Transfer Learning-Based Crack Detection by Autonomous UAVs

Unmanned Aerial Vehicles (UAVs) have recently shown great performance collecting visual data through autonomous exploration and mapping in building inspection. Yet, the number of studies is limited considering the post processing of the data and its integration with autonomous UAVs. These will enable huge steps onward into full automation of building inspection. In this regard, this work presents a decision making tool for revisiting tasks in visual building inspection by autonomous UAVs. The tool is an implementation of fine-tuning a pretrained Convolutional Neural Network (CNN) for surface crack detection. It offers an optional mechanism for task planning of revisiting pinpoint locations during inspection. It is integrated to a quadrotor UAV system that can autonomously navigate in GPS-denied environments. The UAV is equipped with onboard sensors and computers for autonomous localization, mapping and motion planning. The integrated system is tested through simulations and real-world experiments. The results show that the system achieves crack detection and autonomous navigation in GPS-denied environments for building inspection

Process improvement and automation in construction: Opposing or complementing approaches?

It is widely recognized that there must be wide-ranging changes in construction before automation can be implemented in practice. On the other hand, the innovation rate of construction is rather low, and thus it is unclear, how the steps necessary for automation could be realized. It is argued, that an insufficient attention to process improvement is a major barrier to automation and other technological progress of construction

Automatic Crack Detection in Built Infrastructure Using Unmanned Aerial Vehicles

This paper addresses the problem of crack detection which is essential for health monitoring of built infrastructure. Our approach includes two stages, data collection using unmanned aerial vehicles (UAVs) and crack detection using histogram analysis. For the data collection, a 3D model of the structure is first created by using laser scanners. Based on the model, geometric properties are extracted to generate way points necessary for navigating the UAV to take images of the structure. Then, our next step is to stick together those obtained images from the overlapped field of view. The resulting image is then clustered by histogram analysis and peak detection. Potential cracks are finally identified by using locally adaptive thresholds. The whole process is automatically carried out so that the inspection time is significantly improved while safety hazards can be minimised. A prototypical system has been developed for evaluation and experimental results are included.Comment: In proceeding of The 34th International Symposium on Automation and Robotics in Construction (ISARC), pp. 823-829, Taipei, Taiwan, 201

Teaching and learning mathematics and science in English in primary schools in the state of Johor, Malaysia

This article attempts to highlight the opinions of the public on the effectiveness of the use of English in teaching and learning Mathematics and Science (PPSMI) in primary schools in Johor. After nearly six years of its implementation, some people found out that the students have not demonstrated a good command of the language and the acquisition of knowledge of Mathematics and Science is seen to be declining. The teachers also do not seem to adapt well in the implementation. A group of respondents from among the headmasters and headmistress have given their views through a questionnaire and structured interview that showed the government's intention to strengthen the English language in teaching and learning Mathematics and Science did not show an impressive result. Thus, the study suggests that the government can try to give an option of using both languages in the implementation of this policy

Robotizing Workforce in Future Built Environments

The aim of this paper is to define challenges for Automation and Robotics in construction (A+R) to enhance client and social value. Construction contributes to a positive living environment for society and is the largest sector of Europe’s economy with a size of around 2,500 billion Euros. Ten research projects have been analyzed to select the challenges for development. These challenges present a road map for Automation and Robotics in construction particularly on Human-machine technologies, Process management and Performance engineering