Artificial intelligence in civil engineering technicial seminar ppt
- 1. A Technical Seminar On The Topic ARTIFICIAL INTELLIGENCE IN CIVIL ENGINEERING UNDER THE GUIDENCE OF PRESENTED BY 1
- 2. CONTENTS 1. Introduction 2. History of AI 3. Importance of AI in civil engineering 4. Application of AI in civil engineering 5. Future trends 6. Advantages 7. Disadvantages 8. Conclusion 9. Reference 2
- 3. INTRODUCTION • Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. •The field of artificial intelligence, or AI, attempts to understand intelligent entities as well as construct them to make the operation reasonably simple and easy, correct and precise. •AI deals with machines that perform functions, which require intelligence. •Using the concept of the artificial intelligence makes the field of civil engineering more accurate, precise and efficient especially in the fields of smart materials and many more •AI helps in automated data collection and data analysis techniques to improve several aspects of construction engineering and management for productivity assessment, safety management, idle time reduction, prediction, risk analysis, decision-making and optimizing construction costs 3
- 4. HISTORY OF AI The term Artificial Intelligence was coined by John McCarthy Alan Turings Turing machine was the first know machine that used AI They failed to recognize the difficulty of some of the remaining tasks during 1970’s In the early 1980s, AI research was revived and slowly started growing fron there and By 2000, AI solutions were being widely used Japan was highly invested in AI, which Inspied other countries like US and UK to Invest In a 2017 survey, one in five companies reported they had "incorporated AI in some offerings or processes" 4
- 5. IMPORTANCE OF AI IN CIVIL ENGINEERING •The traditional methods used for modeling and optimizing complex structural systems consume considerable time and computing resources. But AI-based algorithms provide better alternatives to solve problems in civil engineering. •AI algorithms have the potential to help the construction sector overcome challenges and improve overall productivity and efficiency. •The data required to develop AI algorithms are obtained using programmed machines like drones, smart cameras, smart sensors, etc. The data is analyzed to determine all possible construction aberrations and anomalies. • AI algorithms also use trial and error methods to identify the best process that needs to be followed depending on the site Using the concept of the artificial intelligence makes the field of civil engineering more accurate, precise and efficient especially in the fields of smart materials and many more 5
- 6. APPLICATION OF AI IN CIVIL ENGINEERING 1. Structural health monitoring • Embedding sensors- monitor stress and damage can reduce maintenance cost and increase lifespan • Used in over 40 bridges worldwide 2. Self repair materials • Embedding thin tubes containing uncured resin • Due to damage these tubes break, exposing the resin which fills any damage and sets • It is important in inaccessible environments such as underwater or in space 6
- 7. 3. Structural engineering • Used to evaluate durability • Smart materials or structures are restricted to sensing • They adapt to their surrounding environment • Monitor the integrity of bridges, dams, offshore oil drilling towers etc. 7
- 8. 8 4. Waste management • Challenging, expensive and time consuming task • Smart material helps to automate the process • Even it shows a role in food waste management
- 9. 5. Concrete mix design • Based on the principle of workability of concrete, desired strength and durability of concrete which in turn is governed by water cement ratio law • Strength of concrete determined by the characteristics of mortar and coarse aggregate 9
- 10. 10 6. Estimation • Suited for developing decision aids with analogy based problem solving capabilities
- 11. 7.Construction robot fleet management system 11 Construction robot fleet management
- 12. 8. Intelligent planning of construction project • Represent knowledge about how to generate plans • Researchers Kartam and Levitt, have chosen the system for interactive planning and execution (SIPE) 12
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- 14. 9. Bridge planning using GIS and Expert system approach • GIS and expert systems - two methodologies in comparing candidate site and candidate type • Computation power and quantitative comparison can be done faster 14 Bridge planning using GIS and expert system approach
- 15. 10. AI approach for pavement maintenance • Selecting an appropriate maintenance and repair action for a defected pavement • Done by collecting condition data, analysing and selecting appropriate maintenance and repair actions 21 15
- 16. 16 11. ANN for EHS • Robot carrying out tasks in construction • Accidents would potentially be zero because of the lack of human errors
- 17. 12. Tidal forecasting • Important factor in determining constructions or activity in maritime areas 17
- 18. 18 13. Predict and Protect against natural disasters • Can predict future disasters and also protect and minimize the damage • Helps in the design of structures to safeguard against earthquakes and other natural disasters
- 19. FUTURETRENDS 1. Fuzzy processing, integrated intelligent technology and intelligent emotion technology in civil engineering 2. Hybrid intelligence system and a large civil expert system approach 3. would besed in many areas of civil engineering 19
- 20. ADVANTAGES 1. Reduce the risk of accidents in the workplace 2. Not affected by hostile environments 3. Can replace tiresome tasks 4. Don’t need break at work time 20
- 21. DISADVANTAGES 1. Can be very expensive 2. Not able to work outside of what they are programmed to do 3. Unemployment may rise 4. Robots do not get better with experience…yet 21
- 22. CONCLUSION 1. Applied to many civil engineering areas 2. Plays a major role in constructing and maintaining different aspects of civil engineering problems 3. Perform better than the conventional methods 4. Help inexperienced users solve engineering problems and experienced users to improve the work efficiency 5. Powerful and practical tool for solving many problems in civil engineering field 6. Instruments based on the algorithms and database to reduce the efforts and cost of construction and management 22
- 23. REFERENCE 1. Akshata Patil, Lata Patted, Mahesh Tenagi, Vaishnavi Jahagirdar, Madhuri Patil and Rahul Gautam(2017), “Artificial Intelligence as a Tool in Civil Engineering- A Review”, IOSR Journal of Computer Engineering 2. Artificial intelligence, 2012, http://en.wikipedia.org/wiki/Artificial_intelligence 3. Pengzhen Lu, Shengyong Chen and Yujun Zheng (2012), “Artificial intelligence in Civil engineering, Mathematical Problems in Engineering”, Volume 2012, Article ID 145974, 22 pages http://dx.doi.org/10.1155/2012/145974 4. P. Krcaronemen and Z. Kouba, “Ontology-driven information system design,” IEEE Transactions on Systems, Man and Cybernetics C, vol. 42, no. 3, 2012 5. R. Bendaña, A. Del Caño, and M. P. De La Cruz, “Contractor selection: Fuzzy-control approach,” Canadian Journal of Civil Engineering, vol. 35, no. 5, pp. 473–486, 2008 23
- 24. 6. http://ai.business/2016/11/23/10-use-cases-of-ai-in-the-field-of-construction 7. Jeng, D. S.; Cha, D. H.; Blumenstein, M. “Application of Neural Networks in Civil Engineering Problems.” // Proceedings of the International Conference on Advances in the Internet, Processing, Systems and Interdisciplinary Research, 2003 8. A. Khalafallah and M. Abdel-Raheem, “Electimize: new evolutionary algorithm for optimization with application in construction engineering,” Journal of Computing in Civil Engineering, vol. 25, no. 3, pp. 192–201, 2011 9. M. Rezania, A. A. Javadi, and O. Giustolisi, “An evolutionary-based data mining technique for assessment of civil engineering systems,” Engineering Computations (Swansea, Wales), vol. 25, no. 6, pp. 500–517, 2008 10. S. Sharma and A. Das, “Backcalculation of pavement layer moduli from falling weight deflectometer data using an artificial neural network,” Canadian Journal of Civil Engineering, vol. 35, no. 1, pp. 57–66, 2008 24
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