Advancing Pathogen Elimination: A Self-Driving UV Robot System Equipped with Sophisticated Navigation and Smart Disinfection Methods
Disciplines
Robotics
Abstract (300 words maximum)
UV-based mobile robots have proven effective in eliminating pathogens, there is an increasing need to enhance their functionality and guarantee their security. This work explores how digital twin technology can be used to improve the performance and dependability of UV-based mobile robots designed to disinfect pathogens. Virtual twins, or virtual copies of actual systems or devices, offer a unique chance to model and examine UV robot behavior in real time. We can properly mimic the mobility, UV emission patterns, and pathogen disinfection efficacy of UV-based mobile robots by building digital twins of them. This procedure creates a dynamic feedback loop that allows robot algorithms and parameters to be adjusted continuously, leading to continuous progress. This reduces the possibility of UV exposure threats to people and the environment while also improving disinfection efficiency. Our work investigates how sensor data, ambient parameters, and UV characteristics can be combined to create an accurate digital twin for UV robots. We can improve the robot's ability to adapt to different surfaces and environments while using less energy by incorporating real-world data. Furthermore, in order to facilitate adaptive decision-making based on real-time pathogen identification and guarantee a thorough and efficient disinfection procedure, we look into the integration of machine learning techniques. The utilization of digital twins in UV-based mobile robots has the potential to transform the field of pathogen disinfection through enhanced performance, reduced operational hazards, and the ability to operate autonomously. The research has the potential to have a significant impact on the protection of public health, public safety, and infection control protocols in a variety of contexts, such as public transportation, healthcare institutions, and workplaces. The world is facing persistent health difficulties, but the combination of UV robot technology and digital twin technology has the potential to create safe environments from harmful diseases.
Academic department under which the project should be listed
SPCEET - Robotics and Mechatronics Engineering
Primary Investigator (PI) Name
Muhammad Hassan Tanveer
Advancing Pathogen Elimination: A Self-Driving UV Robot System Equipped with Sophisticated Navigation and Smart Disinfection Methods
UV-based mobile robots have proven effective in eliminating pathogens, there is an increasing need to enhance their functionality and guarantee their security. This work explores how digital twin technology can be used to improve the performance and dependability of UV-based mobile robots designed to disinfect pathogens. Virtual twins, or virtual copies of actual systems or devices, offer a unique chance to model and examine UV robot behavior in real time. We can properly mimic the mobility, UV emission patterns, and pathogen disinfection efficacy of UV-based mobile robots by building digital twins of them. This procedure creates a dynamic feedback loop that allows robot algorithms and parameters to be adjusted continuously, leading to continuous progress. This reduces the possibility of UV exposure threats to people and the environment while also improving disinfection efficiency. Our work investigates how sensor data, ambient parameters, and UV characteristics can be combined to create an accurate digital twin for UV robots. We can improve the robot's ability to adapt to different surfaces and environments while using less energy by incorporating real-world data. Furthermore, in order to facilitate adaptive decision-making based on real-time pathogen identification and guarantee a thorough and efficient disinfection procedure, we look into the integration of machine learning techniques. The utilization of digital twins in UV-based mobile robots has the potential to transform the field of pathogen disinfection through enhanced performance, reduced operational hazards, and the ability to operate autonomously. The research has the potential to have a significant impact on the protection of public health, public safety, and infection control protocols in a variety of contexts, such as public transportation, healthcare institutions, and workplaces. The world is facing persistent health difficulties, but the combination of UV robot technology and digital twin technology has the potential to create safe environments from harmful diseases.