Browse Prior Art Database

MOBILE CROWDSENSING BASED AD-HOC COLLABORATION MEETING OPTIMIZATION AND USER NOTIFICATION FOR VERY LARGE SCALE MEETINGS

IP.com Disclosure Number: IPCOM000253446D
Publication Date: 2018-Mar-29
Document File: 5 page(s) / 189K

Publishing Venue

The IP.com Prior Art Database

Related People

Carlos M. Pignataro: AUTHOR [+1]

Abstract

Techniques are provided herein for ad-hoc meeting reservation, instantiation, and notification based on mobile crowdsourcing. Leveraging mobile crowdsensing, indoor positioning, and geofencing enables gathering details about the mobile users around the "main" meeting room. The geofencing or intrusion prevention system may help gather the information about the users waiting outside the room. The information may further be correlated with the registered participants for the meeting. This information is used to create a heat map based on the location and the proximity of the potential mobile users and the main meeting room. A meeting room in close proximity may be detected to accommodate the overwhelming crowd. In one example, this room is reserved, a copy of the stream is redirected to the room, and the users are directed to the room.

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 44% of the total text.

Copyright 2018 Cisco Systems, Inc. 1

MOBILE CROWDSENSING BASED AD-HOC COLLABORATION MEETING OPTIMIZATION AND USER NOTIFICATION FOR VERY LARGE SCALE

MEETINGS

AUTHORS: Carlos M. Pignataro

Nagendra Kumar Nainar

CISCO SYSTEMS, INC.

ABSTRACT

Techniques are provided herein for ad-hoc meeting reservation, instantiation, and

notification based on mobile crowdsourcing. Leveraging mobile crowdsensing, indoor

positioning, and geofencing enables gathering details about the mobile users around the

“main” meeting room. The geofencing or intrusion prevention system may help gather the

information about the users waiting outside the room. The information may further be

correlated with the registered participants for the meeting. This information is used to

create a heat map based on the location and the proximity of the potential mobile users and

the main meeting room. A meeting room in close proximity may be detected to

accommodate the overwhelming crowd. In one example, this room is reserved, a copy of

the stream is redirected to the room, and the users are directed to the room.

DETAILED DESCRIPTION

Large-scale meeting are common in almost any business (e.g., keynote sessions,

all-hands meetings, partner summits, etc.). In large-scale meetings, a large meeting room

is booked based on the anticipated number of participants. Anticipation is not always

accurate, and in many instances people attend the meeting outside the room due to the

space crunch. Unfortunately, this occurs quite often. Moreover, although this problem may

not impact the remote participants, other types of issues might. For example, the

audio/video streaming can freeze, causing remote participants to drop from the session out

of frustration.

Accordingly, techniques are provided for ad-hoc meeting instantiation and

notification based on mobile crowdsourcing. This applies to Internet of Things (IoT) and

sensor inputs combined with the collaboration environment and intelligent room system.

Copyright 2018 Cisco Systems, Inc. 2

Leveraging mobile crowdsensing, indoor positioning, and geofencing enables

gathering details about the mobile users around the “main” meeting room. The geofencing

or intrusion prevention system may help gather the information about the users waiting

outside the room. The information may further be correlated with the registered participants

for the meeting. This information is used to create a heat map based on the location and the

proximity of the potential mobile users and the main meeting room. A meeting room at

close proximity may be detected to accommodate the overwhelming crowd.

For potential meeting participant overflow detection, mobile crowdsending may be

either participatory sensing or opportunistic sensing. In the case of participatory sensing,

the mobile users can actively express the desire to participate in the meeting. In the case of

opportunistic sensing, the collaboration system can leverage the user profile, location

sample, and participant list to ident...