DeepAI AI Chat
Log In Sign Up

EXTRACT: Strong Examples from Weakly-Labeled Sensor Data

by   Davis W Blalock, et al.

Thanks to the rise of wearable and connected devices, sensor-generated time series comprise a large and growing fraction of the world's data. Unfortunately, extracting value from this data can be challenging, since sensors report low-level signals (e.g., acceleration), not the high-level events that are typically of interest (e.g., gestures). We introduce a technique to bridge this gap by automatically extracting examples of real-world events in low-level data, given only a rough estimate of when these events have taken place. By identifying sets of features that repeat in the same temporal arrangement, we isolate examples of such diverse events as human actions, power consumption patterns, and spoken words with up to 96 fast enough to run in real time and assumes only minimal knowledge of which variables are relevant or the lengths of events. Our evaluation uses numerous publicly available datasets and over 1 million samples of manually labeled sensor data.


page 1

page 5


Sprintz: Time Series Compression for the Internet of Things

Thanks to the rapid proliferation of connected devices, sensor-generated...

Yet it moves: Learning from Generic Motions to Generate IMU data from YouTube videos

Human activity recognition (HAR) using wearable sensors has benefited mu...

Detecting F-formations Roles in Crowded Social Scenes with Wearables: Combining Proxemics Dynamics using LSTMs

In this paper, we investigate the use of proxemics and dynamics for auto...

Attention-based Convolutional Neural Network for Weakly Labeled Human Activities Recognition with Wearable Sensors

Unlike images or videos data which can be easily labeled by human being,...

ESPRESSO: Entropy and ShaPe awaRe timE-Series SegmentatiOn for processing heterogeneous sensor data

Extracting informative and meaningful temporal segments from high-dimens...

A Policy Editor for Semantic Sensor Networks

An important use of sensors and actuator networks is to comply with heal...

A streaming feature-based compression method for data from instrumented infrastructure

An increasing amount of civil engineering applications are utilising dat...