PRoA: An intelligent multi-criteria Personalized Route Assistant

Torres, Marina; Pelta, David A.; Verdegay, José L.

doi:10.1016/j.engappai.2018.03.016

Cited by 14 publications

(5 citation statements)

References 14 publications

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“… Ref. Type Application Information Extracted From AI Implemented Year [ 10 ] App Traffic jams Smartphone sensors Decision algorithm in function of the via status 2018 [ 11 ] App Traffic jams and incidents Smartphone sensors and third parties - 2019 [ 12 ] App Accident risk Personal information and historical data Fuzzy harmonic systems and fuzzy patterns 2017 [ 13 ] App Improve pedestrian routes Open Street Maps and Google APIs A * algorithm 2018 [ 14 ] App Improve pedestrian routes Data base with architectural barriers and Google APIs Optimizing iterative algorithm 2020 [ 15 ] App Improve pedestrian routes Maps stored in Google ...…”

Section: Table A1mentioning

confidence: 99%

“…In this way, this app avoids exposing the user to certain health risks. Besides, this app generates routes that require travelling a shorter distance than those offered by Google Maps thanks to the use of Open Street Maps (OSM) and the A * algorithm [ 13 ]. In addition to the previous application, there is another proposal called UniBS4All based on Google Directions, which allows generating routes adapted to the needs of people with physical disabilities.…”

Section: Introductionmentioning

confidence: 99%

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Walking Secure: Safe Routing Planning Algorithm and Pedestrian’s Crossing Intention Detector Based on Fuzzy Logic App

Domínguez

Sanguino

2021

Sensors

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Improving road safety through artificial intelligence is now crucial to achieving more secure smart cities. With this objective, a mobile app based on the integration of the smartphone sensors and a fuzzy logic strategy to determine the pedestrian’s crossing intention around crosswalks is presented. The app developed also allows the calculation, tracing and guidance of safe routes thanks to an optimization algorithm that includes pedestrian areas on the paths generated over the whole city through a cloud database (i.e., zebra crossings, pedestrian streets and walkways). The experimentation carried out consisted in testing the fuzzy logic strategy with a total of 31 volunteers crossing and walking around a crosswalk. For that, the fuzzy logic approach was subjected to a total of 3120 samples generated by the volunteers. It has been proven that a smartphone can be successfully used as a crossing intention detector system with an accuracy of 98.63%, obtaining a true positive rate of 98.27% and a specificity of 99.39% according to a receiver operating characteristic analysis. Finally, a total of 30 routes were calculated by the proposed algorithm and compared with Google Maps considering the values of time, distance and safety along the routes. As a result, the routes generated by the proposed algorithm were safer than the routes obtained with Google Maps, achieving an increase in the use of safe pedestrian areas of at least 183%.

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Section: Table A1mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Walking Secure: Safe Routing Planning Algorithm and Pedestrian’s Crossing Intention Detector Based on Fuzzy Logic App

Domínguez

Sanguino

2021

Sensors

View full text Add to dashboard Cite

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“…The suitability for instance of a sustainable travel route will depend on the mobility of the patient wanting to come to the hospital. There are already systems developed that are devised to help people in these contexts and ongoing research investigating how to improve them [87][88][89]. Google Maps already have an accessibility mode on their free application with richer data powering it.…”

Section: Embed Sustainable Transport Within Patient Correspondencementioning

confidence: 99%

Evaluating Actions to Improve Air Quality at University Hospitals Birmingham NHS Foundation Trust

et al. 2022

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Air pollution is the single largest environmental risk to human health in the UK, exerting a major healthcare sector burden and exacerbating health and social inequalities. The NHS Long Term Plan commits the healthcare sector to reducing emissions from all sources, however, to date few Acute NHS Trusts have implemented air quality focused sustainability plans. In this case study, we assess potential air quality improvement actions at University Hospitals Birmingham NHS Foundation Trust’s, Queen Elizabeth Hospital in Birmingham, UK as a test case for NHS sustainability actions. We generate an evidenced based, prioritized shortlist of actions to mitigate emissions and protect patients, staff, and local communities from air pollution exposure. The project supports adoption of an evidence-based, contextually relevant, approach to air quality management within healthcare provision. The methodology used could be employed by organizations with similar goals to address environmental concerns.

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“…To address this, we have proposed personalized navigation, taking into account subjective evaluations of walkability, safety, and pleasantness (Furukawa and Wang, 2020). Despite the global pursuit of research into personalized adaptation methodologies, these can potentially diverge from users' actual conditions due to restrictions in model-building techniques and adaptability deficiencies (Novack, 2018;Torres, 2018). Our focus in the practical application of this methodology is on "automatic responsiveness to individual user differences."…”

Section: Introductionmentioning

confidence: 99%

A Study on User-Adaptive Navigation Incorporating Preference of Elderly Pedestrians Using Their Route Evaluation and Walking History

2023

IJCISIS

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Our study aims to devise a new method for route planning that caters to the distinct needs of elderly pedestrians. We established a quantitative model to capture the relationship between the characteristics of elderly users and their route preferences. Additionally, we evaluated a user adaptation methodology that incorporates user preference assessment and walking history data. "Acceptable detour time" was used as a measure of user preferences. As the primary plan, we suggested a method based on post-walking evaluations of route factors by the user, which was validated through an empirical walking experiment, highlighting the feasibility of our approach. However, this approach relies on user input for each route factor, raising concerns over user convenience. To address this issue, we extended our objective to devise a methodology that incorporates walking history, eliminating the need for user input. Drawing insights from an additional walking experiment, we formulated an alternative strategy for adjusting the acceptable detour time in our secondary plan. This strategy estimates the user's evaluation of each route factor by comparing the shortest route with the actual route walked. Application of this method to our experimental data demonstrated its utility and viability, but it also revealed an exacerbation of estimation error with updates in some situations, requiring further research to enhance the efficiency of our proposed methodology.

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PRoA: An intelligent multi-criteria Personalized Route Assistant

Cited by 14 publications

References 14 publications

Walking Secure: Safe Routing Planning Algorithm and Pedestrian’s Crossing Intention Detector Based on Fuzzy Logic App

Walking Secure: Safe Routing Planning Algorithm and Pedestrian’s Crossing Intention Detector Based on Fuzzy Logic App

Evaluating Actions to Improve Air Quality at University Hospitals Birmingham NHS Foundation Trust

A Study on User-Adaptive Navigation Incorporating Preference of Elderly Pedestrians Using Their Route Evaluation and Walking History

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