My research work spans multiple areas including computer networks, wireless communication, mobile computing, sensor networks and system building. Over the time I contributed to the following projects:

Activity Sensing using Ceiling Photosensors

This paper explores the feasibility of tracking motion and activities of humans using visible light. Shadows created by casting visible light on humans and objects are sensed using sensors that are embedded along with the light sources. Existing Visible Light Sensing (VLS) techniques require either light sensors deployed on the floor or a person carrying a device. Our approach seeks to measure light reflected off the floor to achieve an entirely device-free and light-source based system. We co-locate photosensors with LED light sources to observe the changes in light level occurring on the floor.

Over-the-air TV Detection using Mobile Phones

This work introduces a mobile sensing technique to detect a nearby active television, the channel it is tuned to, and whether it is receiving this channel over the air. This technique can find applications in tracking TV viewership, second screen services and advertising, as well as improving the efficiency of TV whitespace spectrum usage. The technique uses a three-stage detection process. It first uses a probabilistic model on audio recordings from mobile phones to detect likely TV sounds in the area. It then correlates the recording with known TV channel audio to identify the channel and improve detection robustness. Finally, it applies a latency analysis to determine whether programming is received over-the-air or through alternate means such as cable or satellite TV.


Large-Scale Framework for Cognitive Radio Routing Protocols Testing

Building testbeds for Cognitive Radio Networks (CRNs) is one of the main challenges that can affect the wide deployability of such networks. In this project we develop a framework that facilitates the development of cost-efficient large-scale CRNs routing protocols testbeds. The framework allows the designers to focus on the CRNs routing protocols by abstracting the PHY and MAC layers while providing the necessary cross layer functionalities. CogFrame, our developed framework, allows the development of testbeds that work with standard computers and WiFi cards to reduce the cost while allowing integrating with other special hardware for more flexibility. It also provides different modules for implementing and emulating complex scenarios such as regulatory authority policies, mobility management, topology management.


CellSense: An Accurate Energy-Efficient GSM Positioning System

Context-aware applications have been gaining huge interest in the last few years. With cell phones becoming ubiquitous computing devices, cell phone localization has become an important research problem. In this project, we present CellSense, a probabilistic RSSI-based fingerprinting location determination system for GSM phones. We discuss the challenges of implementing a probabilistic fingerprinting localization technique in GSM networks and present the details of the CellSense system and how it addresses these challenges. We then extend the proposed system using a hybrid technique that combines probabilistic and deterministic estimation to achieve both high accuracy and low computational overhead.