Research Vision:
Building on my extensive work in RF-sensing-based human activity monitoring, my vision is to revolutionize real-time, scalable, and cost-effective sensing systems that integrate seamlessly into everyday life. I aim to broaden the scope of my investigations across diverse domains and environments, developing technologies that not only monitor human activities but also deepen our understanding of behavior in homes, public spaces, outdoor settings, and even hazardous environments.
Recent advancements in RF sensing, radar, and sensor-based technologies have opened new avenues for non-intrusive, real-time monitoring. However, challenges such as real-time processing, robustness in complex conditions, and affordability still impede widespread deployment. My research addresses these challenges by focusing on practical and scalable solutions applicable to healthcare, security, smart homes, and autonomous systems.
A central element of my vision is the integration of RF sensing with emerging technologies like radar, camera, and lidar systems. In the context of Advanced Driver Assistance Systems (ADAS), this fusion paves the way for cost-effective alternatives to expensive sensors, contributing to safer and more efficient autonomous vehicles.
Furthermore, my work extends into multidisciplinary areas such as environmental sensing and disaster response. By combining RF sensing with modalities such as polarimetric imaging, gas sensors, and acoustic arrays, I strive to create innovative solutions capable of operating in challenging settings—including underground spaces, dense forests, and disaster-stricken areas.
Collaborating with esteemed institutions like the National Science Foundation (NSF), Air Force Research Laboratory (AFRL), the Department of Defense (DoD), and the United States Department of Agriculture (USDA), my ultimate goal is to develop sensing technologies that improve quality of life, enhance safety and security, and offer groundbreaking solutions to pressing societal and scientific challenges. Through an interdisciplinary approach, creativity, and relentless passion for research, I am dedicated to advancing the frontiers of sensing technology and fostering collaborations across academia, industry, and government.
1. Real-Time Indoor Activity Monitoring
I am developing a radar-based system for real-time monitoring of human activities indoors. By leveraging techniques such as angular separation and range gating, the system constructs detailed radar data cubes to detect multiple targets and accurately estimate human poses. Key elements include:
Efficient Algorithm Development: Refining feature extraction from radar data to ensure real-time performance.
Hardware Integration: Seamlessly combining software with radar hardware and reducing latency via optimized processing pipelines and GPU acceleration.
Targeted Applications: Tailored trials in smart homes and healthcare settings, with special focus on monitoring infants, babies, and the elderly—all while addressing privacy and ethical concerns.
2. Wi-Fi-Based Cost-Effective Sensing
Building on radar-based solutions, I am exploring the use of ubiquitous Wi-Fi signals for human activity monitoring. This approach harnesses Wi-Fi Channel State Information (CSI) through low-cost platforms like software-defined radios (SDRs) and Raspberry Pi devices. Key aspects include:
CSI Data Interpretation: Developing novel methods for accurate activity recognition from Wi-Fi signals.
Angle-of-Arrival Estimation: Using existing Wi-Fi antennas to track movements precisely.
Broad Applications: Delivering a scalable and affordable solution for smart homes, elderly care, and security.
3. RF-Sensing for Enhanced Human-Machine Interaction in Public Spaces
I envision transforming public spaces—such as airports, shopping malls, and office buildings—through advanced RF-sensing. By tracking movement patterns and behavioral cues, this research aims to:
Integrate Multiple Modalities: Combine RF-sensing with cameras and microphones for a comprehensive understanding of human behavior.
Improve Public Experience: Enhance customer service, bolster security through anomaly detection, and streamline navigation in crowded environments.
Real-Time Adaptability: Develop robust machine learning models capable of interpreting complex behavioral data on the fly.
4. Multimodal Sensing in Challenging and Hazardous Environments
My research extends to developing a multimodal sensing system for environments where traditional sensors struggle. By integrating:
Diverse Sensing Technologies: Combining RF-sensing, polarimetric imaging, gas sensors, and acoustic arrays,
Autonomous Platforms: Equipping unmanned ground vehicles (UGVs) to navigate and map complex, dynamic spaces,
Advanced Sensor Fusion: Leveraging Kalman filtering, Bayesian inference, and neural network-based processing to detect and classify hazards in real time,
this work aims to enhance situational awareness and decision-making for first responders and military personnel.
Advancing ADAS Systems: A Multi-Sensor Approach
In collaboration with the Alabama Transportation Institute (ATI), I am working on a next-generation Advanced Driver Assistance System (ADAS) that integrates short- and long-range radar, lidar, and cameras. The project focuses on:
Sensor Fusion: Optimizing object detection, tracking, and decision-making across diverse environmental conditions—daylight, nighttime, stormy, rainy, and foggy.
Cost-Effective Solutions: Investigating radar-based alternatives to expensive lidar systems, particularly in low-visibility conditions.
Traffic Sign Recognition: Developing algorithms for accurate and responsive traffic sign detection and segmentation.
Innovative Soil Moisture Monitoring for Agriculture
Partnering with institutions like the Alabama Agricultural Experiment Station and the Winfred Thomas Agricultural Research Station, I am combining Ground Penetrating Radar (GPR) and Synthetic Aperture Radar (SAR) technologies to advance soil moisture monitoring. This research aims to:
Field-Level Precision: Utilize drone-mounted GPR systems for high-resolution, real-time moisture measurements.
Regional Analysis: Leverage SAR imaging to capture soil moisture variations over large agricultural areas.
Sustainable Agriculture: Provide farmers with actionable insights for optimized irrigation and enhanced crop health, in line with sustainable farming practices supported by USDA’s National Institute of Food and Agriculture (NIFA).
These research thrusts and collaborations form the foundation of my ongoing commitment to developing innovative, practical sensing systems that address real-world challenges across multiple domains.