Cost-Efficient and Smart Automated Structural Health Monitoring System using Micro-Controller UAV-Driven Drone

Progressive deterioration of civil infrastructures such as buildings, bridges, aircraft, ships, and trains can lead to catastrophic failure and present a threat to public safety. During the last few years, there has been an increasing interest in studying and predicting the failure modes of

Project Title

Cost-Efficient and Smart Automated Structural Health Monitoring System using Micro-Controller UAV-Driven Drone

Project Area of Specialization

Internet of Things

Project Summary

Progressive deterioration of civil infrastructures such as buildings, bridges, aircraft, ships, and trains can lead to catastrophic failure and present a threat to public safety. During the last few years, there has been an increasing interest in studying and predicting the failure modes of such structures by instrumenting them with numerous sensors and collecting data on their response to stresses and vibrations. Such an approach is the basis of Structural Health Monitoring (SHM) technology.

Structural cracks are a vital feature in evaluating the health of ageing structures. Inspectors regularly monitor structures’ health using visual information because early detection of cracks on highly trafficked structures is critical for maintaining the public’s safety. In this work, a framework for detecting cracks along with their locations is proposed. Image data provided by an unmanned aerial vehicle (UAV) is stitched using image processing techniques to overcome limitations in the resolution of cameras[1]. This stitched image is analyzed to identify cracks using Micro Controller Sensors that make judgements regarding the presence of cracks in the image. Moreover, cracks’ locations are also determined using data from UAV micro controller sensors. To validate the system, cracks forming on an actual building are captured by a UAV, and these images are analyzed to detect and locate cracks. The proposed framework is proven as an effective way to detect cracks and to represent the cracks’ locations. 

Sensors are available in abundance at markets worldwide but unfortunately, due to high cost, utilizing and installation are burdensome. So out of survey, we must come to a comparatively cost-effective sensor which is easy to handle and pocket friendly. Microcontroller based circuit can readily detect any defect in concrete structures and highly efficient[2].

PAST EVENTS OF BUILDING FAILURES IN PAKISTAN DUE TO VITAL CRACKS AND THEIR LACK OF ASSESMENT:

Reference 

[1] Prateek Prasanna, Kristin J. Dana, Nenad Gucunski, Basily B. Basily, Hung M. La,Ronny Salim Lim, and Hooman Parvardeh, “Automated Crack Detection on Concrete Bridges”, IEEE Transactions On Automation Science And Engineering, Vol. 13, No. 2, April 2014

[2] Wenyu Zhang, Zhenjiang Zhang, Dapeng Qi and Yun Liu, “Automatic Crack Detection and Classification Method for Subway Tunnel Safety Monitoring”, Sensors 2014, 14, ISSN 1424-8220,19307-19328.

Fig 01: At least 16 people have been reported dead after a building failure in Karachi’s Central district Gulistan Colony. This failure occurred on March 5, 2020

Fig. 02: Six-storey residential building collapses in Karachi's Ranchhore Line

Fig. 03: Costly and dangerous structure safety diagnosis using excavation procedure

Project Objectives

1. To develop a Smart and Cost-Efficient structural health monitoring system to detect Cracks severity.
2. To Conduct Frequent Surveys of various structures to familiarize with the possibility of cracks according to their shapes and depth.
3. To develop a system that can detect cracks according to crack thickness and depth using collected from the microcontroller.  
4. To automate an early warning system and damage assessment using AI.

Project Implementation Method

There are mainly four modules for the proposed crack detecting scheme such as;

• UAV (Multi-rotor Drone)
• Software application for detecting the severity of cracks with respect to its width
• Programming Hardware Unit (ATMEGA 328 Microcontroller)
• Image Processing Unit (Laptop/PC)

Drone Unit carry a camera with the proposed sensor device that will fly around the inside and outside perimeter of the building surface in order to detect the cracks on the structures (beams, walls, Columns, Slabs etc). The main heart of programming the hardware unit is microcontroller. A high-resolution camera has been used in order to collect images of surfaces. A global map will also be created for locating the position of cracks that can transmit the captured images. By using the wireless method like Bluetooth; or IOT, images are sent to the laptop where images are processed through image processing techniques (software). Thus, a wireless connection will be established between the Drone Unit and laptop. An algorithm is to be developed for crack detection, path planning of drone and then program the microcontroller by the programmer. Once the crack has been detected successfully and images are sent along with the location, the drone unit will fly further on the model path till next crack has been detected.

BLOCK DIAGRAM OF PROPOSED SYSTEM:

SOFTWARE APPLICATION FOR DETECTING THE SEVERITY OF CRACKS:

A software application (like Single shot multibox detector) will be developed to identify the severity of cracks according to width measurement for Example If the width of crack is larger than 0.3mm, maintenance work is started, and if it is 0.3mm to 0.2mm, the trend is observed. Cracks less than 0.2 mm are considered to be of low risk. Languages which we will be using for developing a software application will be; C++, Python, Anaconda.

CRACK DETECTION USING IMAGE PROCESSING:

1. Firstly, the images of the structures for the process of crack detection have been collected by using camera or any other sources via drone.
2. The collected images are preprocessed after the segmentation in which different methodologies are done in order to make it an efficient one for the purpose of image processing.
3. In the image processing step, some of the techniques will be employed to process the deducted image sample. (Means if the taken images are blurred or less pixelated therefore techniques like gray scaling could be employed to detect the cracks, this method require no software, since it’s a filtering process on taken images).
4. By using the result of the processed image, cracks will be detected on the structure through the software application with respect to its width.
5. Finally, the detected cracks will be extracted based on different parameters like shape, size, width.

        width

     > 0.3mm

  0.3mm ~ 0.2mm

      <0.2mm

Benefits of the Project

1. Automation of safety diagnosis

Some of the safety diagnoses of concrete structures can be automated. We will develop our software application in such a way that it gives the information on which cracks require a further diagnosis based on crack width. This will help make further detailed diagnostics in the future more efficient.

2. Saving time for safety diagnosis:

You can know in advance the location and severity of cracks that require a further detailed diagnosis. This is because, based on the width cracks, the highest severity cracks are reported first. Therefore, the time required for safety diagnosis is shortened.

3. Universality:

Concrete cracks all show a similar pattern, regardless of the type of building, region, or country. In other words, it can achieve the same performance regardless of which region or type of target is applied, and it can be used without additional modification.

4. Less Manpower:

Another main advantage of this project is to accomplish a complete tool that will lessen the requirement of manpower for detecting the concrete failures in the pre-constructed building.

Technical Details of Final Deliverable

The project will deliver an advanced yet cheap health monitoring system that can detect cracks and provide information based on severity level to the owner via software to assess. The owner receives clear information on whether the crack needs to be repaired or replaced 

By using the result of the processed image, crack has been detected in the structure.

Finally, the detected cracks have been extracted based on different parameters like shape, size, width,
depth etc.

            

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Health

Other Industries

IT , Others , Security

Core Technology

Artificial Intelligence(AI)

Other Technologies

Internet of Things (IoT), Others

Sustainable Development Goals

Industry, Innovation and Infrastructure, Sustainable Cities and Communities, Life on Land, Partnerships to achieve the Goal

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com