The transportation industry is currently undergoing a drastic shift towards autonomous vehicles (AV) and processes. It is likely that autonomous transportation systems will be deployed within retirement communities significantly sooner than they are available to the general public: these communities have a particularly acute need for assisted mobility, and the controlled environment of a retirement campus simplifies many of the technical problems related to autonomous control. The elderly population has a relatively high prevalence of physical, sensory and cognitive limitations that must be addressed in the design of an AV system. We believe that a successful user interface in this domain will require a high level of passenger awareness. External and in-vehicle sensors will monitor the position, activities and mental state of passengers. The user interface will use that information to guide passenger interactions. For example, raising the volume of spoken instructions if a passenger is having difficulty hearing, or calling for assistance if a passenger is having difficulty entering or exiting the vehicle. The central research questions that we consider are 1) How can machine learning models be used to extract relevant passenger information? 2) How should an AV user interface incorporate passenger monitoring data to provide safe and reliable mobility service for the elderly? In earlier work, we developed an autonomous golf cart that provides the key capabilities required for autonomous passenger transport. The proposed work will build on that foundation to address the research questions outlined above. We propose to: 1) Equip our autonomous vehicle with a sensor suite that will enable the collection of passenger data suitable for training machine learning models. 2) Develop and train machine learning models to extract passenger information that can be used by the user interface. 3) Prototype a passenger-aware user interface. 4) Validate the user interface design through user trials.

Collaborative Project between James Madison University, and Explore More Discovery Museum involving undergrad and graduate students from James Madison University. These collaborations connect James Madison University with a local non-profit educational institution (Explorer More Discovery Museum: located in Downtown Harrisonburg and considered as a main hub for K-12 Education).

Students involved: Two undergraduate students (seniors) from ISAT and CS department. One graduate student from Adult Educational/Human Resource Development Department (AHRD). Three undergraduate students from Management Department.

This project is focus on the transit bus system. The transit bus system was chosen as it is a key component in achieving more sustainable urban transportation system. Our goal is to increase bus ridership through better scheduling and route management. In this study, the two groups will assess the performance of current bus operations (e.g., waiting time at bus stations) using a low cost technology system (e.g., Bluetooth reader, iBeacon, etc.) to be assembled or available through off-the-shelf devices. We will study the performance of bus systems in Harrisonburg and Charlottesville.

Students involved: Three undergraduate students (seniors) from ISAT department, two senior student from CS, one graduate student from CS. Collaboration work between JMU and UVA (University of Virginia).

Objectives: Students, faculty members and staff have been struggling lately to find a space in parking lots around JMU without driving around several times, especially at peak hours.
Our Solution: A mobile-friendly website/mobile app that is connected to a database that keeps track of number of avilable spaces in each parking lot and determines the number of spaces open in a given parking lot by counting the numbers of cars entering and leaving.
Story: A student/faculty/staff will be able to open his/her smart phone app to check which parking lots have an available parking space. Although nothing will guarantee that the space will be available by the time of arrival, an estimate will be given of the likelihood that the space will still be available on arrival (by studying the time, distance and historical data). The app will push notifications if parking lots are full and what to consider as an alternative. Cars will replace the normal parking decal with a smart decal that has a built-in tag (similar to the “easy pass” used on highways).

Students involved: Five undergraduate students (seniors) from ISAT and CS departments.

With the Internet of Things  (IoT) being a main topic in the Internet, we are investigating the security of WSNs. Our research is focus on working with ZigBee Alliance due to its global wireless standard to provide the foundation for IoT. Currently, there is an implementation of Zigbee on TinyOS, however, the security feature is not implemented. Furthermore, TinyOS has an implementation of the IEEE 802.15.4 standard and the Open-ZB working group has implemented the security feature of IEEE 802.15.4. The thesis work is to implement and improve the security aspect of ZigBee on top of IEEE 802.15.4. The study is to analyze the performance and feasibility of using the security ZigBee implementation on TelosB WSN nodes. Our ultimate goal is to provide the Internet community with a working implementation of ZigBees security feature.

Students involved: One graduate student from CS department.

Senior Projects Supervision:

Academic Year 2015-2016

• Mobile & Web Application: User Friendly Hub for Taxi Services in Harrisonburg, VA
  
  Develop a website and mobile app (iOS) for Harrisonburg community to request Taxi

• Secure Smart Parking at James Madison University via the Cloud Environment (SPACE)
  
  A secure smart solution for parking around James Madison University.

• Improving Transit Bus Operations Using Low-Cost Bluetooth/Wi-Fi Technology
  
  Check projects above

Academic Year 2014-2015

• ISAT Alumni Connect
  
  Develop a website and mobile app for ISAT Alumni to connect with ISAT students

• Study of the Capabilities of the Yellow Flashing Arrow Traffic Signal & Driver Response
  
  Develop a traffic simulation for yellow flashing signal using AORTA Traffic Simulator.
  Develop a survey for the driver response in case of various types of signal.
  Analyze data coming from simulation and survey, and conclude results.

• The JMU Textbook Exchange
  
  Develop a website for JMU students to sell and buy used books

• AirClock: The Wireless Game Clock Controller
  
  A device that allows for complete, near instant control of the game clock by a single or even multiple officials thereby eliminating the delay between signaling and clock stoppage

Scientific Activities:

Invited Talks:

1. Review Panel member for the National Science Foundation (NSF) Education and Human Resources Directorate (EHR) Core Research program Nov 2016
2. Feature Speaker at 4-VA Research Symposium, September 2016.
3. Invited Talk at the Civil and Environmental Engineering Department at University of Virginia. November 2015.
4. Panelist at ATARC (Advanced Technology Academic Research Center) Federal Mobile Computing Summit. August 2015, Ronald Reagan Building, Washington, D.C.
5. Invited Talk at the Electrical and Computer Engineering Department at Old Dominion University. November 2014.
6. Invited Talk at the Computer Science Department at Old Dominion University. November 2013.