PI: Matthew E. Tolentino
Start-Up Company Name: Namatad
Lab/Project Website: http://www.tacoma.uw.edu/set/tolentino-makes-new-portable-tech-systems-firefighters and http://faculty.washington.edu/metolent/
Work Location: UW Tacoma Cherry Parkes Building, IPA Research Lab, CP206i
Work Hours: 10am – 4pm will be the typical working hours. We will hold regular weekly meetings
Overall Program Goal: The goal of the company is to improve the safety of first responders and visibility of the fire ground operations during structural fires, as well as collect and analyze environmental data during emergency events in real time. We have built a complete system to track the location of first responders as well as the environmental conditions encountered while responding to building fires. We have built wearable devices in addition to drone-mounted devices for localization and environmental data. We have also built a real-time data processing system that applies advanced analytics and machine learning techniques to translate collected data into actionable information. Finally, we have developed a visualization system built on top of the Unity game engine to enable Incident Commanders responsible for managing the fire ground to observe and manage the locations of all on-scene personnel and conditions during fire operations.
The goal of the project for this internship will be to evaluate and improve the wearable indoor positioning and environmental monitoring system developed within the IPA Research Lab for fire departments. It is critical that we can ensure high fidelity environmental data is collected during field trials and then analyzed to determine efficacy. Another primary responsibility of the intern will be to evaluate the power capacity of current generation devices and develop and evaluate alternative power-management support and policies to maximize usable lifetime requirements during emergency scenarios.
Intern Project Description and Responsibilities: The intern will be responsible for development of software support for air quality and particulate sensors, inertial measurement units, and other sensors that are directly attached to a custom, wearable, microcontroller-based board as well as drone-mounted boards. The intern will also be responsible for validating the developed software functions meet predetermined performance requirements. Additionally, the intern will be responsible for identifying power management capabilities of system devices/components and generating alternative power management policies. This work will involve modifying FreeRTOS device drivers, extensive field-testing both on campus and at the Tacoma Fire Training Facility, and analysis of data collected during field experiments.
This internship requires an understanding of microcontrollers, system architecture and design, the C programming languages. Candidates should have some experience reading and decoding device specifications. An understanding of operating system fundamentals, particularly real-time operating systems (RTOS) would be helpful but not strictly required. Some knowledge (or interest) in traditional infrastructure-based networks as well as mesh networks and distributed systems would be helpful. Most importantly, internship candidates should have a strong interest in low-level programming and interacting directly with devices at register-level as well. This is a hands-on position and will require significant experimentation in the field in collaboration with the Tacoma Fire Department and City of Tacoma.
Preference will be given to Computer Engineering, Computer Science, or Electrical Engineering majors. All candidates must have a strong interest in working hands-on with embedded hardware as well as system software.
Level of Independence:
This position will be well structured in terms of roles and responsibilities with clear weekly goals over the team of the project. This project has a clear roadmap of work to be completed over the summer. However, there will be flexibility in terms of how the intern will be required to meet these goals, requiring creating thought and execution. The selected intern will work directly with the PI as well as IPA lab team members consisting of both undergraduate and graduate students.
- The primary learning outcome for the intern will be to learn how to design and execute validation plans for a real, distributed system composed of multiple wearable and drone-mounted devices.
- A secondary learning outcome will be to learn how to analyze power and energy consumption of power-constrained devices and power management techniques to maximize device lifetime.
- A third learning outcome will be the experience of working with a team to deploy and evaluate an IoT-based system.