Chaudhry Nouman Ali
A rule-based automated plan approval system of single-story timber homes according to the NZ building code using CNN and GAN
The purpose of this research is to automate the plan approval process for residential homes in New Zealand by developing a software that integrates Convolutional Neural Networks (CNN) and Generative Adversarial Networks (GAN). These AI technologies will be used to analyze building plans and ensure compliance with the New Zealand Building Code. The research aims to streamline the plan approval process by reducing the manual workload, thereby enhancing the efficiency of the construction sector in New Zealand. This project offers significant advancements in AI applications within the construction industry. The expected outcome is a prototype AI system capable of automatically reviewing and approving building plans. This system will transform current practices, benefiting architects, builders, and regulatory authorities by providing a more efficient and accurate plan approval process. Many AI applications in the construction industry have been developed in the last decade, driven by increased computational power from high-performing GPUs, advanced machine learning (ML) and deep learning (DL) algorithms, and modern programming languages. The construction industry in New Zealand faces challenges in ensuring a fast and accurate building plan approval process, which is predominantly manual, time-consuming, and prone to human error. AI integration in this process is not just a futuristic vision but a current reality with implications for efficiency, decision-making, and project outcomes. AI's impact is evident in various phases of construction management, from automating routine tasks to providing predictive analytics. For example, Autodesk's Construction IQ demonstrates how AI can swiftly analyze data and offer precise insights that enhance workflow efficiency. The New Zealand Building Code enforces strict standards for construction safety and quality, which are complex to interpret during plan approvals. Using AI in this process promises to reduce delays and ensure higher compliance standards.
Supervisors
Qualifications
MPhil Computer Science, Lahore Leads University Pakistan, 2022
Bachelor of Science (Hons) in Computer Science, University of the Punjab Pakistan, 2017
Presentations
1. ICCET - International Conference on Computing & Emerging Technologies, 27 May 2023, "Roles of Sentiment Analysis in Social Media."
2. ICACS - International Conference on Advancements in Computational Sciences, 22 Feb 2023, "Cyber security intrusion detection using deep learning approaches, datasets, Bot-IOT dataset."
Publications
Hussain, Ayaz, Hanan Sharif, Faisal Rehman, Hina Kirn, Ashina Sadiq, Muhammad Shahzad Khan, Amjad Riaz, Chaudhry Nouman Ali, and Adil Hussain Chandio. "A Systematic Review of Intrusion Detection Systems in Internet of Things Using ML and DL." In 2023 4th International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), pp. 1-5. IEEE, 2023.
Manan, Iram, Faisal Rehman, Hanan Sharif, Chaudhry Nouman Ali, Rana Rashid Ali, and Amiad Liaqat. "Cyber security intrusion detection using deep learning approaches, datasets, Bot-IOT dataset." In 2023 4th international conference on advancements in computational sciences (ICACS), pp. 1-5. IEEE, 2023.
Khalid, Muhammad Hassaan, Hanan Sharif, Faisal Rehman, Muhammad Naeem Ullah, Shahbaz Shaukat, Hadia Maqsood, Chaudhry Nouman Ali, Ayaz Hussain, and Irfana Iftikhar. "A brief overview of deep learning approaches for IoT security." In 2023 4th International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), pp. 1-5. IEEE, 2023.
Sharif, Hanan, Faisal Rehman, Amina Rida, Chaudhry Nouman Ali, Rana Zeeshan Zulfiqar, Salman Akram, Hina Kirn, Ayaz Hussain, and Razia Iftikhar. "Application of Artificial Neural Networks inSatellite Imaging–A Systematic Review." In 2023 4th International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), pp. 1-5. IEEE, 2023.
Shakeel, Hafsa, Hanan Sharif, Faisal Rehman, Bilal Rasool, Azher Mahmood, Hadia Maqsood, Hina Kirn, Chaudhry Nouman Ali, and Muhammad Bilal. "Machine Learning in Banking Risk Management-A Brief Overview." In 2023 4th International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), pp. 1-5. IEEE, 2023.
Humayoun, Muneeba, Hanan Sharif, Faisal Rehman, Shahbaz Shaukat, Muhbat Ullah, Hadia Maqsood, Chaudhry Nouman Ali, Razia Iftikhar, and Adil Hussain Chandio. "From Cloud Down to Things: An Overview of Machine Learning in Internet of Things." In 2023 4th International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), pp. 1-5. IEEE, 2023.
Sharif, Hanan, Faisal Rehman, Amina Rida, Usman Nawaz, Chaudhry Nouman Ali, Hira Akram, and Ammara Zahid. "A quick review on cardiac image segmentation." In 2022 International Conference on IT and Industrial Technologies (ICIT), pp. 01-05. IEEE, 2022.
Yaqoob, Alina, Faisal Rehman, Hanan Sharif, Muhammad Hamza Mahmood, Shahid Sharif, Awais Ahmad, Chaudhry Nouman Ali, Ayaz Hussain, and Malhar Khan. "Skip Connections' Importance in Biomedical Image Segmentation." In 2023 4th International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), pp. 1-5. IEEE, 2023.
Awards
1. Distinguished Performance award on getting 3.9/4.0 CGPA in MPhil
2. Workshop completion certificate on Generative Artificial Intelligence