IoT Data Analytics in Retail: Framework and Implementation

Jānis Grabis, Kristina Jegorova, Krišjānis Pinka

2020

Abstract

IoT data analytics has many potential applications in the retail industry. However, relations among ambient conditions at stores as measured by IoT devices and sales performance are not well understood. This paper explores sensory and sales data provided by a large retail chain to quantify the impact of air quality, temperature, humidity and lighting on customer behaviour. It has been determined that the air quality and humidity have a significant impact and temperature appears to have a non-linear effect on customer behaviour. The data analysis findings are used to configure an IoT data analytics platform. The platform is used to monitor the ambient conditions in retail stores, to evaluate a need for improving the conditions as well as to enact improvement by passing them over to a building management system.

Paper Citation

in Harvard Style

Grabis J., Jegorova K. and Pinka K. (2020). IoT Data Analytics in Retail: Framework and Implementation.In Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics - Volume 1: IN4PL, ISBN 978-989-758-476-3, pages 93-100. DOI: 10.5220/0010133700930100

in Bibtex Style

@conference{in4pl20,
author={Jānis Grabis and Kristina Jegorova and Krišjānis Pinka},
title={IoT Data Analytics in Retail: Framework and Implementation},
booktitle={Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics - Volume 1: IN4PL,},
year={2020},
pages={93-100},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010133700930100},
isbn={978-989-758-476-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics - Volume 1: IN4PL,
TI - IoT Data Analytics in Retail: Framework and Implementation
SN - 978-989-758-476-3
AU - Grabis J.
AU - Jegorova K.
AU - Pinka K.
PY - 2020
SP - 93
EP - 100
DO - 10.5220/0010133700930100