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AI Analytics at the Shelf: Empowering Retailers with Electronic Labels

EasyChair Preprint no. 11084

7 pagesDate: October 12, 2023


The retail industry is undergoing a seismic shift driven by technological innovation, and
Artificial Intelligence (AI) is increasingly becoming a key player in this transformation. This
abstract introduces the concept of AI Analytics at the Shelf, a game-changing approach powered
by Electronic Shelf Labels (ESLs), which empowers retailers with data-driven insights to
optimize operations, pricing strategies, and customer interaction Analytics at the Shelf leverages
AI technologies like machine learning, computer vision, and data analytics to revolutionize
traditional retail processes. This abstract provides an overview of the benefits and applications of
this groundbreaking approach, demonstrating its potential to empower retailers and reshape the
retail landscape. Dynamic Pricing, Optimization Inventory Intelligence, Personalized Customer
Engagement, Operational Efficiency. This abstract also delves into the AI technologies behind
AI Analytics at the Shelf, including computer vision for product recognition and natural
language processing for improved customer interactions. It highlights potential challenges and
considerations such as data security and integration with existing retail systems.

Keyphrases: ESL, IoT, Security

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Lee Kasowaki and Cong Lin William},
  title = {AI Analytics at the Shelf: Empowering Retailers with Electronic Labels},
  howpublished = {EasyChair Preprint no. 11084},

  year = {EasyChair, 2023}}
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