BOSS:A Flexible and Extensible Bluetooth Research Platform

BOSS targets providing an open source implementing for the Bluetooth protocol firmware shown in the yellow section in Figure. In addition to, providing the driver level interface to access the firmware changes. Unlike Bluetooth driver, firmware has no open source equivalent available to the research community.

CHKD Project:

Mobile devices such as smart phones have a number of sensors that can be exploited to solve a number of problems in health care delivery. In this paper we use accelerometer, gyroscope, and compass sensors to solve a location tracking problem common to many emergency departments. An emergency department is not friendly to be visually surveyed, layout consists of many isolated islands, and workstation layout is not standardized. An automated tool to create spaghetti diagrams of movements of personnel in a non-intrusive way is the problem we are reporting in this paper. A preliminary prototype shows very encouraging results of producing paths. We also identify challenges and our approach to meet them.

Audio-WiFi Project:

Wi-Fi is becoming widely popular network interface for data communication in smart devices. However, the Wi-Fi network still has several inefficiencies in terms of high energy consumption, unfairness between co-located nodes, and bandwidth poor utilization. In this project we like to address these issues of the Wi-Fi network by integrating the mic/speaker of the smart phones as a parallel communication channel. Our idea is to propose a novel framework of communication using mic/speaker in order to develop a more efficient Wi-Fi network communication for smart devices. The non-interferential nature with Wi-Fi network and low power consumption is the biggest advantage of using audio communication channel in parallel with WiFi. On the other hand, slow propagation and low data rate of the acoustic channel are some biggest challenges we are addressing in order to implement the Audio-WiFi framework.


BlueEye, a location identification system to estimate vehicles queue length at signalized intersections. In fact, the received Bluetooth radio signal strength varies depending on transmitter distance. By providing BlueEye system with the signal strength distribution over vehicles locations at traffic intersection, it becomes able to identify vehicles locations at the site using a probabilistic approach. Despite the noise and randomness associated with the Bluetooth radio signals, and the dissimilarity between mobile devices, BlueEye showed high locating accuracy with limited location error. However, this project is addressing number of challenges such as the impact of surrounding environment on Bluetooth radio signal, Bluetooth devices heterogeneity, and the Bluetooth standards restrictions that strangles system's throughput. more

meSDN:Mobile Extension of SDN:

Now-a-days large number of mobile devices use numerous apps that access internet through wireless. With such significant amount of traffic growth and variability, it is now necessary to have greater visibility and control over the traffic generated from the client devices, such that we can ensure performance guarantees to multiple types of users on a shared network infrastructure. In a wired infrastructure, network virtualization is a means to deliver such performance guarantees using Software-Defined Networking (SDN) APIs do dynamically coordinate network edges (e.g. routers, switch etc.); we don't need to change the client device behavior because the last hop between the network edge and the wired end device is an isolated full-duplex point-to-point link, e.g., Ethernet. However, this is not the case with wireless LANs (WLAN) as the last hop between the mobile device and the access points is shared medium. Moreover the current WiFi MAC protocol does not allow edge access points (APs) to control client uplink transmissions and their 802.11 quality of service (QoS) settings. Therefore, we argue that the SDN framework needs to be extended to the client devices to realize services such as WLAN virtualization with end-to-end QoS, and we propose a framework called msSDN. We show that meSDN also improves application-awareness and power-efficiency from our prototype on Android phones.


Smart Home is becoming a hot area of research for both academic and industrial researchers. In Smart Home, sensing the status of home devices (e.g., home appliances) is a corner stone for having better control over the home appliances as well as power consumption. In this project we present the design and the evaluation of a framework MagnoTricorder, a system that utilizes the magnetic sensor in smartphones to detect the running devices at home thru a singlepoint sensing. MagnoTricorder leverages the effect of Electro Magnetic Interference (EMI) generated by the AC current in the main power-line at home. This EMI induces a magnetic Şeld that highly ßuctuates the reading of the magnetic sensor in smartphones. In this project, we utilize this characteristic for detecting and identifying the running devices at home thru the Circuit Breaker Panel.


Accurate localization in outdoor and indoor spaces is a challenging task. The widely used GPS is not designed for high accuracy applications and yields accuracy levels not sufficient for lane or spot level localization. In addition, errors from inertial sensors accumulate with time due to integration drift. We introduce a smartphone based, infrastructure aided parking localization system called ParkZoom for estimating (zooming into) the precise parking spot location of a vehicle during traversal in both indoor and outdoor parking lots. On the vehicle side, the proposed method utilizes conventional smartphones for generating and transferring continuous sensor data, such as accelerometer, gyroscope, and compass readings. On the infrastructure side, ParkZoom employs statistical learning of sensor data signatures, pattern classification of data, constraint propagation and error correction for accurate parking spot identification. The paper presents experimental results with the ParkZoom algorithm obtained on real data in city driving and two parking areas.

Drive Blue -2014

Bluetooth wide availability in vehicles either through passengers' smartphones or vehicle hardware have been poorly exploited by researchers. Neighbor discovery an exclusive Bluetooth feature can be utilized to enhance transportation services while maintaining vehicle's privacy. In this project, we advocate for using Bluetooth in developing intelligent transportation services. We name our project DriveBlue.
Bluetooth data can be collected by placing multiple receivers in a single site. Features are extracted, and classifed revealing some of the current traffic conditions (e.g. average speed on the road, differentiate between vehicles on HOV ver- sus regular lanes). more...


Smartphones have created a strong tie with human beings. It is likely to have plenty of smartphones in the same proximity. However, users are limited with the capabilities of a single device. In this work we propose ColPhone a framework that facilitates collaboration between smartdevices in the vicinity to share their resources providing users hardware upgrade for their devices. Further, we implemented an application (3D Story Teller) on top of ColPhone , and measured the impact of collaboration on smartphone's power consumption. more .

Multi-User MIMO:

The goal of this project is to explore the capabilities of USRP2 boards and use them to build 802.11 testbed. more

Smartphone based Social Networks -2013

Day by day smartphones are moving towards being a necessity rather than a luxury. Smartphones are now so close to the users raising the question: How close the phone is from its owner? In this project we will try to explore the smartphone communication. we assume that users proximity has something to do with the data viewed by users. The relation between users can be a factor in the percentage of common data used. We will try to use the data collected from smartphone usage to construct an anonymous social networks mapping the repetition of data usage keeping an eye on their proximity. more...

Orange Data for Development (D4D) -2012

Is an open data challenge, encouraging research teams around the world to use four datasets of anonymous call patterns of Orange's Ivory Coast subsidiary, to help address society development questions in novel ways.
We proposed a scheme to detect the underutilized nodes in the cellular Network, providing a simple applicable solution based on the available information. We Also mentioned how to use the network's unreleased information to have further enhancements. The code we used for the D4D challenge can be found here.


In this project, we propose a simple and flexible energy monitoring system using smart phones. We call our system EnergySniffer in which it exploits various sensors, such as magnetic sensor, light, microphone, temperature, camera, WiFi, in smart phones to detect and monitor operating machines in its vicinity. The advantages of EnergySniffer system can be summarized as follow: First, it monitors energy consumption for each individual machine. Second, it has very low overhead and also no new hardware is needed to install or maintain. Third, very flexible in updating software and deploying new services using the application updating feature of the smart phones' application markets. Using the sensors in smart phones to monitor the energy consumption by machines is an eccentric way to approach the problem. Our final objective is to fuse the data from multiple sensors in phone to build a multi sensing framework to generate a unique fingerprint profile for each machine. Later, we apply a machine learning method using fingerprint profiles to recognize and monitor operating machines. In addition to that, this system will also communicate with the Energy Profile of the identiŞed machine to finally calculate the actual energy consumption.