Evidence map›Paper›PMID 41977816›Full record

ArticleSensors (Basel, Switzerland)2026

Vertex: A Semantic Graph-Based Indoor Navigation System with Vision-Language Landmark Verification.

Isabel Ferri-Molla, Dena Bazazian, Marius N Varga, Jordi Linares-Pellicer, Joan Albert Silvestre-Cerdà

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Isabel Ferri-MollaValencian Research Institute for Artificial Intelligence (VRAIN), Universitat Politècnica de València (UPV), Camí de Vera, s/n, 46022 Valencia, Spain.ORCID 0009-0008-3608-9891
Dena BazazianSchool of Engineering, Computing and Mathematics (SECaM), University of Plymouth, Plymouth PL4 8AA, UK.ORCID 0000-0002-1229-4494
Marius N VargaSchool of Nursing and Midwifery, University of Plymouth, Plymouth PL4 8AA, UK.ORCID 0000-0001-7655-9829
Jordi Linares-PellicerValencian Research Institute for Artificial Intelligence (VRAIN), Universitat Politècnica de València (UPV), Camí de Vera, s/n, 46022 Valencia, Spain.ORCID 0000-0002-3315-1716
Joan Albert Silvestre-CerdàValencian Research Institute for Artificial Intelligence (VRAIN), Universitat Politècnica de València (UPV), Camí de Vera, s/n, 46022 Valencia, Spain.ORCID 0000-0003-2291-8296

Funding

Generalitat Valenciana CIACIF/2022/098
6 · The paper itself

Abstract

Older adults often need guidance when visiting new buildings for the first time. However, indoor navigation remains challenging due to the lack of Global Positioning System (GPS) availability, visually repetitive corridors, and frequent location failures. This article presents a multimodal indoor navigation assistant that combines graph-based route planning with visual landmark verification to provide step-by-step guidance. The environment is modelled as a directed graph whose nodes are annotated with semantic landmarks, and the graph is constructed primarily from a video of the building, reducing the need for 3D scanners, beacons, or other specialised instruments. Routes are calculated using Dijkstra's shortest-path algorithm over the semantic graph. During navigation, camera frames are analysed using a restricted vision-language recognition strategy that only considers candidate landmarks from the current and next nodes, reducing false detections and improving interpretability. To increase robustness, a temporary voting mechanism was introduced to confirm node transitions, as well as a hierarchical redirection strategy with local and global recovery. The system is implemented in two modes: handheld mode with visual cues using augmented reality arrows, mini map and voice instructions, and hands-free mode with front camera using voice instructions and keywords. Evaluation involved preliminary technical testing in the United Kingdom followed by formal user validation in Spain. During these trials, participants reported high usability, strong confidence and safety, and increased perceived independence.

Indexed as

augmented realityindoor navigationinfrastructure-free localisationmultimodal interactionolder adultssemantic graphspatial anxietyvision–language modelsvisual verification

Identifiers

PMID41977816
PMCPMC13075130

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.