Shelf out of stock is one of the leading motivations of technology innovation in the shelf of the future. The Shelf Detector project described in this paper aims to solve the problem of data knowledge in the shelf out of stock (SOOS) problem. This paper is mainly focused on the information layer of the system and main novelties illustrated in this work are in the information field demonstrating the huge number of insights that can be derived from the use of such a tool able to gather data in real time from the store. The tool presented is the first being installed for long time in a high number of stores and products demonstrating the ability to gather data from there and extract interesting insights. This paper aims to demonstrate the feasibility and the scalability of our system in providing a high number of data and interesting insights for store team and marketing team. The cloud based architecture developed and tested in this project is a key feature of our system together with the ability to collect data from a distributed sensor network.

Information management for intelligent retail environment: the Shelf Detector system / Frontoni, Emanuele; Mancini, Adriano; Zingaretti, Primo; Valerio, Placidi. - In: INFORMATION. - ISSN 2078-2489. - 5:2(2014), pp. 255-271. [10.3390/info5020255]

Information management for intelligent retail environment: the Shelf Detector system

FRONTONI, EMANUELE;MANCINI, ADRIANO;ZINGARETTI, PRIMO;
2014-01-01

Abstract

Shelf out of stock is one of the leading motivations of technology innovation in the shelf of the future. The Shelf Detector project described in this paper aims to solve the problem of data knowledge in the shelf out of stock (SOOS) problem. This paper is mainly focused on the information layer of the system and main novelties illustrated in this work are in the information field demonstrating the huge number of insights that can be derived from the use of such a tool able to gather data in real time from the store. The tool presented is the first being installed for long time in a high number of stores and products demonstrating the ability to gather data from there and extract interesting insights. This paper aims to demonstrate the feasibility and the scalability of our system in providing a high number of data and interesting insights for store team and marketing team. The cloud based architecture developed and tested in this project is a key feature of our system together with the ability to collect data from a distributed sensor network.
2014
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/128495
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