Comparative study of the road roughness measurement of Roadlab Pro and Roadroid applicatons for IRI data collection in NigeriaEkpenyong, E.E. ORCID: https://orcid.org/0000-0001-8509-5309, Abu, A.S.P. and Cinfwat, K.Z. (2021) Comparative study of the road roughness measurement of Roadlab Pro and Roadroid applicatons for IRI data collection in Nigeria. The International Journal of Engineering and Science (IJES), 10 (5). pp. 14-19. ISSN 2319-1813 ISSN
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.9790/1813-1005031419 Abstract/SummaryModern smartphones are equipped with many useful sensors. These sensors range from gyroscopes to global position systems (GPS) and sensors like magnetometers and three-dimensional accelerometers in-between. These sensors being used by applications installed in the phones can be used to measure the level of serviceability of a road by measuring the international roughness index (IRI). Early researchers have established that the World Bank standard of IRI was the method used in assessing road conditions. It serves as a means of evaluating the conditions and level of serviceability of a road network. This paper evaluates the roughness, surveyed length and vehicle speed measurement using RoadLab Pro (open sourced) and Roadroid (commercial) applications along selected routes. The selected route was carried on four major road networking the Federal Capital Territory (FCT) to neigbouring state capitals. Result show significant proximity in values for total surveyed length and average vehicle speed with error margins within 0.008% - 2% and 0.58% - 3.33% respectively. It was observed that RoadLab Pro smartphone application failed to sense data on sections of road with total/partial pavement deterioration; this may be a failure which smartphone applications reliant on accelerometers as primary roughness sensors may not detect. However, both applications performed consistently on roads with severe rutting. Furthermore, IRI values for certain routes were on different IRI condition category. Lastly, the study reveals that it is possible to get Road Asset Management System (RAMS) data in an inexpensive manner. ------------------------
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