The objective of this project is to develop software algorithms for state-of-the-art audio surveillance of aircraft cabin areas to enhance cabin safety and improve the passenger experience. Students on the Collins Audio Analytics team will develop software algorithms to support sound and voice identification, detection, and key word recognition in aircraft interiors.
Abstract:
Collins Aerospace’s aircraft video and audio monitoring devices enhance situational awareness and record incidents for evidence capture and analysis. Flight crew and security personnel benefit from our scalable solutions for cabins, flight decks, cargo bays and aircraft exteriors. These devices integrate with complementary aircraft systems, including aircraft data management systems.
The objective of this project is to develop software algorithms for state-of-the-art audio surveillance of aircraft cabin areas. The system will classify, interpret, and respond to the sensed audio data automatically through artificial intelligence enabled analytics. The processing system will utilize Nvidia Jetson Nano line of System-On-Modules for artificial intelligence and audio analytics. Students on the Collins Audio Analytics team will develop software algorithms to support sound and voice identification, detection, and key word recognition in aircraft interiors.
Impact:
Flight safety continues to be a focus area of commercial aviation and its regulatory agencies. This has increased the workload of the cabin crew throughout various phases of a flight. The use of advanced intelligent surveillance technology will enable overall safety of flight operations to increase while also reducing the workload of the flight crew. Additional benefits include improved passenger experience and comfort, aircraft operation and maintenance.
Full Project Details
Algorithm Development and Audio processing (3-5 Students)
Specific Skills: Algorithm development, Machine Learning, AI, interest/experience in audio processing, Python, Linux, ROS
Must have completed EECS 281
Likely Majors: CS, DATA, EE, PAT
User Interface Development (1 student)
Specific Skills: Standard textual and/or GUI interface design skills
Should have completed EECS 280 or equivalent
Likely Majors: SI, CS
Audio Hardware and Processing, Systems Planning and Testing (1-2 students)
Specific Skills: Audio capture and processing. System configuration and integrated test development/planning,
Likely Majors: PAT, EE, ISD-Systems, AERO
Sponsor Mentors
Mr. Brad Mennicke
Brad has over 20 years of experience in the Computing and Aerospace Industry, including 7 years at Collins Aerospace. He holds a MSEE with focus on machine learning and parallel processing. With a background in FPGA and processor development for video and data processing, and connectivity products. He has been a primary contributor and leader in Collins Vision and Connectivity Systems (VCS) group. He currently leads a team of 9 FPGA and Electrical engineers.
Mr. Rameshkumar Balasubramanian
Ramesh has over 17 years of experience in the Aerospace industry, including 14 years at Collins Aerospace. He holds a Master of Engineering in Avionics. With a background in Systems and Software design for various avionics products, he is currently a leader in Collins Vision and Connectivity System group with focus on wireless connectivity and Prognostics Health Monitoring. Ramesh holds eight patents with additional pending, primarily in the areas of connectivity, and system design.
Faculty Mentor
Carol Menassa
Associate Professor and John L. Tishman CM Faculty Scholar, Civil Engineering
Professor Menassa’s research focuses on understanding and modeling the interconnections between the human and the built environment. From her website: In this context, my research group focuses on two main research thrusts. In the first, we study the impact of human behaviors and actions on the built environment. For example, we use modeling and simulation to understand the impact of occupants on energy use in buildings and develop decision frameworks to sustainably retrofit existing buildings. In the second thrust, we focus on understanding the effect of the built environment on human comfort, well-being and accessibility issues. For example, we use non-intrusive methods such as low cost thermal cameras to provide personalized thermal comfort settings in single and multi-occupancy space. We also develop personalized localization and path planning methods to assist people with physical disabilities in navigating unknown building environments. My research group has expertise in energy simulation, complex adaptive systems modeling, high-level architecture and informatics, computer vision and robotics.
Course Substitutions: Honors, ChE Elective, CS MDE/Capstone, CE MDE, EE MDE, IOE Senior Design, IOE Grad Cognate, SI Elective, SI Grad Cognate
Citizenship Requirements: This project is open to all students on campus.
IP/NDA: Students will sign standard University of Michigan IP/NDA documents.
In Person/Remote Participation Options:
Work will take place on campus in Ann Arbor, MI.
On-Campus Participation Requirements –
Students on this team must be able to be physically present on campus in Ann Arbor to work as local safety protocols allow.
Internship/Summer Project Activities: No summer activity will take place on the project.