Automation has significantly simplified our daily lives, but the escalating number of vehicles on the roads, particularly in Bangladesh, has led to persistent traffic congestion and increased human effort. The existing manual traffic light system proves inadequate for addressing this issue promptly. To address this, we propose an experimental solution, an automated traffic signal system operating 24/7 with Machine-to-Machine (M2M) communication. This system aims to minimize human effort, save time, and effectively alleviate traffic congestion. Our approach involves a vehicle density measurement device utilizing a Light-Dependent Resistor (LDR) and laser technology to gauge the density of passing vehicles. This device identifies the maximum number of cars within a predetermined time frame. If the LDR detects a high volume of traffic, signaling excessive congestion, this information is relayed to the master unit (ESP32). Conversely, if the LDR registers a normal flow with fewer vehicles, this data is also transmitted to the master unit. The master unit analyzes the data to determine the traffic conditions. In typical situations, when the LDR and laser detect a vehicle, the corresponding green LED is illuminated. This dynamic adjustment of LED status based on vehicle density helps mitigate undesirable traffic congestion, ultimately saving valuable time for the public. Notably, our solution operates without the need for internet connectivity for M2M communication.


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    Titel :

    Density Based Traffic Signal Light Control with Machine to Machine Communication System




    Erscheinungsdatum :

    2024-03-08


    Format / Umfang :

    1431702 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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