Statistics based on Trafsense data can detect degradation of the road surface, development of cracks, pot holes, etc. Such data and statistics may be correlated with weather data, seasons, repeated external traffic events, etc. as input to machine learning.
Real time Trafsense data may identify degrading driving conditions due to heavy rain or snow, fog, oil spills, lost goods, etc. This may trigger a quick response from the road authorities in the form of changes of signage (e.g., reduced speed limit, warning signs, push warnings, etc) or immediate road maintenance: Filling of pot holes, sanding, removal of snow, oil or goods lost from a flat bed truck.
Trafsense can detect both real time changes and slower changes over hours / days / weeks / seasons for optimisation of road maintenance, road design and signage, etc. Such statistical data, coupled with machine learning and correlated with weather data etc, will facilitate a bespoke reference system for refined analysis of traffic data.
.jpg)
.jpg)