This is a cross-disciplinary project that draws inspiration from biological systems to help design wireless sensing and communications networks to aid emergency responders in rescuing victims after a disaster. The project is supported by an NSF EAGER (EArly-concept Grants for Exploratory Research) award, which is targeted at exploratory research to test out new ideas and approaches.

The project is currently focused on how to quickly and efficiently get useful information to first responders about the status and location of individuals trapped inside a building. In general, first-responders have no way of sensing the presence of trapped individuals. But today, even in poorer countries, almost everybody carries a cell phone. Cell phones are getting more sophisticated every year, with dozens of onboard sensors (camera, microphone, GPS, gyroscope, accelerometer, etc.) and support for multiple wireless communications protocols (cellular, Wi-Fi, Bluetooth). Our idea is to use individual smartphones inside a building as a distributed wireless sensing network. We have been developing a prototype system called iRescue, short for Illinois Rescue:

  • Following a disaster, a smartphone application could be launched automatically to assess the status of a user via on-screen questions. We have also developed an application that automatically uses the smartphone’s sensor data to assess the likely status of its owner. Using accelerometer and gyroscope sensors, which act much like an animal’s vestibular system, the smartphone can monitor its own motion and determine what may be happening. Using a Bayesian classifier system, which is similar to how the brain processes noisy and uncertain sensory data, we successfully recognized nine different activity patterns (e.g., sitting, standing, walking, running, etc.) with 90% accuracy. The system can also distinguish between a cell phone on a desk or in a drawer from one that is being carried by an individual.

  • We are currently working on an indoor localization system that can estimate each smartphone’s location in the absence of GPS signals that don’t penetrate into the building . Status and location information from individual smartphones could then be communicated wirelessly to a tablet-like device carried by first responders, providing them with an overview of the current situation. So far, we have implemented the basic functionalities of this localization system for Android devices. We have also performed several test cases to evaluate the accuracy and efficiency of our developed algorithm. The results show that we can improve the performance and accuracy of the system by revising the algorithm used. We are now in need of 2 programmers to help us with the following tasks:

    1. Android Programmer: Our main prototyping platform is Android. Current version of the Android application is based on the older algorithm. The algorithm has to be updated in addition to re-organizing the existing code and improving the UI. Furthermore, the application currently relies on its local database for both storing and retrieving fingerprinting data. This has to be replaced by accessing a database stored at a server. JSON seems to be a good candidate for communication. In addition, since Internet connection on the cellphone might not be reliable, caching of the most relevant fingerprinting data on the phone is also important. The developer should expect to spend some time evaluating the performance of the developed algorithm and code on a test area.

    2. Server Programmer: Our implemented system is currently an Android application and all the fingerprinting data is stored locally on the device. Obviously, this requires manual transfer of the fingerprinting data from cellphone to cellphone. This worked for our initial prototyping but is not practical in case of a large scale experiment. We need a server programmer to develop a server side version of the algorithm which can hold the large fingerprinting database required for the localization algorithm. Users should be able to easily fingerprint the area and send the fingerprint data to the server. Server should process those recordings, integrate them with the previous recorded data and store them in its database. Later, when the users want to localize, they scan the area, send the list of the scanned WiFi access-points to the server. The server should then use the previous recorded data and the developed algorithm to find the user location. Server should notify the end user about the calculated location inside the building. We are relatively flexible with the server technology to be used but PHP+JSON seems like a good candidate. The developer should expect to spend some time evaluating the performance of the server in a few test cases under different request loads.
if you are interested in getting involved with this project, please contact me at sshifte2@illinois.edu

© Copyright 2007-2013 Reza Shiftehfar | All Rights Reserved