ArticleSensors (Basel, Switzerland)2022
Development of a GIS-Based Methodology for the Management of Stone Pavements Using Low-Cost Sensors.
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 3 papers.
What it found
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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.
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.
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Who cites it
3 citing papers in PubMed, 11 citations in OpenAlex.
- A Robotized Raspberry-Based System for Pothole 3D Reconstruction and Mapping.Sensors (Basel, Switzerland) · 2023Article
- Torque Measurement and Control for Electric-Assisted Bike Considering Different External Load Conditions.Sensors (Basel, Switzerland) · 2023Article
- Pavement Distress Estimation via Signal on Graph Processing.Sensors (Basel, Switzerland) · 2022Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Stone pavements are present in many cities and their historical and cultural importance is well recognized. However, there are no standard monitoring methods for this type of pavement that allow road managers to define appropriate maintenance strategies. In this study, a novel method is proposed in order to monitor the road surface conditions of stone pavements in a quick and easy way. Field tests were carried out in an Italian historic center using accelerometer sensors mounted on both a car and a bicycle. A post-processing phase of that data defined the comfort perception of the road users in terms of the
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Registered trials
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.