Research
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Research Interests
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Autonomous Navigation Technologies: Aerial/Terrestrial, Autonomous Navigation Testbed/Living Lab,Drone Based Sensing, Wireless communications, Wireless sensor networks, UAV-based sensing, Embedded systems, Cyber Physical Systems/Internet of Things (CPS/IoT), Converged network modelling, Energy efficiency, Green communications.
The research work mainly focuses on the following areas:
· AI-based Aerial/Terrestrial traffic sensing using LiDAR point cloud processing - Object Detection and Tracking which involves
o Object segmentation (clustering)
o Classification of objects e.g. cars, pedestrians, cyclists etc.
o Finding vehicle count
o Speed detection
o Intrusion detection.
· High Throughput Crop Phenotyping using UAV based sensor like Hyperspectral, multispectral and RGB camera, for the following
o Standard operating Procedure for capturing of images from UAV
o Calculation of phenotypic traits (LAI, plant count, 50% flowering, plant height, tassel detection etc.,) using AI/ML techniques
o Weed/Crop segmentation
o Stress classification
o IoT network for monitoring soil moisture and soil temperature.
· IoT enabled artificial intelligence-based guided and automated diagnostic system for ultrasound imaging systems which ensure that a semi-skilled person with minimum expertise can provide non-invasive imaging diagnostic in remote healthcare. AI based healthcare includes the following:
o Developing algorithm for quantification of fatty liver using ultrasound imaging
o Organ detection in ultrasound imaging
o Abnormality detection in kidney ultrasound image.
· The brain-controlled IoT environments (BCE) which provides the communication between the brain and the external world and involves the following:
o Developing sophisticated AI based algorithms to detect the performed MI task by the user
o Efficiently Communicating the intelligent decision engine’s command to actuate the surrounding environments by using a low power IoT network.
· Developing algorithm for enhancing cyber security in IoT infrastructure including the following:
o Studying the different attacks in IoT networks
o Mitigating the attacks by exploring physical layer in addition to computational complexity based security algorithms
o Analysing the vulnerabilities in IoT communication standards like NBIoT, IEEE 802.15.4 etc.
· Enhancing the throughput in dense traffic IoT networks by developing AI-based channel access mechanisms and proposing adaptive communication strategies for optimal performance.
· Wireless Sensor Networks: Actively involved in
o Design and development of cost effective multiple architecture solutions for air pollution monitoring system
o Test bed deployment
o Data collection, interpretation and statistical modeling
o Smart/Green Buildings
o Mobile sensor networks.
· Cognitive Radio Networks:
o Cognitive spectrum sensing, Boundary detection
o Green/Energy Efficient Communication technologies.