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Authors: David Bell ; Nikhil Makwana and Chidozie Mgbemena

Affiliation: Brunel University, United Kingdom

Keyword(s): Motion Sensors, Gestures, Business Intelligence.

Related Ontology Subjects/Areas/Topics: Data Communication Networking ; Decision Support Systems ; Enterprise Information Systems ; Internet of Things ; Platforms and Operating Systems ; Programming and Middleware ; Sensor Networks ; Software Agents and Internet Computing ; Software and Architectures ; Telecommunications

Abstract: The combination of sensor data with analytic techniques is growing in popularity for both practitioners and researchers as an Internet of Things (IoT) offers new opportunities and insights. Organisations are trying to use sensor technologies to derive intelligence and gain a competitive edge in their industries. Obtaining data from sensors might not pose too much of a problem, however subsequent utilisation in meeting an organisation’s decision making can be more problematic. Understanding how sensor data analytics can be undertaken is the first step to deriving business intelligence from front line retail environments. This paper explores the use of the Microsoft Kinect sensor to provide intelligence by identifying and sensing gestures to better understand customer behaviour in the retail space.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Bell, D.; Makwana, N. and Mgbemena, C. (2014). Sensing Gestures for Business Intelligence. In Proceedings of the 3rd International Conference on Sensor Networks - SENSORNETS; ISBN 978-989-758-001-7; ISSN 2184-4380, SciTePress, pages 52-60. DOI: 10.5220/0004878100520060

@conference{sensornets14,
author={David Bell. and Nikhil Makwana. and Chidozie Mgbemena.},
title={Sensing Gestures for Business Intelligence},
booktitle={Proceedings of the 3rd International Conference on Sensor Networks - SENSORNETS},
year={2014},
pages={52-60},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004878100520060},
isbn={978-989-758-001-7},
issn={2184-4380},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Sensor Networks - SENSORNETS
TI - Sensing Gestures for Business Intelligence
SN - 978-989-758-001-7
IS - 2184-4380
AU - Bell, D.
AU - Makwana, N.
AU - Mgbemena, C.
PY - 2014
SP - 52
EP - 60
DO - 10.5220/0004878100520060
PB - SciTePress