Project

# Title Team Members TA Documents Sponsor
43 Digital Twin Bridge Monitoring System
Hanchi Ge
Kowshik Dey
Rongjian Chen
design_document1.pdf
design_document2.pdf
proposal2.pdf
Simon Hu
**Project Advisor:**
Dr. Cristoforo Demartino

**Team Members:**
- Kowshik Arko Dey [arkod2]
- Hanchi Ge [hanchig2]
- Rongjian Chen [rc21]

**Problem:**
Bridges are one of the most vital infrastructures that serve as connectors both inside and outside of a country. They facilitate the movement of people, goods, and vehicles. Despite being marvels of engineering and architecture, accidents in bridges have become more frequent as time passes. The significant causes can be attributed to as being vehicle overloading and structural concerns of the bridge. These type of accidents are more prominent in third world countries, like Bangladesh, where most of the bridges have no monitoring system due to the cost involving these traditional monitoring systems. As a result, the drivers are left to their own assessments and judgements which may lead to accidents and structural damage to the bridges. The development of digital monitoring system can effectively save the money wasted on repetitive maintenance and repair of bridges due to overloading and structural damage.

**Solution Overview:**
The Digital Twin Bridge Monitoring System is designed to address the critical issue of bridge safety and maintenance. This innovative system involves the creation of a digital counterpart for a physical bridge, which is outfitted with advanced pressure sensors. These sensors are crucial for accurately gauging the weight of vehicles as they traverse the bridge, ensuring that the bridge's load capacity is not exceeded. Additionally, the system is equipped with a traffic light mechanism. This feature plays a vital role in warning drivers about potential overloading or existing structural issues, thereby enhancing safety measures.

To demonstrate the practicality and functionality of this system, we plan to construct a scaled-down prototype model. This model will serve as a platform for installing our hardware components, which include various modules such as sensors and a micro-controller. The key to our system's effectiveness lies in the ability to transmit the sensor's processed data to the digital twin platform. This enables the real-time monitoring and detection of the bridge's condition, allowing for immediate responses to any detected problems. Through this advanced monitoring system, we aim to revolutionize how bridge safety is managed, ensuring the longevity and reliability of these critical infrastructures.

**Solution Components:**

*Pressure Sensor Subsystem Overview*
The Sensor Subsystem is strategically designed for early detection of potential risks posed by overweight vehicles. Situated in every lane at the initial incline of the bridge, pressure sensors are meticulously installed. Their primary role is to identify vehicles exceeding the weight limit. Upon detection, the traffic light will show red.

*Displacement Subsystem Overview*
Displacement sensors are used to measure the displacement of a bridge structure, which is critical for us to assess the structural safety of a bridge. Displacement sensors will be strategically placed at key points in the bridge structure, such as supports, beams and joints, to ensure we can fully monitor the health of the bridge.

*Processing Subsystem Details*
The operation of the Processing Subsystem is pivotal for maintaining traffic flow and ensuring safety. Under standard operational circumstances, the traffic signal lights are set to green, allowing vehicles to pass. However, the system is on constant alert for overweight vehicles. The moment an overweight vehicle is identified, the traffic lights switch to flashing red, serving as a clear warning to drivers to halt and not to enter the bridge. Further, should there be any detected structural deformation within the bridge, the signal lights will steadfastly remain red. Moreover, to prevent any approach towards the potentially unsafe bridge, all traffic lights leading to it from the preceding intersection will be deactivated.

The heart of this subsystem is an internal micro-controller responsible for Analog-to-Digital (A/D) conversion and the initial stages of signal processing.

- **Signal Conditioning:** The raw signals from the sensors are often weak and noisy. Signal conditioning modules are used to amplify, filter, and convert these signals into a format suitable for digital processing.
- **Analog-to-Digital Conversion (ADC):** The conditioned analog signals are converted into digital data through ADC. This conversion is essential for the subsequent data analysis and digital twin simulation.
- **Data Processing Unit:** A micro-controller processes the digital data, performing preliminary calculations and data compression to reduce the amount of data to be transmitted.
- **Data Transmission:** The processed data is transmitted to the Digital twin software.

*Power Subsystem Functionality*
It efficiently converts AC power, commonly available from standard outlet sources, into the DC voltages required by the various components of the system. This includes the sensors, micro-controller, and communications modules, thereby guaranteeing their uninterrupted operation and performance.

**Criterion for Success:**
Successful development and integration of the scaled physical model, software, and hardware components. The scale model can use pressure sensors to measure the weight of the passing model car, and when the weight of the car exceeds our preset standard, the signal light of the scale bridge will be red to warn the driver. At the same time, the

signals obtained from the scale model, such as pressure signals and structural deformation signals of the bridge, need to be transmitted in real time to the digital twin monitoring system. Comprehensive documentation of the project's design, implementation, and testing process.

---

BusPlan

Featured Project

# People

Scott Liu - sliu125

Connor Lake - crlake2

Aashish Kapur - askapur2

# Problem

Buses are scheduled inefficiently. Traditionally buses are scheduled in 10-30 minute intervals with no regard the the actual load of people at any given stop at a given time. This results in some buses being packed, and others empty.

# Solution Overview

Introducing the _BusPlan_: A network of smart detectors that actively survey the amount of people waiting at a bus stop to determine the ideal amount of buses at any given time and location.

To technically achieve this, the device will use a wifi chip to listen for probe requests from nearby wifi-devices (we assume to be closely correlated with the number of people). It will use a radio chip to mesh network with other nearby devices at other bus stops. For power the device will use a solar cell and Li-Ion battery.

With the existing mesh network, we also are considering hosting wifi at each deployed location. This might include media, advertisements, localized wifi (restricted to bus stops), weather forecasts, and much more.

# Solution Components

## Wifi Chip

- esp8266 to wake periodically and listen for wifi probe requests.

## Radio chip

- NRF24L01 chip to connect to nearby devices and send/receive data.

## Microcontroller

- Microcontroller (Atmel atmega328) to control the RF chip and the wifi chip. It also manages the caching and sending of data. After further research we may not need this microcontroller. We will attempt to use just the ens86606 chip and if we cannot successfully use the SPI interface, we will use the atmega as a middleman.

## Power Subsystem

- Solar panel that will convert solar power to electrical power

- Power regulator chip in charge of taking the power from the solar panel and charging a small battery with it

- Small Li-Ion battery to act as a buffer for shady moments and rainy days

## Software and Server

- Backend api to receive and store data in mongodb or mysql database

- Data visualization frontend

- Machine learning predictions (using LSTM model)

# Criteria for Success

- Successfully collect an accurate measurement of number of people at bus stops

- Use data to determine optimized bus deployment schedules.

- Use data to provide useful visualizations.

# Ethics and Safety

It is important to take into consideration the privacy aspect of users when collecting unique device tokens. We will make sure to follow the existing ethics guidelines established by IEEE and ACM.

There are several potential issues that might arise under very specific conditions: High temperature and harsh environment factors may make the Li-Ion batteries explode. Rainy or moist environments may lead to short-circuiting of the device.

We plan to address all these issues upon our project proposal.

# Competitors

https://www.accuware.com/products/locate-wifi-devices/

Accuware currently has a device that helps locate wifi devices. However our devices will be tailored for bus stops and the data will be formatted in a the most productive ways from the perspective of bus companies.