One of the most critical and recurring tasks in managing a store is to provide accurate, up-to-date price information to customers on the shelves. Manual updating of price tags has been a time-consuming, error-prone task with high labor costs. An electronic shelf label (ESL) system is an excellent solution to solve many of the problems that traditional paper label systems have, and it is also a foundation system for next-generation services in markets.
A typical ESL system configuration in a retail store includes thousands of battery-powered ESL tags that are mostly connected wirelessly in a dense indoor environment. Raising the success ratio of wireless communication is essential for the system's viability due to its limited battery life. Most of the ESL traffic is the image data of goods that appear on the tags, and reducing the amount of the data is one of the most effective ways to enhance communication performance and reduce retransmission.
In this dissertation, we propose two schemes to improve the ESL system. One is a new image compression algorithm, ECO, based on chain coding that utilizes the characteristics of the ESL images. The other is a novel media-access-control protocol, ESL-MAC, to transfer images to many ESL tags effectively.
ESL images have characteristics that suit the purpose. First, they consist of text, barcodes, and simple figures, and text usually accounts for a large portion of them. Second, there are two or three colors used for them, and last, they have a lot of similar parts. The proposed scheme actively utilizes these characteristics.
We elaborate on the proposed methods and demonstrate that they are suitable for improving the performance of ESL systems through performance comparison and simulation with other existing algorithms. In performance evaluation, ECO showed higher compression efficiency and faster decompression speed than other algorithms. ECO can improve the ESL system's overall performance by compensating for the shortcomings of low transmission speed ESL networks and low computational capabilities ESL tags. In addition, ESL-MAC showed that it can effectively update many ESL tags with a shorter time and less traffic generation.