Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
April 1, 2026SensorsOpen Access

Neural Network-Based LoRa Received Signal Strength Indicator Fingerprint Identification for Indoor Localization of Mobile Robots

View Full Paper
Ask AI
Bookmark
Share

Authors

CBChandan BaraiMSMeem SarkarUSUshnish Sarkar

Discussion

Loading...

Member takes

Overview

This framework demonstrates enhanced indoor localization accuracy in mobile robots, indicating effective automation in smart environments.

Key Points

  • The aim is to develop a framework for precise indoor localization of mobile robots using LoRa technology and neural networks.
  • Utilized received signal strength indicator (RSSI) fingerprinting with LoRa technology for localization.
  • Employed Structural Similarity Index Measure (SSIM) for optimizing communication parameters.
  • Calculated entropy of the RSSI database to ensure fingerprint stability.
  • Developed a Multi-layer Perceptron (MLP) neural network for positional prediction within a grid setup.
  • Achieved a validation accuracy of 91.8 percent using the MLP during training.
  • Demonstrated high precision in classifying grid regions in a signal-dense environment.
  • Provided highly accurate localization data for slow-moving robots in applications such as radiation mapping.

Cite This Study

Barai et al. (2026) studied this question.

synapsesocial.com/papers/69ccb6b416edfba7beb88612https://doi.org/10.3390/s26072127
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1A Resilient Indoor Localization Framework Using Wireless Signal Sensing and Data-Driven Machine Learning Models2026
  2. 2RSSI Fingerprint-Based Indoor Localization Solutions Using Machine Learning Algorithms: A Comprehensive Review2025 · 20 citations
  3. 3RSSI-Based LoRa Simulation Environment: An MLP Application for Position Estimation2026
  4. 4RSS-Based Localization using Deep Learning Models with Optimizer in LoRaWAN-IoT Networks2024 · 4 citations
  5. 5RSSI-based fingerprint localization in LoRaWAN networks using CNNs with squeeze and excitation blocks2024 · 29 citations