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project2.html
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<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Document</title>
<link rel="stylesheet" href="project2.css">
<link href="https://unpkg.com/[email protected]/dist/aos.css" rel="stylesheet">
</head>
<body>
<nav id="nav" >
<a href="./index.html"><img class="logo" src="./images/logo-removebg-preview (1).png" alt=""></a>
<ul class="list">
<li><a href="#about">About</a></li>
<li><a href="#Project">Projects</a></li>
<li><a href="#Mission">Our Mission</a></li>
<li><a href="#Contact">Contact</a></li>
</ul>
<button class="search">Search</button>
<button class="menu">Menu</button>
</nav>
<div id="particles-js"></div> <!-- stats - count particles -->
<div class="count-particles">PROJECT 2</div>
<!-- ............................... -->
<div class="afterDiv">
<div class="responsive-container-block bigContainer" id="about" data-aos="fade-down-right">
<div class="responsive-container-block Container bottomContainer">
<div class="ultimateImg">
<img class="mainImg" src="./images/project2.png">
</div>
<div class="allText bottomText">
<p class="text-blk headingText">
Requirement
</p>
<p class="text-blk description">
The aim of the project is to use machine learning
to study and analyze different types of road
defects and to automatically detect any road
abnormalities. We will design, build and test an
inspection system for this purpose
</p>
</div>
</div>
</div>
<div class="responsive-container-block bigContainer" id="about" data-aos="fade-down-right">
<div class="responsive-container-block Container bottomContainer">
<div class="ultimateImg">
<img class="mainImg" src="https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcTdDidYPp8T-5ZnQGUcQpR2q95ohE7UEt5Tnw&usqp=CAU">
</div>
<div class="allText bottomText">
<p class="text-blk headingText">
Approach </p>
<p class="text-blk description">
The system is equipped with a camera to collect
video streams from different roads with and
without defects. Then, the captured data will be
analyzed using the Matlab machine learning
toolbox to train and test the network. Finally, the
system will provide recommended actions for the
municipality related to actions required to
fix/correct road defects. The approach is divided
into 4 main tasks: Data acquisition, Data
Training/Testing, and Dashboard Building and
Testin
</p>
</div>
</div>
<div class="technologiesUsed">
<h1>Technology and
resources used</h1>
<p>
Our road inspection system utilizes advanced
technology to automate the detection of road defects
and damages. Equipped with HD cameras, the system
captures live video streams from roads, allowing for
comprehensive data acquisition. The captured data is
then analyzed using the Matlab machine learning
toolbox, enabling the training and testing of a network
that can accurately categorize road flaws. By leveraging
machine learning algorithms and image processing
techniques, the system can detect various road defects,
including cracks, patching, rutting, and deformation. It
further enhances efficiency by providing recommended
actions for municipalities to address and correct the
identified road issues. Additionally, the system
incorporates a user-friendly dashboard and graphical
interface to visualize and report the detected road
defects in real-time. This project showcases the power
of technology in streamlining road inspections and
improving infrastructure maintenance practices.
</p>
</div>
</div>
<footer id="footer" id="Contact" data-aos="zoom-in-up" data-aos="fade-down-right">
<div class="footer">
<div class="row">
<ul>
<li><a href="#">Contact us</a></li>
<li><a href="#">Our Services</a></li>
<li><a href="#">Privacy Policy</a></li>
<li><a href="#">Terms & Conditions</a></li>
<li><a href="#">Career</a></li>
</ul>
</div>
<div class="text-center" data-aos="fade-down-right">
Copyright © 2023 - All rights reserved || Designed By: Ayush
</div>
</div>
</footer>
</div>
<script src="http://cdn.jsdelivr.net/particles.js/2.0.0/particles.min.js"></script> <!-- stats.js lib -->
<script src="http://threejs.org/examples/js/libs/stats.min.js"></script>
<script src="./project2.js"></script>
<script src="https://unpkg.com/[email protected]/dist/aos.js"></script>
<script>
AOS.init();
</script>
</body>
</html>