Entity Recognition Via Multimodal Sensor Fusion With Smart Phones

Abstract

This thesis serves as an exploration that takes the sensors within a cell phone beyond the current state of recognition activities. Current state of the art sensor recognition processes tend to focus on recognizing user activity. Utilizing the same sensors available for user activity classi cation, this thesis validates the ability to gather data about entities separate from the user carrying the smart phone. With the ability to sense entities, the ability to recognize and classify a multitude of items, situations, and phenomena opens a new realm of possibilities for how devices perceive and react to their environment.

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Document Details

Document Type
Technical Report
Publication Date
Mar 26, 2015
Accession Number
ADA614892

Entities

People

  • John E. Nagy

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Engineered Resilient Systems
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Computational Science
  • Computer Programming
  • Computers
  • Data Mining
  • Databases
  • Detection
  • Feature Extraction
  • First Responders
  • Gamma Rays
  • Information Science
  • Machine Learning
  • Measurement
  • Mobile Phones
  • Network Science
  • Smartphones
  • Supervised Machine Learning

Readers

  • Distributed Systems and Data Platform Development
  • Speech Processing/Speech Recognition.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems