INTELLIGENT TRAFFIC CONGESTION CONTROL SYSTEM USING A CONTROLLED MACHINE LEARNING ALGORITHM ON ADAPTIVE IOTN

The phenomenon of congestion on the roads occurs when demand rate road or ona transport facility exceeds available capacity, and there are two types: either routine, i.e.occurs at certain times that peak, for example, road, walking returning from work oreducational institutions people; another type – sudden traffic jams have appeared as aresult a accident, is, in event an accident due to other forcemajeure reasons. In this regard, order reduce increase cities, it is possibleand necessary use concept smart systems modern conditions life technologydevelopment. It distinguished by variety algorithms used world machine learning(ML) Internet Things (IoT) more accurately predict flow shortterm identify opportunities prevent congestion. many different sensors canbe collect information short-term city capture thespatial temporal evolution (change) flow. Algorithms embedded learningimprove capabilities system being developed. quality decisions made thedeveloped artificial intelligence increases with simultaneous volume data collected.This article proposes model TCC-SVM analyzing smartcity environment. proposed includes managementsystem reports point. Existing management becomingineffective number vehicles roads. urban areas, trafficjams accidents serious problem. An intelligent solve theproblems caused