I am an assistant professor in the Department of CSE at IIT Madras. My research interests are in designing IoT-based/mobile systems that interact with and interpret (sense) the physical world, spanning both algorithm design as well as end-to-end system prototyping.
Harness the versatility of RF-based sensing (RFID, ultra
wideband, millimeter waves) to address challenges in location estimation, smart spaces, surveillance and RF communications. Such sensing is often aided by autonomous mobile
platforms like robots or drones that makes the process ubiqutious, scalable and time efficient, often in challenging environments like emergency situations.
With advancement in the field of aerial robotics, unmanned aerial vehicles (UAVs) have gained wide applicability providing an array of "on-demand" services. We explore the capabilities of UAVs to host wireless networks that are lightweight, flexible, portable and easy to deploy on demand. This finds great applicability where network infrastructure is absent/destroyed, sparingly present or additional capacity is required. Such networks, due to their ubiquitous nature, are really helpful in disaster scenarios that can aid first responders in an emergency.
With millions of apps in the play-store, their diverse requirements for resources and a sky-rocketing user-base, guaranteeing good Quality of Experience (QoE) has become a challenge particularly in resource constrained and highly congested wireless networks. With a multitude of radios available in newer generation smartphones (WiFi, 3G, 4G, LTE) and accessibility to multiple cellular ISPs simultaneously (dual SIMs, Google Fi) a key question we ask is, "Which network is just enough for a good QoE and yet save on the phone's battery, data cost etc and be fair to other users of the network?".
Demo Video of the SkyLiTE network. SkyLiTE is an UAV based LTE network.
Spectrum databases maintain geographic availability of unused RF spectrum or whitespaces. However, they are often inaccurate leading to inefficient spectrum usage. Hence such databases need to be intelligently augmented by real spectrum measurements wherever and whenever necessary. Further, to make spectrum sensing scalable, pervasive and potentially crowdsourced, we create 'mobile spectrum sensing' devices by interfacing low cost, portable SDRs to smartphones.
We are broadly interested in designing IoT-based/mobile systems that interact with and interpret (sense) the physical world, spanning both algorithm design as well as system prototyping. Our research focuses on building intelligent sensing platforms, through the use of heterogeneous sensor modalities, to solve real-world problems - e.g., indoor localization, smarthome applications or intelligent human computer interaction interfaces.