestamps, and acceleration data from the MPU6050 sensor. The stress ball uses the Bluetooth module to transmit data wirelessly to a remote device running Python script which stores the data for later analysis. The pressure data and the acceleration data generated during the squeezing action and the throwing action were collected across 6 weeks. The average of the peak force and the acceleration data were plotted for multiple weeks.
Stress Ball with Embedded Sensor for Exercise and Muscle Strength Assessment in Autistic Children
This study describes the construction and testing of a ball with built-in sensors that are intended to evaluate muscular strength and promote exercise in autistic youngsters. To measure the throwing force and the squeezing strength, the ball has in built accelerometers and force sensors. This research highlights how technology-assisted therapy can benefit autistic children's physical health and development. The data collected by the stress ball included force data from the FSR sensor, timestamps, and acceleration data from the MPU6050 sensor. The stress ball uses the Bluetooth module to transmit data wirelessly to a remote device running Python script which stores the data for later analysis. The pressure data and the acceleration data generated during the squeezing action and the throwing action were collected across 6 weeks. The average of the peak force and the acceleration data were plotted for multiple weeks.
Automatic Water Conservation System
IoT-enabled flow sensor work synergistically with the variable orifice, orifice sensor monitors real-time flow rates, expedite the orifice aperture's adjustment, and optimizes water usage this mortar is attached to the orifice to maintain the flow rate of water. In addition, this sensor provides granular data collection, and continuous monitoring and is essential for subsequent data analysis. Flow sensor data is uploaded to the cloud with a time stamp. The designed prototype was installed in both public washrooms and home-use situations to take measurements of washing hands, vegetables, etc., and determine the most appropriate flow rates for specific household tasks. This prototype’s data was evaluated based on the flow control accuracy, data transmission reliability, efficiency in conservation, and waste reductions. During the present study, data from daily household activities to evaluate the efficiency of the variable orifice system in conjunction with two different modes: Mode1 and Mode 2.
Automatic Water Conservation System
IoT-enabled flow sensor work synergistically with the variable orifice, orifice sensor monitors real-time flow rates, expedite the orifice aperture's adjustment, and optimizes water usage this mortar is attached to the orifice to maintain the flow rate of water. In addition, this sensor provides granular data collection, and continuous monitoring and is essential for subsequent data analysis. Flow sensor data is uploaded to the cloud with a time stamp. The designed prototype was installed in both public washrooms and home-use situations to take measurements of washing hands, vegetables, etc., and determine the most appropriate flow rates for specific household tasks. This prototype’s data was evaluated based on the flow control accuracy, data transmission reliability, efficiency in conservation, and waste reductions. During the present study, data from daily household activities to evaluate the efficiency of the variable orifice system in conjunction with two different modes: Mode1 and Mode 2.
Automatic Water Conservation System
IoT-enabled flow sensor work synergistically with the variable orifice, orifice sensor monitors real-time flow rates, expedite the orifice aperture's adjustment, and optimizes water usage this mortar is attached to the orifice to maintain the flow rate of water. In addition, this sensor provides granular data collection, and continuous monitoring and is essential for subsequent data analysis. Flow sensor data is uploaded to the cloud with a time stamp. The designed prototype was installed in both public washrooms and home-use situations to take measurements of washing hands, vegetables, etc., and determine the most appropriate flow rates for specific household tasks. This prototype’s data was evaluated based on the flow control accuracy, data transmission reliability, efficiency in conservation, and waste reductions. During the present study, data from daily household activities to evaluate the efficiency of the variable orifice system in conjunction with two different modes: Mode1 and Mode 2.
Machine Learning for Fault Detection in DC Motors and the Role of Mounting Configurations
Unexpected motor failures can disrupt industrial processes, affecting efficiency, safety, and profitability. This study introduces an AI-based approach for industrial DC motor monitoring to address these issues. This tool accurately detects and predicts motor malfunctions using the k-Nearest Neighbours (k-NN) machine learning model using sensor data analysis, enabling proactive maintenance. This system streamlines industrial operations by reducing downtime, repair costs, and safety. We tested this algorithm under vertical and horizontal mounting conditions for performance analysis. In fully loaded conditions, horizontal mounting outperformed vertical mounting. The k-NN model detected and predicted motor faults with 95.22% accuracy on the test set. Our AI-enabled tool can improve industrial efficiency and safety, according to this study.
Machine Learning for Fault Detection in DC Motors and the Role of Mounting Configurations
Unexpected motor failures can disrupt industrial processes, affecting efficiency, safety, and profitability. This study introduces an AI-based approach for industrial DC motor monitoring to address these issues. This tool accurately detects and predicts motor malfunctions using the k-Nearest Neighbours (k-NN) machine learning model using sensor data analysis, enabling proactive maintenance. This system streamlines industrial operations by reducing downtime, repair costs, and safety. We tested this algorithm under vertical and horizontal mounting conditions for performance analysis. In fully loaded conditions, horizontal mounting outperformed vertical mounting. The k-NN model detected and predicted motor faults with 95.22% accuracy on the test set. Our AI-enabled tool can improve industrial efficiency and safety, according to this study.
Machine Learning for Fault Detection in DC Motors and the Role of Mounting Configurations
Unexpected motor failures can disrupt industrial processes, affecting efficiency, safety, and profitability. This study introduces an AI-based approach for industrial DC motor monitoring to address these issues. This tool accurately detects and predicts motor malfunctions using the k-Nearest Neighbours (k-NN) machine learning model using sensor data analysis, enabling proactive maintenance. This system streamlines industrial operations by reducing downtime, repair costs, and safety. We tested this algorithm under vertical and horizontal mounting conditions for performance analysis. In fully loaded conditions, horizontal mounting outperformed vertical mounting. The k-NN model detected and predicted motor faults with 95.22% accuracy on the test set. Our AI-enabled tool can improve industrial efficiency and safety, according to this study.
LSTM Based Sign Language Detection System
Sign language recognition plays a crucial role in facilitating communication and inclusivity for individuals with hearing impairments. This research paper shows a novel method for detecting sign language gestures using Long Short-Term Memory (LSTM) networks. By leveraging the sequential data processing capabilities of LSTM networks and with the use of feature engineering an accurate model has been developed to predict sign language gestures. The paper extends in-depth discussions into data collection, data pre-processing and feature engineering techniques used to increase the efficiency of the LSTM model. Keras API for TensorFlow was used for creating a sequential model. The paper also presents a comparative study regarding the change in accuracy resulting from the change in the size of the LSTM layer and the dropout layer ratio. The highest-performing model with an accuracy of 91.28% was used for testing the performance of the model in real-life applications.
LSTM Based Sign Language Detection System
Sign language recognition plays a crucial role in facilitating communication and inclusivity for individuals with hearing impairments. This research paper shows a novel method for detecting sign language gestures using Long Short-Term Memory (LSTM) networks. By leveraging the sequential data processing capabilities of LSTM networks and with the use of feature engineering an accurate model has been developed to predict sign language gestures. The paper extends in-depth discussions into data collection, data pre-processing and feature engineering techniques used to increase the efficiency of the LSTM model. Keras API for TensorFlow was used for creating a sequential model. The paper also presents a comparative study regarding the change in accuracy resulting from the change in the size of the LSTM layer and the dropout layer ratio. The highest-performing model with an accuracy of 91.28% was used for testing the performance of the model in real-life applications.
LSTM Based Sign Language Detection System
Sign language recognition plays a crucial role in facilitating communication and inclusivity for individuals with hearing impairments. This research paper shows a novel method for detecting sign language gestures using Long Short-Term Memory (LSTM) networks. By leveraging the sequential data processing capabilities of LSTM networks and with the use of feature engineering an accurate model has been developed to predict sign language gestures. The paper extends in-depth discussions into data collection, data pre-processing and feature engineering techniques used to increase the efficiency of the LSTM model. Keras API for TensorFlow was used for creating a sequential model. The paper also presents a comparative study regarding the change in accuracy resulting from the change in the size of the LSTM layer and the dropout layer ratio. The highest-performing model with an accuracy of 91.28% was used for testing the performance of the model in real-life applications.
Sand Mining Prediction Using Satellite Images
This research paper focuses on the prediction of sand mining in different areas using satellite images. Illegal sand mining has emerged as a major environmental issue, affecting numerous regions worldwide. Sand mining nowadays has become a curse for society. It should be stopped before it creates a drastic problem for the universe. Some areas are widely affected by illegal sand mining resulting in floods and scarcity of resources. In this paper, YOLOv5( you only look once) is used to train the model. The collection of data is a major problem one is going to face at the start of the project, in the case of a satellite-based image. To feed the algorithm, a dataset is taken that clearly demonstrates the difference between legal and illegal sand mining. After collecting the data, the next step is to label the data and for labeling, several platforms can be used. In this research paper, LabelImg is used for the labeling part.
Sand Mining Prediction Using Satellite Images
This research paper focuses on the prediction of sand mining in different areas using satellite images. Illegal sand mining has emerged as a major environmental issue, affecting numerous regions worldwide. Sand mining nowadays has become a curse for society. It should be stopped before it creates a drastic problem for the universe. Some areas are widely affected by illegal sand mining resulting in floods and scarcity of resources. In this paper, YOLOv5( you only look once) is used to train the model. The collection of data is a major problem one is going to face at the start of the project, in the case of a satellite-based image. To feed the algorithm, a dataset is taken that clearly demonstrates the difference between legal and illegal sand mining. After collecting the data, the next step is to label the data and for labeling, several platforms can be used. In this research paper, LabelImg is used for the labeling part.
Sand Mining Prediction Using Satellite Images
This research paper focuses on the prediction of sand mining in different areas using satellite images. Illegal sand mining has emerged as a major environmental issue, affecting numerous regions worldwide. Sand mining nowadays has become a curse for society. It should be stopped before it creates a drastic problem for the universe. Some areas are widely affected by illegal sand mining resulting in floods and scarcity of resources. In this paper, YOLOv5( you only look once) is used to train the model. The collection of data is a major problem one is going to face at the start of the project, in the case of a satellite-based image. To feed the algorithm, a dataset is taken that clearly demonstrates the difference between legal and illegal sand mining. After collecting the data, the next step is to label the data and for labeling, several platforms can be used. In this research paper, LabelImg is used for the labeling part.
A Novel Approach to Quantify and Compute Gait Analysis Parameters of Quadrupeds
Gait analysis is the study of human and animal locomotion. Analysis of gait is particularly prevalent in developed countries, owing to extensive capital and resources. However, in developing countries such as India, gait analysis devices and instruments are restricted solely to metropolitan cities. Even in Metropolitan Cities, the analysis of human gait is costly. An analysis of quadruped gait is notably absent in developing countries and, if present, is extremely expensive. This creates a financial disparity, in which those in poverty are unable to have a veterinarian kinematically check their Quadruped's gait, while the wealthy are able to do so. The solution presented aims to analyze the gait of all quadrupeds. This mechanism correlates the usage of a Gyroscope, 3-axis accelerometer, and Digital Motion Processor along with graphs plotted using Python's MatPlotLib Library and three-dimensional simulations with an AutoCAD model and simulated using the library Panda3D in a portable, wearable device.
A Novel Approach to Quantify and Compute Gait Analysis Parameters of Quadrupeds
Gait analysis is the study of human and animal locomotion. Analysis of gait is particularly prevalent in developed countries, owing to extensive capital and resources. However, in developing countries such as India, gait analysis devices and instruments are restricted solely to metropolitan cities. Even in Metropolitan Cities, the analysis of human gait is costly. An analysis of quadruped gait is notably absent in developing countries and, if present, is extremely expensive. This creates a financial disparity, in which those in poverty are unable to have a veterinarian kinematically check their Quadruped's gait, while the wealthy are able to do so. The solution presented aims to analyze the gait of all quadrupeds. This mechanism correlates the usage of a Gyroscope, 3-axis accelerometer, and Digital Motion Processor along with graphs plotted using Python's MatPlotLib Library and three-dimensional simulations with an AutoCAD model and simulated using the library Panda3D in a portable, wearable device.
A Novel Approach to Quantify and Compute Gait Analysis Parameters of Quadrupeds
Gait analysis is the study of human and animal locomotion. Analysis of gait is particularly prevalent in developed countries, owing to extensive capital and resources. However, in developing countries such as India, gait analysis devices and instruments are restricted solely to metropolitan cities. Even in Metropolitan Cities, the analysis of human gait is costly. An analysis of quadruped gait is notably absent in developing countries and, if present, is extremely expensive. This creates a financial disparity, in which those in poverty are unable to have a veterinarian kinematically check their Quadruped's gait, while the wealthy are able to do so. The solution presented aims to analyze the gait of all quadrupeds. This mechanism correlates the usage of a Gyroscope, 3-axis accelerometer, and Digital Motion Processor along with graphs plotted using Python's MatPlotLib Library and three-dimensional simulations with an AutoCAD model and simulated using the library Panda3D in a portable, wearable device.
Targeted Extinguishing of Fire Through the Propagation of Acoustic Waves
This research explores the use of sound pressure waves as an innovative method for extinguishing fires. Through theoretical analysis and experiments, it confirms that directed longitudinal sound waves can effectively cool and extinguish fires by depriving them of heat. The study optimizes the process using frequency generator circuits, acoustic lensing, and vortex tubes to concentrate the sound toward the fire source. Computer vision algorithms are implemented to detect fires and align the sound waves accordingly. This acoustic fire extinguishing technique offers a cheaper, environmentally friendly alternative to traditional methods, with the potential to save numerous lives.
Targeted Extinguishing of Fire Through the Propagation of Acoustic Waves
This research explores the use of sound pressure waves as an innovative method for extinguishing fires. Through theoretical analysis and experiments, it confirms that directed longitudinal sound waves can effectively cool and extinguish fires by depriving them of heat. The study optimizes the process using frequency generator circuits, acoustic lensing, and vortex tubes to concentrate the sound toward the fire source. Computer vision algorithms are implemented to detect fires and align the sound waves accordingly. This acoustic fire extinguishing technique offers a cheaper, environmentally friendly alternative to traditional methods, with the potential to save numerous lives.
Targeted Extinguishing of Fire Through the Propagation of Acoustic Waves
This research explores the use of sound pressure waves as an innovative method for extinguishing fires. Through theoretical analysis and experiments, it confirms that directed longitudinal sound waves can effectively cool and extinguish fires by depriving them of heat. The study optimizes the process using frequency generator circuits, acoustic lensing, and vortex tubes to concentrate the sound toward the fire source. Computer vision algorithms are implemented to detect fires and align the sound waves accordingly. This acoustic fire extinguishing technique offers a cheaper, environmentally friendly alternative to traditional methods, with the potential to save numerous lives.
Bathymetric Scanner for Underwater Terrain Survey using Embedded System and TF Mini LiDAR Sensor
Marine Geology and OceanographyExisting methods for mapping deep-sea terrains are inefficient, expensive, and time-consuming. The current multi-beam echo-sounder technique requires a specialized submarine, making it risky and inaccessible. To address these issues, we have developed a remote LiDAR scanning device that can efficiently and cost-effectively map deep-sea environments. Our solution utilizes a 3D-printed, remotely controlled scanner to build detailed 3D models of seafloor terrains. This innovative approach revolutionizes the field of deep-sea mapping, enabling enhanced understanding of the Earth's environment and improved disaster response capabilities.
Bathymetric Scanner for Underwater Terrain Survey using Embedded System and TF Mini LiDAR Sensor
Marine Geology and OceanographyExisting methods for mapping deep-sea terrains are inefficient, expensive, and time-consuming. The current multi-beam echo-sounder technique requires a specialized submarine, making it risky and inaccessible. To address these issues, we have developed a remote LiDAR scanning device that can efficiently and cost-effectively map deep-sea environments. Our solution utilizes a 3D-printed, remotely controlled scanner to build detailed 3D models of seafloor terrains. This innovative approach revolutionizes the field of deep-sea mapping, enabling enhanced understanding of the Earth's environment and improved disaster response capabilities.
Bathymetric Scanner for Underwater Terrain Survey using Embedded System and TF Mini LiDAR Sensor
Marine Geology and OceanographyExisting methods for mapping deep-sea terrains are inefficient, expensive, and time-consuming. The current multi-beam echo-sounder technique requires a specialized submarine, making it risky and inaccessible. To address these issues, we have developed a remote LiDAR scanning device that can efficiently and cost-effectively map deep-sea environments. Our solution utilizes a 3D-printed, remotely controlled scanner to build detailed 3D models of seafloor terrains. This innovative approach revolutionizes the field of deep-sea mapping, enabling enhanced understanding of the Earth's environment and improved disaster response capabilities.
Novel Approach to Analyse Structures to Predict Earthquake Impact in Urban Areas
Recent decades have seen a rise in earthquake risks in urban areas due to urbanization, poor planning, infrastructure issues, and environmental degradation. Urban centers need robust preparedness and emergency plans, including quantifying earthquake effects, especially building losses, correlated with casualties and emergency response. My project aims to predict and assess earthquake impact in urban areas by analyzing building structures, using Google Maps images to calculate dimensions and safe areas. Our algorithm employs image processing and Machine Learning to predict seismic wave effects and determine optimal building distances, reducing risk. With high accuracy and scalability, this model could revolutionize infrastructure planning worldwide.
Novel Approach to Analyse Structures to Predict Earthquake Impact in Urban Areas
Recent decades have seen a rise in earthquake risks in urban areas due to urbanization, poor planning, infrastructure issues, and environmental degradation. Urban centers need robust preparedness and emergency plans, including quantifying earthquake effects, especially building losses, correlated with casualties and emergency response. My project aims to predict and assess earthquake impact in urban areas by analyzing building structures, using Google Maps images to calculate dimensions and safe areas. Our algorithm employs image processing and Machine Learning to predict seismic wave effects and determine optimal building distances, reducing risk. With high accuracy and scalability, this model could revolutionize infrastructure planning worldwide.
Novel Approach to Analyse Structures to Predict Earthquake Impact in Urban Areas
Recent decades have seen a rise in earthquake risks in urban areas due to urbanization, poor planning, infrastructure issues, and environmental degradation. Urban centers need robust preparedness and emergency plans, including quantifying earthquake effects, especially building losses, correlated with casualties and emergency response. My project aims to predict and assess earthquake impact in urban areas by analyzing building structures, using Google Maps images to calculate dimensions and safe areas. Our algorithm employs image processing and Machine Learning to predict seismic wave effects and determine optimal building distances, reducing risk. With high accuracy and scalability, this model could revolutionize infrastructure planning worldwide.
Find your nearest innovation lab
These awards reflect projects that pushed my boundaries, told deeper stories, and caught the attention of people who care about what visuals can say.
Find your nearest innovation lab
These awards reflect projects that pushed my boundaries, told deeper stories, and caught the attention of people who care about what visuals can say.