A construction cost estimation framework using DNN and validation unit

Accurate construction cost estimation is crucial to completing projects within the planned timeframe and expenditure. The estimation process depends on multiple variables maintaining complex relationships between themselves and the target cost. As a result, an in-depth analysis from an experienced construction consultant is required to estimate construction costs accurately. Machine learning (ML) technology can learn from previous data, which is equivalent to human experience. Many project-specific ML models estimate the construction cost, which misses the generalizability. This paper addresses the gap and designs, develops, implements, and analyzes a deep learning (DL) based novel framework that maps 94.67% of the independent variables with a mean average percentage error (MAPE) of 11.60%. The proposed framework is not limited to any specific project. It estimates the construction cost of similar projects, further validated by an innovative estimator validation unit

The legacy of Verena Holmes: inspiring next generation of engineers

Verena Holmes was born in 1889 in Ashford, Kent, Verena became a pioneer for women in the industry as arguably the first female in the UK to have a full-time career as a professional mechanical, design and biomedical engineer. Verena was an advocate for widening participation in engineering and dedicated to the development of female engineers, she represented a breakthrough for equal rights in the early 20th century. As a creative and talented mechanical engineer, inventor and entrepreneur with own engineering business in Gillingham, Kent. In 1932, Verena Holmes filed a patent for poppet valve for fluid pressured systems, and in 2021 has provided the inspiration to students to conceive, design, implement and operate their own poppet valve. The poppet valve challenging first year biomedical, mechanical and product design engineering students to consider engineering materials, engineering manufacturing, standard components, fixes and fittings, and tolerances considerations into their poppet valve. This paper will provide qualitative analysis of the level of practical engineering learning, and the depth of student learning. Also, the quantitative analysis of the students’ evaluation of the learning opportunity to inspire, develop and stimulate them to be the next generation of engineers

Practice-based engineering design for next-generation of engineers: A CDIO-based approach

In recent years, practice-based learning has been establishing itself as a new norm in higher education: an enabler to foster knowledge, skills and innovative thinking in young learners. Conceive, design, implement and operate (CDIO), a well-established pedagogical methodology, offers many opportunities for education providers seeking to best achieve this practice-based learning within various educational environments. Case studies of engineering programs that made use of the CDIO model provide illustrations of how the ideas were put into effect in actual projects. This paper draws on a CDIO-based design case study where students were requested to solve a real engineering problem; in order to explore the great potential of such a teaching and learning paradigm in practice settings. Some first-year mechanical, biomedical and product design engineering students studying at the Canterbury Christ Church University were set a design brief by a Ford Motor Company tier supplier, to design a high security lock for commercial vehicles which works on both sliding and rear hinged slam doors. The project had twelve engineering groups, each with three or four students sharing responsibility for separate project design and engineering roles: including design sketches; computer-aided modelling; engineering material investigation; finite element analysis; computer-aided manufacturing; prototyping; project reporting and company presentation. In order to analyse the effect of incentives on the underlying motivation of learners, a cash prize was secured via the Engineers in Business Fellowship (EIBF) organisation, to be shared between the winners selected by the industrial partner after a detailed study of benefits, manufacturability and potential innovation. This paper documents the findings of collected qualitative and quantitative data as part of this project-based case study, and furthermore, reflects on the effectiveness of CDIO implementation on the depth of students’ knowledge and level of practical engineering learning. The objective here is to evaluate the individual and collaborative learning processes that occur among a group of students as they use CDIO active learning tactics. The analysis reported in this paper can serve as a foundation to illustrate how educators may better prepare their students for joining the workforce of the future, by using an active learning approach that provides more weight to practical than theoretical knowledge

Integrating AI into engineering education: Leveraging CDIO for enhanced assessment strategies

The recent advancements of generation artificial intelligence (Gen AI) and large language model (LLM AI) in content creation and manipulation have brought significant challenges to teaching and learning in various disciplines. These challenges have called for a transformative change in traditional teaching and assessment strategies to accommodate the latest technological advancements, without compromising the integrity of assessments and evaluations. Many higher education institutions (HEIs) have employed critical thinking tasks within their evaluation methods to stimulate a thought process that would be difficult to simulate by AI-assisted technologies. However, it has been repeatedly observed that even analytical topics such as mathematics and core engineering modules were susceptible to the corruptive use of AI-assisted technologies in their assessments, which fundamentally demeans the educational qualifications’ quality across the HEIs. Equally well researched and developed machine learning AI (ML AI) can assist in data processing, pattern recognition and analysis. Having witnessed the advantages of CDIO (conceive, design, implement, operate)-based curricula in fostering innovation, critical thinking, and analytical skills across engineering, technology and design courses, this paper designs a modern strategy that harnesses the novelties of AI technologies within a CDIO-based pedagogy. This is as Gen AI has the potential to assist students in evaluating their conceived ideas at “C” stage, feedback on “D” and machine learning AI (ML AI) analysis of “O” stages, shortening the project lifecycle. Using the existing case-studies on CDIO-based teaching and learning, the intersection of CDIO principles and AI technologies have been mapped to identify opportunities and interferences. The findings demonstrated the empowerment of each CDIO stage, conceive, design, implement and operation, through the effective and optimum use of technology, both in teaching methods and in assessments. Therefore, this paper presents a modern approach to teaching and learning, acknowledging the opportunities and risks of AI within the engineering curriculum. It demonstrates the potential benefits of AI in CDIO pedagogy, to not only reduce the risks but also harness the potential benefits as a stimulating tool rather than a replicating technology. The output of this work offers rich insights to HEIs who seek to embrace the positive aspects of AI technologies while preserving the resilience and integrity of their practices in this era of technology

Cybersecurity of smart buildings: a facilities management perspective

The cybersecurity of smart buildings is often perceived from the technological aspects of cybersecurity, pertaining to the cybersecurity of the smart devices and systems installed in facilities. Facilities management (FM) organisations responsible of managing and controlling the buildings using building management systems (BMS) are increasingly collaborating with various stakeholders using digital platforms that enable access to facilities' data. This results in an increased risk of cybersecurity attack to the FM systems, that may enable unwanted access to BMS systems. Poor cybersecurity management in FM may result in disastrous impacts on the facilities and operations within. Therefore, this paper investigates the cybersecurity risks to a smart building, from a facilities management perspective and provides recommendations of the ways in which FM can minimise the risks

A digital approach to health and safety management on-site: A silver lining of the COVID-19 pandemic

The unprecedented distress brought about by ‎COVID-19 has severely impacted the ‎performance of the construction ‎industry. On-site activities face labour ‎shortages and the withdrawal of clients ‎from existing or planned projects, has ‎left huge financial burdens on the ‎contractors and sub-contractors. Thus, ‎digital solutions and tools enabling ‎remote and autonomous work have ‎become more popular. This ‎chapter discusses technological ‎remedies including IoT and Cloud-‎based solutions, smart wearables, and ‎robotic construction , ‎used to assist the industry’s recovery from the aftermath of COVID-19. It also sheds light ‎on the shortfalls of technology ‎implementation for health and safety ‎management on site, through 21 semi-‎structured interviews with construction ‎professionals with relevant experience. The findings demonstrate positive ‎implications of the pandemic, in ‎pushing the industry towards digital ‎transformation; however, the need for investments and ‎training programs to deploy ‎technology on site thus becomes apparent. This ‎research informs the body of ‎knowledge of the challenges and ‎opportunities of digital transformation ‎amongst small and medium ‎construction stakeholders, to encourage the ‎development of strategic health and ‎safety management plans that enable a ‎smooth transition towards digital ‎construction on site, post pandemic