The MERL motion detector dataset

Abstract

Looking into the future of residential and office building Mitsubishi Electric Research Labs (MERL) has been collecting motion sensor data from a network of over 200 sensors for a year. The data is the residual traces of year in the life of a research laboratory. It contains interesting spatio-temporal structure ranging all the way from the seconds of individuals walking down hallways, the minutes in the lobbies chatting with colleagues, the hours of dozens of people attending talks and meetings, the days and weeks that drive the patterns of life, to the months and seasons with their ebb and flow of visiting employees. This document describes that dataset, which contains well over 30 million raw motion records, spanning a calendar year and two floors of our research laboratory, as well as calendar, weather, and some intermediate analytic results. The dataset was originally released as part of the 2007 Workshop on Massive Datasets. The dataset can be obtained from http://www.merl.com/wmd. This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. AbstractLooking into the future of residential and office building Mitsubishi Electric Research Labs (MERL) has been collecting motion sensor data from a network of over 200 sensors for a year. The data is the residual traces of year in the life of a research laboratory. It contains interesting spatio-temporal structure ranging all the way from the seconds of individuals walking down hallways, the minutes in lobbies chatting with colleagues, the hours of dozens of people attending talks and meetings, the days and weeks that drive the patterns of life, to the months and seasons with their ebb and flow of visiting employees. This document describes that dataset, which contains well over 30 million raw motion records, spanning a calendar year and two floors of our research laboratory, as well as calender, weather, and some intermediate analytic results. The dataset was originally released as part of the 2007 Workshop on Massive Datasets. The dataset can be obtained from http://www.merl.com/wmd.

Inferring colocation and conversation networks from privacy-sensitive audio with implications for computational social science

“…For example, Ingram and Morris [2007] use such infrared badges to study patterns of interaction among executive MBA students at a mixer party. Similarly, Connolly et al [2008] use data collected from motion sensors [Wren et al 2007] to infer social events like walking together, attending the same meeting, or coincidentally meeting in a break room. Eagle and Pentland [2006] present a system for inferring physical proximity from the short-range Bluetooth radios in cell phones, and for inferring coarse absolute location using cell tower IDs.…”

Recovering Social Networks From Massive Track Datasets

“…The MERL (Mitsubishi Electric Research Lab) dataset [3] is an excellent example of the result of daily use of large numbers of sensors in an office environment. This is a dataset of activations of motion sensors distributed through the MERL environment, recorded during the course of 1 year.…”

Model predictive HVAC control with online occupancy model

“…The input is a stream of asynchronous pulses from pyroelectric infrared (PIR) or similar sensors that indicate whether at least one person is in the space. We have chosen the Mitsubishi Electric Research Lab (MERL) motion detector data set [24], which consists of a series of one-second pulses from various motion sensors located throughout hallways and conference rooms in MERL. 5 The meetings in the Belady conference room show a good balance between repetition and variety to showcase the benefits of on-line learning.…”