Abstract :
In the article, the multi-agent platform for convergent sensor data processing in a monitoring system for Smart
Road Infrastructure are considered. The platform works with a network of spatially distributed photo-radar complexes, which in real time record road accidents. The paper discusses tools for collection of road accident’s photo and video data fixation, data mining and forecasting of transport incidents, depending on various factors (meteorological, social, operational, etc.). The results of monitoring and analysis of traffic accidents, fixed by an intelligent monitoring system with photo-radar complexes are considered. The connection between the complexes and the data processing center using a heterogeneous wireless network is established. A multi-agent approach developed to address the tasks of sensor data collecting and processing. Convergent approach is the convergence of cloud, fog and mobile data processing technologies. The structure of the neural network is adapted to the diagnosing problems and forecasting. The tasks of intellectual analysis and forecasting traffic accidents solved. The hybrid fuzzy neural network synthesized. Because the comparison of time series of traffic accidents and time series of meteorological factors, it established that the presence of factors to become determinants for an abnormal change in the traffic situation in controlled areas. The monitoring
system is a part of Smart Road Infrastructure within the framework of the Smart & Safe City concept.
Keyword :
multi-agent platform; convergent data processing; monitoring system; smart road infrastructure; wireless sensor networks; machine learning; convergent model; smart&safe city; big sensor data