Smart crowd monitoring and control system

Controlling system

1. SMART CROWD MONITORING AND CONTROL SYSTEM FOR PREVENTING BRIDGE OVERLOAD AND COLLAPSE

2. TEAM MEMBERS L. Sasidhar Reddy (22001A0459) V. Mohan Kumar (22001A0417) S. Venkatesh Naik (22001A0454) K. Suresh (22001A0445) S. Kathyayani (22005A0405) MENTOR Dr.S.Chandra Mohan Reddy Professor of ECE Department

3. abstract:- The study proposes an intelligent crowd control system using weight sensors and infrared (IR) sensors to monitor real-time traffic flow on bridges. Weight sensors detect load distribution to prevent excessive stress on the structure, ensuring stability and safety. IR sensors track pedestrian and vehicle movement, identifying congestion and irregularities in traffic flow. The system uses Internet of Things (IoT) technology to analyze data and trigger automated responses, such as dynamic lane adjustments and warning signals. By integrating these technologies, the proposed system aims to enhance safety, optimize traffic flow, and minimize risks associated with overcrowding and structural overload.

4. Problem dEFINATION :- Bridges are critical infrastructures that facilitate transportation and connectivity. However, excessive crowd density on bridges, especially during public events, festivals, or emergencies, can lead to structural overload, increasing the risk of collapse. Traditional crowd management techniques, such as manual monitoring and static weight limit enforcement, are often inadequate in real-time dynamic scenarios. To address this challenge, a Smart Crowd Control and Monitoring System is proposed. This system will leverage advanced technologies, including IoT-enabled weight sensors, AI-driven crowd analytics, and real-time surveillance, to monitor pedestrian density, detect overload conditions, and trigger automated alerts. By integrating smart sensors and AI-powered predictive analysis, the system can provide proactive measures to prevent potential disasters.  

5. Block Diagram:

6. COMPONENTS USED :- Arduino uno Ir sensor Load cell with hx711 module Liquid crystal display (16x2) Servo motor Connecting wires Bread board mini

7. SENSORS :- Load Cell (HX 711): IR SENSORS: An IR sensor (Infrared sensor) is a device that detects infrared radiation, which is a type of electromagnetic radiation that is not visible to the human eye but can be felt as heat. IR sensors are used in a wide range of applications, from motion detection to communication. A load cell is a type of transducer used to measure force or weight by converting the mechanical force (or weight) applied to it into an electrical signal. It's a critical component in many weighing systems, including industrial scales, digital scales, and even in specialized applications like pressure sensors, force testing, and more.

8. LCD (I2C): Servo Motor: A servo motor is  a rotary actuator that allows for precise control of angular position . It consists of a motor coupled to a sensor for position feedback . It also requires a servo drive to complete the system. The drive uses the feedback sensor to precisely control the rotary position of the motor. An LCD (Liquid Crystal Display) is a flat-panel display technology that uses liquid crystals to modulate light, creating images or text. Unlike older display technologies, such as CRT, LCDs are lightweight, energy-efficient, and compact. They rely on a backlight (usually LED) since liquid crystals do not emit light on their own. The crystals align to control the passage of light, forming pixels that display images, characters, and graphics.

9. Technology used :- Arduino IDE Software The arduino software (IDE) is an open source software, which is used to programme the Arduino boards, and is an  integrated development environment , devlopped by arduino.cc. Allow to write and upload code to arduino boards. And it consiste of many libraries and a set of examples of mini projects.

10. WORKING :- Sensor Integration : Uses infrared (IR) sensors to detect the presence of people and weight sensors (like HX711) to measure total load on the bridge. Data Processing : Continuous data from sensors is sent to an Arduino Uno, which processes and compares it with predefined thresholds. Corrective Actions : If thresholds are exceeded, Arduino triggers actions such as closing gates with a servo motor to prevent additional people from entering. Real-Time Updates : LCD module provides real-time status updates on crowd density, total weight, and safety warnings. Safety Alerts : Activates visual or auditory alarms in case of overload to alert authorities and the public. This system efficiently monitors and controls crowd and weight on the bridge to prevent overload and potential collapse.

11. CONTROL FLOW DIAGRAM:

12. Future scope: Integrating cloud computing with IoT-based bridge monitoring offers several future advancements. With real-time updates on a website, authorities can track the hourly vehicle count and average vehicle weight on the bridge, improving decision-making and safety measures. AI & Predictive Analytics – Machine learning can analyze past data to predict peak traffic hours and potential overload risks, enabling proactive measures. Smart Alerts & Automation – The system can send automated alerts via SMS/email if weight limits exceed, allowing immediate action. Integration with Traffic Control – Traffic signals can be synchronized to regulate vehicle flow based on bridge capacity. Blockchain for Data Security – Secure and tamper-proof storage of bridge usage data for long-term analysis. Mobile App Integration – Users can check bridge congestion levels before travel. This system ensures smoother traffic management, enhanced bridge safety, and data-driven urban planning for future smart cities.

13. THANK YOU…