Evidence map›Paper›PMID 36616873›Full record

ArticleSensors (Basel, Switzerland)2022

An Intelligent Multi-Floor Navigational System Based on Speech, Facial Recognition and Voice Broadcasting Using Internet of Things.

Mahib Ullah, Xingmei Li, Muhammad Abul Hassan, Farhat Ullah, Yar Muhammad, Fabrizio Granelli, Lucia Vilcekova, Tariq Sadad

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 42% of its field
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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Review
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

8 authors at 5 institutions in 4 countries.

Mahib UllahSchool of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan 430074, China.
Xingmei LiSchool of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan 430074, China.
Muhammad Abul HassanDepartment of Information Engineering and Computer Science, University of Trento, 38122 Trento, Italy.ORCID 0000-0002-1694-7317
Farhat UllahSchool of Automation, China University of Geosciences, Wuhan 430074, China.ORCID 0000-0001-6572-5326
Yar MuhammadSchool of Computer Science and Engineering, Beihang University, Beijing 100191, China.ORCID 0000-0001-6224-392X
Fabrizio GranelliDepartment of Information Engineering and Computer Science, University of Trento, 38122 Trento, Italy.ORCID 0000-0002-2439-277X
Lucia VilcekovaInformation Systems Department, Faculty of Management Comenius University in Bratislava, Odboj'arov 10, 82005 Bratislava, Slovakia.
Tariq SadadDepartment of Computer Science, University of Engineering and Technology, Mardan 23200, Pakistan.
China University of Geosciences · CNUniversity of Trento · ITBeihang University · CNComenius University Bratislava · SKUniversity of Engineering and Technology Lahore · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modern technologies such as the Internet of Things (IoT) and physical systems used as navigation systems play an important role in locating a specific location in an unfamiliar environment. Due to recent technological developments, users can now incorporate these systems into mobile devices, which has a positive impact on the acceptance of navigational systems and the number of users who use them. The system that is used to find a specific location within a building is known as an indoor navigation system. In this study, we present a novel approach to adaptable and changeable multistory navigation systems that can be implemented in different environments such as libraries, grocery stores, shopping malls, and official buildings using facial and speech recognition with the help of voice broadcasting. We chose a library building for the experiment to help registered users find a specific book on different building floors. In the proposed system, to help the users, robots are placed on each floor of the building, communicating with each other, and with the person who needs navigational help. The proposed system uses an Android platform that consists of two separate applications: one for administration to add or remove settings and data, which in turn builds an environment map, while the second application is deployed on robots that interact with the users. The developed system was tested using two methods, namely system evaluation, and user evaluation. The evaluation of the system is based on the results of voice and face recognition by the user, and the model's performance relies on accuracy values obtained by testing out various values for the neural network parameters. The evaluation method adopted by the proposed system achieved an accuracy of 97.92% and 97.88% for both of the tasks. The user evaluation method using the developed Android applications was tested on multi-story libraries, and the results were obtained by gathering responses from users who interacted with the applications for navigation, such as to find a specific book. Almost all the users find it useful to have robots placed on each floor of the building for giving specific directions with automatic recognition and recall of what a person is searching for. The evaluation results show that the proposed system can be implemented in different environments, which shows its effectiveness.

Indexed as

Facial RecognitionInternet of ThingsVoiceHumansSpeechautonomic computingfacial recognitionIoTmonitoringroboticssmart servicesvoice recognition

Identifiers

PMID36616873
PMCPMC9824444
OpenAlexW4312223689

What OpenQuestion holds

Textmetadata
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.