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- W4320801962 abstract "Traffic has been a major problem in recent times. Traffic management is a must for safer and faster transportation. Automatic smart signal controlling systems respond to day-to-day world traffic densities to provide precedence and reduction in cross-road delays for travelers. According to the traffic density, the time between signals is adjusted so that the waiting time in traffic reduces. The ML model is capable of detecting accidents and immediately sends notifications or alert messages to nearby hospitals. The model tracks the GPS location of the ambulance and ensures no red signal in its pathway. Zebra crossing signals are also included, the signal timings are switched based on the crossing crowd. Automatic Smart Signal Control is a complete Machine Learning based project with some applications of IoT and Video / Image processing. Implementation of the model all over the major signals and junctions provides faster and safer transportation." @default.
- W4320801962 created "2023-02-15" @default.
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- W4320801962 date "2022-11-09" @default.
- W4320801962 modified "2023-09-30" @default.
- W4320801962 title "Various Algorithms and Techniques for Traffic Density Estimation" @default.
- W4320801962 doi "https://doi.org/10.1109/iccst55948.2022.10040397" @default.
- W4320801962 hasPublicationYear "2022" @default.
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