The detection of cracks in solid infrastructure is a setback of immense significance. Particularly, the detection of cracks in buried pipes is a crucial step in assessing the degree of pipe deterioration for municipal and utility operators. The most widespread ways at currently is time intense and labour demanding as it entails lagging removal; check using the usual non-destructive assessment practices such as visual, ultrasonic or radiography; and lagging replacement. This can also necessitate that the tools are shutdown adding up to extra financial burden to plant repairs and function. Automation has ever since the industrial uprising been used in industries and businesses to improve effectiveness and competency. A greater number of jobs are presently done by machines as an alternative to human effort. The Mindstorm robot intends to solve the problem of detecting flaws in a pipe through its intelligent sensors to provide a monitoring platform along the entire distance of the pipeline and use its NXT tools to monitor and ultimately predict the occurrence of defects.

Maryam Temitayo Ahmed is a BSc Computer Science graduate from Olabisi Onabanjo Univesity and MSc graduate of University of Nottingham. This work is part of my research findings as partial fulfillment of my course completion from the University of Nottingham which tends to simulate the detection of flaws in a pipe using the Mindstorm robot.