Scholarly record
SOLOMON - SOCIAL LOCAL INDOOR ENHANCED SHOPPING PLATFORM
Abstract
In today's world, shopping represents a significant part of everyone's life. The interaction between the customer and store staff has grown to be more critical than ever. To facilitate a pleasant and engaging shopping experience, we acknowledge a market gap and a real competition for developing innovative tools that can be used by both parties: the customers, which need their requirements fulfilled, and the store staff, that can use these tools to satisfy customers' needs further by targeting the correct audience. This paper aims to present a solution designed to improve customers' shopping experience in physical stores by connecting different technologies and data sources. Accessibility and ease of use are essential for reaching the average customer. We incorporated Cloud Computing, Big Data, IoT, and Artificial Intelligence into a unique and innovative architecture to digitally remodel and develop the shopping industry. The SoLoMoN system consists of an Android app connected to a server, through which endusers, the customers, have access to information regarding their location in the shopping center based on indoor positioning, products advertisements when getting close to a store and a heatmap that shows the most visited areas. Also, to facilitate their logistics in transporting the purchased goods, we implemented a smart parking solution that shows the customers' statistics regarding the parking lots availability in near real-time. Also, the SoLoMoN WEB platform brings advantages to retailers in the form of centralized data about the customers' flow during specific parts of the day and the age and buying preferences of customers.
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- Scopus - Citation Indexes: 2
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Publication details
References15
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Number of times cited according to Crossref: 1
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