Target Audience:

Civil Engineering/Architecture/Urban Planning/Interdisciplinary students (at all levels), Field practitioners working in the areas related to civil engineering or similar, Academicians at any level.

Problem Statement:

The world at present is at the tipping point as far as the application of Artificial Intelligence (AI) is concerned. AI is gradually penetrating traditional sectors and making a real difference in lives and processes. 

Civil Engineering, the oldest discipline of engineering, has tremendous potential for applying emerging methods and technologies. According to a study by Markets and Market, the Application of AI into Civil Engineering is a 339 Million USD market growing at a CAGR of 34%. This presents a huge market opportunity for stakeholders. 

Now is the right time to utilize the state-of-the-art development of artificial intelligence and machine learning to accelerate the growth rate of Civil Engineering. 

Identify a problem/process/technique that can be improved by applying Machine Learning / Artificial Intelligence. Describe in detail how you think that the problem mentioned is suitable for using ML/ AI. Any original research/ study done in the past or ongoing are also welcomed.

One example will be to utilize the historical data to predict the CBR value for soil using sieve analysis and density measurements without testing it. 

Ideal Submission: 

Ideal submission should have a write-up stating the issues/ challenges with current practices, detailed proposed solution, limitations and expected outcome, and the predicted impact’s measurable magnitude. The topic of writeup shall target a commonly encountered problem that lacks practical conventional solutions and has tangible benefits for a viable solution.

An ideal submission should look like an abstract of a paper. And should be in such a way that others can easily implement.

Candidates are expected to adhere to the following guidelines: – 

https://www.sciencebuddies.org/science-fair-projects/science-fair/how-to-format-a-research-paper

Criteria: 

• Ubiquitous nature of problem selected & Novelty of the proposed solution. If the solution is readily available on the internet, it will gain less weightage. 
• Scalability of the proposed solutions. If the solution can impact the wider population, it will be given more weightage.