Proceedings of the IoT AND LiDAR Technologies in Healthcare Workshop (ILTH 2024)
Conference: Proceedings of the IoT AND LiDAR Technologies in Healthcare Workshop (ILTH 2024)
Date: 25-29 November 2024
Location: Hyderabad, India (Hybrid)
Website: https://scis.uohyd.ac.in/People/profile/files/nks_IoT_LiDAR_workshop_2024 The IoT and LiDAR Technologies in Healthcare Workshop as part of the SPARC Project: IoT based Sensor Analytics to Enhance the Quality of Life for elderly population (P2354) explored the integration of Internet of Things (IoT) and Light Detection and Ranging (LiDAR) technologies in revolutionizing healthcare systems. IoT enables seamless connectivity between medical devices, providing real-time data and monitoring, which enhances patient care and treatment outcomes. This interconnected network allows for improved diagnostics, remote patient monitoring, and efficient healthcare delivery. Meanwhile, LiDAR, known for its precision in mapping and 3D scanning, offers groundbreaking applications in medical imaging, robotic surgery, and elderly care. The workshop delved into the synergistic potential of these technologies, aiming to foster innovation in predictive healthcare, automation, and data-driven patient management. By advancing these cutting-edge tools, the healthcare sector can expect improved diagnostics, patient safety, and operational efficiency. The five-day workshop provided the hand-on activities to ensure that attendees discuss and understand each topic and apply the information to their own requirements. This workshop brought together experts and 150 participants from Academia, Research Scholars, UG, PG students, faculty members / professionals & industry personnel working in the concerned / allied discipline to explore the fundamentals and applications of IoT and LiDAR technologies. Led by Dr. Nagender Kumar S. (University of Hyderabad) and Dr. Anuroop Gaddam (Deakin University), Dr. Nagarajan Ganapathy (IIT Hyderabad) the event covered theoretical concepts, hands-on demonstrations, and real-world implementations of LiDAR systems and Healthcare systems and applications. Day 1: Introduction to IoT and LiDAR Technologies: The workshop commenced with registration and a welcome coffee session, followed by opening remarks that outlined the workshop objectives and schedule. Morning Session: Introduction to IoT and LiDAR technologies and Overview of SPARC grant and project objectives. Afternoon Session: Lab Session: Introduction to the Unitree 4D LiDAR L2 Sensor, Sensor calibration and data acquisition demonstration and Hands-on Session: Real-time data acquisition in fieldwork scenarios. Participants engaged in practical exercises to calibrate sensors, collect LiDAR data, and analyze its application in real-world environments. This foundation set the stage for the upcoming days, which would dive deeper into data processing, analytics, and industry applications of these technologies. Day 2: The second day of the workshop focused on smart healthcare platforms, emphasizing personalized support, multimodal signal processing, and real-time data acquisition. Led by Dr. Nagarajan Ganapathy (IIT Hyderabad), participants explored how smart systems can enhance health monitoring and independent living. Morning Session:Overview of Smart Healthcare Platforms and Discussion on evidence-based personalized support Smart systems for healthy and independent living in private spaces Afternoon Session: Introduction to multimodal signal quality assessment. Fusion strategies for integrating multiple data sources. Hands-on Session with Real-time multimodal data acquisition in wild (out-of-lab) scenarios and Practical challenges in collecting and analyzing healthcare data This session provided valuable technical insights and hands-on experience, enabling participants to understand the potential of AI-driven healthcare platforms in real-world applications. Day 3:The third day of the workshop focused on deep learning applications for anomaly detection, particularly in LiDAR-based gait analysis. Participants explored CNN-LSTM models, real-world challenges, and practical training techniques for detecting gait disorders. Deep Learning for Anomaly Detection in LiDAR Data Understanding how deep learning enhances LiDAR-based anomaly detection Discussion: Challenges in Real-world Deep Learning Applications. Understanding CNN-LSTM models and their role in gait anomaly detection. Case studies on integrating deep learning with LiDAR. Training a CNN-LSTM Model for Gait Anomaly Detection, Hands-on training for detecting gait disorders Practical implementation of deep learning models with LiDAR data. This session provided valuable insights into machine learning techniques for healthcare and mobility monitoring, preparing participants for real-world AI-driven anomaly detection applications. Day 5:The final day of the workshop explored multi-modal feature learning for Visual Question Answering (VQA) and the future of LiDAR and IoT in healthcare. It provided a platform for participants to engage in discussions, share insights, and explore emerging research trends. Morning Session: Understanding multi-modal AI models for interpreting LiDAR and visual data Applications of VQA in healthcare and smart environments, Future Research Directions in LiDAR and IoT, Open discussion on current trends, challenges, and future research. Afternoon Session: Feedback & Organizing Committee Meeting, Workshop reflections, participant feedback, and closing remarks. Workshop Proceedings The workshop on IoT and LiDAR Technologies for Healthcare within the theme of Smart Interactive Outdoor Environments as a Healthcare Intervention aligns strongly with multiple United Nations Sustainable Development Goals (SDGs). The following SDGs contributes to global sustainability and community well-being: SDG 3: Good Health and Well-being Improving Healthcare Access: IoT-based smart outdoor environments enhance accessibility for the elderly and disabled, providing real-time health monitoring and emergency response. Disease Prevention & Early Diagnosis: LiDAR can track movement patterns to identify health risks such as falls through GAIT monitoring, while IoT sensors monitor vital signs and environmental conditions that influence health outcomes. SDG 9: Industry, Innovation, and Infrastructure Smart Cities & Infrastructure: The integration of IoT sensors and LiDAR into urban environments enhances accessibility, making cities safer and more inclusive for vulnerable populations. Data-Driven Decision Making: Real-time analytics from IoT and LiDAR can assist in designing health-conscious urban spaces, improving air quality, and reducing accident-prone zones. SDG 11: Sustainable Cities and Communities Enhancing Livability: Smart outdoor environments equipped with AI-driven IoT and LiDAR technologies foster safe, healthy, and inclusive public spaces for all age groups. Smart Mobility for Disabled & Elderly: LiDAR-assisted navigation and IoT-based mobility aids increase accessibility and promote independent movement in urban settings. The integration of IoT and LiDAR in healthcare-focused outdoor environments directly contributes to sustainable urban development, improved health outcomes, and a more resilient healthcare system. By leveraging cutting-edge technology, the workshop serves as a catalyst for smart, inclusive, and sustainable community well-being. Background and Motivation: The demographic profile of India is now witnessing changes, in 2011 the aging population was at 8.6% and it is predicted that the population of elderly in India could be around 19% of total population by the year 2050. This will only mean that caring for the elderly and all aspects of geriatric services would come under greater focus in the coming years.Population ageing is an inevitable, irreversible demographic reality associated with decline in health and quality of life. The Government of India introduced National Policy on Older Persons (NPOP), Integrated Programme for the Older Persons (IPOP) to tackle this issue, improve the quality of life of the elderly. While increasing longevity is a matter to celebrate, various studies have found multiple illnesses and disabilities linked to the advancement of age.The ability to walk while performing concurrent cognitive, motor tasks; and the ability to negotiate unpredictable terrain is a key aspect for elderly in accessing the local community and having active healthy aging. Walking speed (Gait) below 0.4meters/second indicates a loss of confidence in walking, leading to increased social isolation and reduced mental, physical health.Currently, gait assessment of elderly is often done in costly clinical settings thus limiting access to this service for many elderly people in the community. Enabling communities with enhanced services to improve health, social wellbeing outcomes of elderly through the development of unobtrusive technologies embedded in outdoor landscapes to monitor individuals’ gait and identify patterns of gait change is paramount. The aim of the workshop on IoT and LiDAR Technologies for Healthcare is to explore and demonstrate how smart interactive outdoor environments can be leveraged as healthcare interventions to improve the quality of life in communities. Objectives: 1. Understanding IoT and LiDAR Applications in Healthcare: ○ Introduce IoT-based health monitoring systems for real-time tracking of environmental and physiological data. ○ Demonstrate LiDAR-based movement analysis for fall detection, pedestrian safety, and accessibility improvements. 2. Promoting Smart & Inclusive Public Spaces: ○ Discuss how sensor-based urban planning can improve accessibility for elderly and disabled individuals. ○ Explore the role of automated emergency response systems in outdoor environments. 3. Enhancing Preventive Healthcare & Well-being: ○ Showcase how IoT-driven environmental monitoring (air quality, UV exposure, temperature) can mitigate health risks. ○ Highlight wearable IoT technologies for chronic disease management in smart urban settings. 4. Aligning with Sustainable Development Goals (SDGs): ○ Address SDG 3 (Good Health and Well-being) by enhancing preventive healthcare solutions. ○ Support SDG 11 (Sustainable Cities and Communities) through AI-driven smart city planning. ○ Foster SDG 9 (Industry, Innovation, and Infrastructure) by encouraging research and development in smart healthcare. 5. Encouraging Cross-disciplinary Collaboration: ○ Bring together healthcare professionals, urban planners, engineers, and policymakers to create integrated healthcare solutions. ○ Foster public-private partnerships to advance IoT and LiDAR research for sustainable healthcare applications. Outcome Expectations: ● Development of pilot projects integrating IoT and LiDAR in public healthcare settings. ● Creation of policy recommendations for implementing smart health interventions in urban environments. ● Strengthened collaborations between academia, industry, and government for future research and funding. The workshop ultimately aims to bridge technology and healthcare, ensuring that communities benefit from data-driven, sustainable, and inclusive healthcare solutions. Summary and Conclusion Chapter 1 provides the Introduction about the advancements in science and technology for the development of Healthcare applications. Chapters 2, 3, and 4 describe the science and technology utilization of digital tools that can empower patients and doctors to manage their well-being and address chal lenges with new approaches. There is an excellent discussion around user-driven tech nology, along with the tools developed by our team over the years, namely, Patient Journey Records (PaJR) and Case-Based Blended Learning Ecosystem. These models have encouraged us to move forward with a 360-degree approach in medicine, which traditional old models lack. Chapters 5, 6, and 7 present the impact of IoT on patient monitoring, specifically on gait monitoring and analysis. This chapter examines how the Internet of Things (IoT) transforms the healthcare landscape by enabling real-time patient monitoring. It discusses various IoT devices, such as wearables and smart sensors, and their role in enhancing patient care, improving outcomes, and reducing hospital visits. The presentation of fundamental terminologies, the methodology used to monitor the human gait parameters, and the corresponding science and technology are presented. Chapters 8, 9, and 10 present the integration of LiDAR technology in healthcare. They involve exploring novel applications of LiDAR technology in the medical field. They show how LiDAR can be used for precise imaging and diagnostics and its potential for monitoring health conditions through non-invasive techniques. In conclusion, the book presents the SPARC sponsored workshop proceedings in ten chapters providing information related to healthcare, Internet of Things, and the usage of LiDAR sensors for healthcare applications.
Date: 25-29 November 2024
Location: Hyderabad, India (Hybrid)
Website: https://scis.uohyd.ac.in/People/profile/files/nks_IoT_LiDAR_workshop_2024 The IoT and LiDAR Technologies in Healthcare Workshop as part of the SPARC Project: IoT based Sensor Analytics to Enhance the Quality of Life for elderly population (P2354) explored the integration of Internet of Things (IoT) and Light Detection and Ranging (LiDAR) technologies in revolutionizing healthcare systems. IoT enables seamless connectivity between medical devices, providing real-time data and monitoring, which enhances patient care and treatment outcomes. This interconnected network allows for improved diagnostics, remote patient monitoring, and efficient healthcare delivery. Meanwhile, LiDAR, known for its precision in mapping and 3D scanning, offers groundbreaking applications in medical imaging, robotic surgery, and elderly care. The workshop delved into the synergistic potential of these technologies, aiming to foster innovation in predictive healthcare, automation, and data-driven patient management. By advancing these cutting-edge tools, the healthcare sector can expect improved diagnostics, patient safety, and operational efficiency. The five-day workshop provided the hand-on activities to ensure that attendees discuss and understand each topic and apply the information to their own requirements. This workshop brought together experts and 150 participants from Academia, Research Scholars, UG, PG students, faculty members / professionals & industry personnel working in the concerned / allied discipline to explore the fundamentals and applications of IoT and LiDAR technologies. Led by Dr. Nagender Kumar S. (University of Hyderabad) and Dr. Anuroop Gaddam (Deakin University), Dr. Nagarajan Ganapathy (IIT Hyderabad) the event covered theoretical concepts, hands-on demonstrations, and real-world implementations of LiDAR systems and Healthcare systems and applications. Day 1: Introduction to IoT and LiDAR Technologies: The workshop commenced with registration and a welcome coffee session, followed by opening remarks that outlined the workshop objectives and schedule. Morning Session: Introduction to IoT and LiDAR technologies and Overview of SPARC grant and project objectives. Afternoon Session: Lab Session: Introduction to the Unitree 4D LiDAR L2 Sensor, Sensor calibration and data acquisition demonstration and Hands-on Session: Real-time data acquisition in fieldwork scenarios. Participants engaged in practical exercises to calibrate sensors, collect LiDAR data, and analyze its application in real-world environments. This foundation set the stage for the upcoming days, which would dive deeper into data processing, analytics, and industry applications of these technologies. Day 2: The second day of the workshop focused on smart healthcare platforms, emphasizing personalized support, multimodal signal processing, and real-time data acquisition. Led by Dr. Nagarajan Ganapathy (IIT Hyderabad), participants explored how smart systems can enhance health monitoring and independent living. Morning Session:Overview of Smart Healthcare Platforms and Discussion on evidence-based personalized support Smart systems for healthy and independent living in private spaces Afternoon Session: Introduction to multimodal signal quality assessment. Fusion strategies for integrating multiple data sources. Hands-on Session with Real-time multimodal data acquisition in wild (out-of-lab) scenarios and Practical challenges in collecting and analyzing healthcare data This session provided valuable technical insights and hands-on experience, enabling participants to understand the potential of AI-driven healthcare platforms in real-world applications. Day 3:The third day of the workshop focused on deep learning applications for anomaly detection, particularly in LiDAR-based gait analysis. Participants explored CNN-LSTM models, real-world challenges, and practical training techniques for detecting gait disorders. Deep Learning for Anomaly Detection in LiDAR Data Understanding how deep learning enhances LiDAR-based anomaly detection Discussion: Challenges in Real-world Deep Learning Applications. Understanding CNN-LSTM models and their role in gait anomaly detection. Case studies on integrating deep learning with LiDAR. Training a CNN-LSTM Model for Gait Anomaly Detection, Hands-on training for detecting gait disorders Practical implementation of deep learning models with LiDAR data. This session provided valuable insights into machine learning techniques for healthcare and mobility monitoring, preparing participants for real-world AI-driven anomaly detection applications. Day 5:The final day of the workshop explored multi-modal feature learning for Visual Question Answering (VQA) and the future of LiDAR and IoT in healthcare. It provided a platform for participants to engage in discussions, share insights, and explore emerging research trends. Morning Session: Understanding multi-modal AI models for interpreting LiDAR and visual data Applications of VQA in healthcare and smart environments, Future Research Directions in LiDAR and IoT, Open discussion on current trends, challenges, and future research. Afternoon Session: Feedback & Organizing Committee Meeting, Workshop reflections, participant feedback, and closing remarks. Workshop Proceedings The workshop on IoT and LiDAR Technologies for Healthcare within the theme of Smart Interactive Outdoor Environments as a Healthcare Intervention aligns strongly with multiple United Nations Sustainable Development Goals (SDGs). The following SDGs contributes to global sustainability and community well-being: SDG 3: Good Health and Well-being Improving Healthcare Access: IoT-based smart outdoor environments enhance accessibility for the elderly and disabled, providing real-time health monitoring and emergency response. Disease Prevention & Early Diagnosis: LiDAR can track movement patterns to identify health risks such as falls through GAIT monitoring, while IoT sensors monitor vital signs and environmental conditions that influence health outcomes. SDG 9: Industry, Innovation, and Infrastructure Smart Cities & Infrastructure: The integration of IoT sensors and LiDAR into urban environments enhances accessibility, making cities safer and more inclusive for vulnerable populations. Data-Driven Decision Making: Real-time analytics from IoT and LiDAR can assist in designing health-conscious urban spaces, improving air quality, and reducing accident-prone zones. SDG 11: Sustainable Cities and Communities Enhancing Livability: Smart outdoor environments equipped with AI-driven IoT and LiDAR technologies foster safe, healthy, and inclusive public spaces for all age groups. Smart Mobility for Disabled & Elderly: LiDAR-assisted navigation and IoT-based mobility aids increase accessibility and promote independent movement in urban settings. The integration of IoT and LiDAR in healthcare-focused outdoor environments directly contributes to sustainable urban development, improved health outcomes, and a more resilient healthcare system. By leveraging cutting-edge technology, the workshop serves as a catalyst for smart, inclusive, and sustainable community well-being. Background and Motivation: The demographic profile of India is now witnessing changes, in 2011 the aging population was at 8.6% and it is predicted that the population of elderly in India could be around 19% of total population by the year 2050. This will only mean that caring for the elderly and all aspects of geriatric services would come under greater focus in the coming years.Population ageing is an inevitable, irreversible demographic reality associated with decline in health and quality of life. The Government of India introduced National Policy on Older Persons (NPOP), Integrated Programme for the Older Persons (IPOP) to tackle this issue, improve the quality of life of the elderly. While increasing longevity is a matter to celebrate, various studies have found multiple illnesses and disabilities linked to the advancement of age.The ability to walk while performing concurrent cognitive, motor tasks; and the ability to negotiate unpredictable terrain is a key aspect for elderly in accessing the local community and having active healthy aging. Walking speed (Gait) below 0.4meters/second indicates a loss of confidence in walking, leading to increased social isolation and reduced mental, physical health.Currently, gait assessment of elderly is often done in costly clinical settings thus limiting access to this service for many elderly people in the community. Enabling communities with enhanced services to improve health, social wellbeing outcomes of elderly through the development of unobtrusive technologies embedded in outdoor landscapes to monitor individuals’ gait and identify patterns of gait change is paramount. The aim of the workshop on IoT and LiDAR Technologies for Healthcare is to explore and demonstrate how smart interactive outdoor environments can be leveraged as healthcare interventions to improve the quality of life in communities. Objectives: 1. Understanding IoT and LiDAR Applications in Healthcare: ○ Introduce IoT-based health monitoring systems for real-time tracking of environmental and physiological data. ○ Demonstrate LiDAR-based movement analysis for fall detection, pedestrian safety, and accessibility improvements. 2. Promoting Smart & Inclusive Public Spaces: ○ Discuss how sensor-based urban planning can improve accessibility for elderly and disabled individuals. ○ Explore the role of automated emergency response systems in outdoor environments. 3. Enhancing Preventive Healthcare & Well-being: ○ Showcase how IoT-driven environmental monitoring (air quality, UV exposure, temperature) can mitigate health risks. ○ Highlight wearable IoT technologies for chronic disease management in smart urban settings. 4. Aligning with Sustainable Development Goals (SDGs): ○ Address SDG 3 (Good Health and Well-being) by enhancing preventive healthcare solutions. ○ Support SDG 11 (Sustainable Cities and Communities) through AI-driven smart city planning. ○ Foster SDG 9 (Industry, Innovation, and Infrastructure) by encouraging research and development in smart healthcare. 5. Encouraging Cross-disciplinary Collaboration: ○ Bring together healthcare professionals, urban planners, engineers, and policymakers to create integrated healthcare solutions. ○ Foster public-private partnerships to advance IoT and LiDAR research for sustainable healthcare applications. Outcome Expectations: ● Development of pilot projects integrating IoT and LiDAR in public healthcare settings. ● Creation of policy recommendations for implementing smart health interventions in urban environments. ● Strengthened collaborations between academia, industry, and government for future research and funding. The workshop ultimately aims to bridge technology and healthcare, ensuring that communities benefit from data-driven, sustainable, and inclusive healthcare solutions. Summary and Conclusion Chapter 1 provides the Introduction about the advancements in science and technology for the development of Healthcare applications. Chapters 2, 3, and 4 describe the science and technology utilization of digital tools that can empower patients and doctors to manage their well-being and address chal lenges with new approaches. There is an excellent discussion around user-driven tech nology, along with the tools developed by our team over the years, namely, Patient Journey Records (PaJR) and Case-Based Blended Learning Ecosystem. These models have encouraged us to move forward with a 360-degree approach in medicine, which traditional old models lack. Chapters 5, 6, and 7 present the impact of IoT on patient monitoring, specifically on gait monitoring and analysis. This chapter examines how the Internet of Things (IoT) transforms the healthcare landscape by enabling real-time patient monitoring. It discusses various IoT devices, such as wearables and smart sensors, and their role in enhancing patient care, improving outcomes, and reducing hospital visits. The presentation of fundamental terminologies, the methodology used to monitor the human gait parameters, and the corresponding science and technology are presented. Chapters 8, 9, and 10 present the integration of LiDAR technology in healthcare. They involve exploring novel applications of LiDAR technology in the medical field. They show how LiDAR can be used for precise imaging and diagnostics and its potential for monitoring health conditions through non-invasive techniques. In conclusion, the book presents the SPARC sponsored workshop proceedings in ten chapters providing information related to healthcare, Internet of Things, and the usage of LiDAR sensors for healthcare applications.