@Article{jbd.2021.016213,
AUTHOR = {Malak Abid Ali Khan, Xiaofeng Lian, Imran Khan Mirani, Li Tan},
TITLE = {Research on Key Technologies of Electronic Shelf Labels Based on LoRa},
JOURNAL = {Journal on Big Data},
VOLUME = {3},
YEAR = {2021},
NUMBER = {2},
PAGES = {49--63},
URL = {http://www.techscience.com/jbd/v3n2/42216},
ISSN = {2579-0056},
ABSTRACT = {The demand for Electronic Shelf Labels (ESL), according to the 
Internet of Things (IoT) paradigm, is expected to grow considerably in the 
immediate future. Various wireless communication standards are currently 
contending to gain an edge over the competition and provide the massive 
connectivity that will be required by a world in which everyday objects are 
expected to communicate with each other. Low-Power Wide-Area Networks 
(LPWANs) are continuously gaining momentum among these standards, mainly 
thanks to their ability to provide long-range coverage to devices, exploiting 
license-free frequency bands. The main theme of this work is one of the most 
prominent LPWAN technologies, LoRa. The purpose of this research is to 
provide long-range, less intermediate node, less energy dissipation, and a 
cheaper ESL system. Much research has already been done on designing the 
LoRaWAN network, not capable to make a reliable network. LoRa is using 
different gateways to transmit the same data, collision, data jamming, and data 
repetition are expected. According to the transmission behavior of LoRa, 50% of 
data is lost. In this paper, the Improved Backoff Algorithm with synchronization 
technique is used to decrease overlapping and data loss. Besides, the improved 
Adaptive Data Rate algorithm (ADR) avoids the collision in concurrently 
transmitted data by using different Spreading Factors (SFs). The allocation of SF 
has the main role in designing LoRa based network to minimize the impact of the 
intra-interference, cost function, and Euclidean distance. For this purpose, the K- means machine learning algorithm is used for clustering. The data rate model is 
using an intra-slicing technique based on Maximum Likelihood Estimation 
(MLE). The data rate model includes three critical communication slices, High 
Critical Communication (HCC), Medium Critical Communication (MCC), and 
Low Critical Communication (LCC), having the specified number of End 
devices (EDs), payload budget delay, and data rate. Finally, different 
combinations of gateways are used to build ESL for 200 electronic shelf labels.},
DOI = {10.32604/jbd.2021.016213}
}