NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Virtual Assistant for First Responders Using Natural Language Understanding and Optical Character RecognitionCommercial deep learning capabilities are available for many applications such as computer vision processing and intelligent chat bots. The Google Cloud Platform product Google Dialogflow provides lifelike conversational artificial intelligence (AI) using machine learning (ML) to generate natural conversations between computers and humans. This ML utilizes natural language understanding (NLU) to recognize a user’s intent and extracts key information into a form of entities. We have developed a user-friendly application through understanding the hazardous material database, first aid safety guidelines and observing the process of first responders who access this information in the field. We created the Trusted and Explainable Artificial Intelligence for Saving Lives (TruePAL) virtual assistant using Dialogflow1 and TensorFlow2 paired with EasyOCR.3 The chatbot supports first responders by providing voice interaction which helps limit additional steps such as browsing through multiple categories when searching for information. Using feedback from our field interviews, the voice interface has been developed to enable the first responder to focus on the immediate emergency. With less distractions, the first responder is able to engage the incident more effectively. The partial hands-free TruePAL chatbot assistant improves the accessibility to the correct guidance by an average of 1.9 seconds compared to the widely used application, NIH WISER, which requires full attention to operate. We combined this intelligent chatbot with a separate visual processing capability to produce hazardous signage analysis and generate the proper guidance for first responders. With the evolving functionality of AI tools, the use of virtual assistants in first responder technology will be an advancement, benefiting the safety of both first responders and civilians.
Document ID
20230006947
Acquisition Source
Jet Propulsion Laboratory
Document Type
Preprint (Draft being sent to journal)
External Source(s)
Authors
Chow, Edward
Lu, Thomas
Yun, Kyongsik
Gabrield, Mina
Joubert, Frederick J.
Huyen, Alexander
Do, Vickie
Date Acquired
April 3, 2022
Publication Date
April 3, 2022
Publication Information
Publisher: Pasadena, CA: Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2022
Distribution Limits
Public
Copyright
Other
Technical Review

Available Downloads

There are no available downloads for this record.
No Preview Available